Merge pull request #25598 from pjhwa/outdated2-25522

Update outdated kubernetes-api.md file in the dev-1.19-ko.7
2020-12-14 21:47:48 -08:00 · 2020-12-14 07:23:12 +00:00 · 2020-12-13 16:45:27 -08:00 · 2020-12-14 06:46:21 +09:00 · 2020-12-08 14:19:33 -08:00 · 2020-12-07 14:01:15 -06:00
1243 changed files with 30463 additions and 138030 deletions
@@ -1,15 +0,0 @@
---
-name: Scheduled Netlify site build
-on:
-  schedule: # Build twice daily: shortly after midnight and noon (UTC)
-            # Offset is to be nice to the build service
-  - cron: '4 0,12 * * *'
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-    - name: Trigger build on Netlify
-      env:
-        TOKEN: ${{ secrets.NETLIFY_BUILD_HOOK_KEY }}
-      run: >-
-          curl -s -H "Accept: application/json" -H "Content-Type: application/json" -X POST -d "{}" "https://api.netlify.com/build_hooks/${TOKEN}"
@@ -1,6 +1,3 @@
 [submodule "themes/docsy"]
 	path = themes/docsy
 	url = https://github.com/google/docsy.git
-[submodule "api-ref-generator"]
-	path = api-ref-generator
-	url = https://github.com/kubernetes-sigs/reference-docs
@@ -4,7 +4,7 @@
 # change is that the Hugo version is now an overridable argument rather than a fixed
 # environment variable.

-FROM golang:1.15-alpine
+FROM alpine:latest

 LABEL maintainer="Luc Perkins <lperkins@linuxfoundation.org>"

@@ -58,7 +58,7 @@ docker-serve:
 	@echo -e "$(CCRED)**** The use of docker-serve is deprecated. Use container-serve instead. ****$(CCEND)"
 	$(MAKE) container-serve

-container-image: ## Build a container image for the preview of the website
+container-image:
 	$(CONTAINER_ENGINE) build . \
 		--network=host \
 		--tag $(CONTAINER_IMAGE) \
@@ -67,7 +67,7 @@ container-image: ## Build a container image for the preview of the website
 container-build: module-check
 	$(CONTAINER_RUN) --read-only --mount type=tmpfs,destination=/tmp,tmpfs-mode=01777 $(CONTAINER_IMAGE) sh -c "npm ci && hugo --minify"

-container-serve: module-check ## Boot the development server using container. Run `make container-image` before this.
+container-serve: module-check
 	$(CONTAINER_RUN) --read-only --mount type=tmpfs,destination=/tmp,tmpfs-mode=01777 -p 1313:1313 $(CONTAINER_IMAGE) hugo server --buildFuture --bind 0.0.0.0 --destination /tmp/hugo --cleanDestinationDir

 test-examples:
@@ -85,10 +85,3 @@ docker-internal-linkcheck:
 container-internal-linkcheck: link-checker-image-pull
 	$(CONTAINER_RUN) $(CONTAINER_IMAGE) hugo --config config.toml,linkcheck-config.toml --buildFuture
 	$(CONTAINER_ENGINE) run --mount type=bind,source=$(CURDIR),target=/test --rm wjdp/htmltest htmltest
-
-clean-api-reference: ## Clean all directories in API reference directory, preserve _index.md
-	rm -rf content/en/docs/reference/kubernetes-api/*/
-
-api-reference: clean-api-reference ## Build the API reference pages. go needed
-	cd api-ref-generator/gen-resourcesdocs && \
-		go run cmd/main.go kwebsite --config-dir config/v1.20/ --file api/v1.20/swagger.json --output-dir ../../content/en/docs/reference/kubernetes-api --templates templates
@@ -7,10 +7,12 @@ aliases:
    - mrbobbytables
  sig-docs-blog-reviewers: # Reviewers for blog content
    - castrojo
+    - cody-clark
    - kbarnard10
    - mrbobbytables
    - onlydole
-    - sftim
+    - parispittman
+    - vonguard
  sig-docs-de-owners: # Admins for German content
    - bene2k1
    - mkorbi
@@ -28,7 +30,6 @@ aliases:
    - kbarnard10
    - kbhawkey
    - onlydole
-    - reylejano
    - savitharaghunathan
    - sftim
    - steveperry-53
@@ -93,21 +94,14 @@ aliases:
    - daminisatya
    - mittalyashu
  sig-docs-id-owners: # Admins for Indonesian content
-    - ariscahyadi
-    - danninov
    - girikuncoro
-    - habibrosyad
    - irvifa
-    - phanama
-    - wahyuoi
  sig-docs-id-reviews: # PR reviews for Indonesian content
-    - ariscahyadi
-    - danninov
    - girikuncoro
-    - habibrosyad
    - irvifa
-    - phanama
    - wahyuoi
+    - phanama
+    - danninov
  sig-docs-it-owners: # Admins for Italian content
    - fabriziopandini
    - Fale
@@ -144,7 +138,6 @@ aliases:
    - seokho-son
    - ysyukr
    - pjhwa
-    - yoonian
  sig-docs-leads: # Website chairs and tech leads
    - irvifa
    - jimangel
@@ -176,20 +169,14 @@ aliases:
    # zhangxiaoyu-zidif
  sig-docs-pt-owners: # Admins for Portuguese content
    - femrtnz
-    - jailton
    - jcjesus
    - devlware
    - jhonmike
-    - rikatz
-    - yagonobre
  sig-docs-pt-reviews: # PR reviews for Portugese content
    - femrtnz
-    - jailton
    - jcjesus
    - devlware
    - jhonmike
-    - rikatz
-    - yagonobre
  sig-docs-vi-owners: # Admins for Vietnamese content
    - huynguyennovem
    - ngtuna
@@ -227,12 +214,3 @@ aliases:
    - idvoretskyi
    - MaxymVlasov
    - Potapy4
-  # authoritative source: git.k8s.io/community/OWNERS_ALIASES
-  committee-steering: # provide PR approvals for announcements
-    - cblecker
-    - derekwaynecarr
-    - dims
-    - liggitt
-    - mrbobbytables
-    - nikhita
-    - parispittman
@@ -14,9 +14,9 @@ Sobald Ihre Pull-Anfrage erstellt wurde, übernimmt ein Rezensent von Kubernetes
 Weitere Informationen zum Beitrag zur Kubernetes-Dokumentation finden Sie unter:

 * [Mitwirkung beginnen](https://kubernetes.io/docs/contribute/start/)
-* [Ihre Dokumentationsänderungen bereitstellen](https://kubernetes.io/docs/contribute/intermediate#view-your-changes-locally)
-* [Seitenvorlagen verwenden](https://kubernetes.io/docs/contribute/style/page-content-types/)
-* [Dokumentationsstil-Handbuch](https://kubernetes.io/docs/contribute/style/style-guide/)
+* [Ihre Dokumentationsänderungen bereitstellen](http://kubernetes.io/docs/contribute/intermediate#view-your-changes-locally)
+* [Seitenvorlagen verwenden](http://kubernetes.io/docs/contribute/style/page-content-types/)
+* [Dokumentationsstil-Handbuch](http://kubernetes.io/docs/contribute/style/style-guide/)
 * [Übersetzung der Kubernetes-Dokumentation](https://kubernetes.io/docs/contribute/localization/)

 ## `README.md`'s Localizing Kubernetes Documentation
@@ -65,7 +65,7 @@ Dadurch wird der lokale Hugo-Server an Port 1313 gestartet. Öffnen Sie Ihren Br

 ## Community, Diskussion, Beteiligung und Unterstützung

-Erfahren Sie auf der [Community-Seite](https://kubernetes.io/community/) wie Sie mit der Kubernetes-Community interagieren können.
+Erfahren Sie auf der [Community-Seite](http://kubernetes.io/community/) wie Sie mit der Kubernetes-Community interagieren können.

 Sie können die Betreuer dieses Projekts unter folgender Adresse erreichen:

@@ -17,9 +17,9 @@ Los revisores harán todo lo posible para proporcionar toda la información nece
 Para obtener más información sobre cómo contribuir a la documentación de Kubernetes, puede consultar:

 * [Empezando a contribuir](https://kubernetes.io/docs/contribute/start/)
-* [Visualizando sus cambios en su entorno local](https://kubernetes.io/docs/contribute/intermediate#view-your-changes-locally)
-* [Utilizando las plantillas de las páginas](https://kubernetes.io/docs/contribute/style/page-content-types/)
-* [Guía de estilo de la documentación](https://kubernetes.io/docs/contribute/style/style-guide/)
+* [Visualizando sus cambios en su entorno local](http://kubernetes.io/docs/contribute/intermediate#view-your-changes-locally)
+* [Utilizando las plantillas de las páginas](http://kubernetes.io/docs/contribute/style/page-content-types/)
+* [Guía de estilo de la documentación](http://kubernetes.io/docs/contribute/style/style-guide/)
 * [Traduciendo la documentación de Kubernetes](https://kubernetes.io/docs/contribute/localization/)

 ## Levantando el sitio web kubernetes.io en su entorno local con Docker
@@ -30,17 +30,6 @@ El método recomendado para levantar una copia local del sitio web kubernetes.io

 > Si prefiere levantar el sitio web sin utilizar **Docker**, puede seguir las instrucciones disponibles en la sección [Levantando kubernetes.io en local con Hugo](#levantando-kubernetesio-en-local-con-hugo).

-**`Nota`: Para el procedimiento de construir una imagen de Docker e iniciar el servidor.**
-El sitio web de Kubernetes utiliza Docsy Hugo theme. Se sugiere que se instale si aún no se ha hecho, los **submódulos** y otras dependencias de herramientas de desarrollo ejecutando el siguiente comando de `git`:
-
-```bash
-# pull de los submódulos del repositorio
-git submodule update --init --recursive --depth 1
-
-```
-
-Si identifica que `git` reconoce una cantidad innumerable de cambios nuevos en el proyecto, la forma más simple de solucionarlo es cerrando y volviendo a abrir el proyecto en el editor. Los submódulos son automáticamente detectados por `git`, pero los plugins usados por los editores pueden tener dificultades para ser cargados.
-
 Una vez tenga Docker [configurado en su máquina](https://www.docker.com/get-started), puede construir la imagen de Docker `kubernetes-hugo` localmente ejecutando el siguiente comando en la raíz del repositorio:

 ```bash
@@ -84,4 +73,4 @@ La participación en la comunidad de Kubernetes está regulada por el [Código d

 Kubernetes es posible gracias a la participación de la comunidad y la documentación es vital para facilitar el acceso al proyecto.

-Agradecemos muchísimo sus contribuciones a nuestro sitio web y nuestra documentación.
+Agradecemos muchísimo sus contribuciones a nuestro sitio web y nuestra documentación.
@@ -1,193 +1,76 @@
 # A documentação do Kubernetes

-[![Netlify Status](https://api.netlify.com/api/v1/badges/be93b718-a6df-402a-b4a4-855ba186c97d/deploy-status)](https://app.netlify.com/sites/kubernetes-io-master-staging/deploys) [![GitHub release](https://img.shields.io/github/release/kubernetes/website.svg)](https://github.com/kubernetes/website/releases/latest)
+[![Build Status](https://api.travis-ci.org/kubernetes/website.svg?branch=master)](https://travis-ci.org/kubernetes/website)
+[![GitHub release](https://img.shields.io/github/release/kubernetes/website.svg)](https://github.com/kubernetes/website/releases/latest)

-Bem-vindos! Este repositório contém todos os recursos necessários para criar o [website e documentação do Kubernetes](https://kubernetes.io/). Estamos muito satisfeitos por você querer contribuir!
+Bem vindos! Este repositório abriga todos os recursos necessários para criar o [site e documentação do Kubernetes](https://kubernetes.io/). Estamos muito satisfeitos por você querer contribuir!

-# Utilizando este repositório
+## Contribuindo com os documentos

-Você pode executar o website localmente utilizando o Hugo (versão Extended), ou você pode executa-ló em um container runtime. É altamente recomendável utilizar um container runtime, pois garante a consistência na implantação do website real.
+Você pode clicar no botão **Fork** na área superior direita da tela para criar uma cópia desse repositório na sua conta do GitHub. Esta cópia é chamada de *fork*. Faça as alterações desejadas no seu fork e, quando estiver pronto para enviar as alterações para nós, vá até o fork e crie uma nova solicitação de pull para nos informar sobre isso.

-## Pré-requisitos
-
-Para usar este repositório, você precisa instalar:
-
- [npm](https://www.npmjs.com/)
- [Go](https://golang.org/)
- [Hugo (versão Extended)](https://gohugo.io/)
- Um container runtime, por exemplo [Docker](https://www.docker.com/).
-
-Antes de você iniciar, instale as dependências, clone o repositório e navegue até o diretório:
-
-```
-git clone https://github.com/kubernetes/website.git
-cd website
-```
-
-O website do Kubernetes utiliza o [tema Docsy Hugo](https://github.com/google/docsy#readme). Mesmo se você planeje executar o website em um container, é altamente recomendado baixar os submódulos e outras dependências executando o seguinte comando:
-
-```
-# Baixar o submódulo Docsy
-git submodule update --init --recursive --depth 1
-```
-
-## Executando o website usando um container
-
-Para executar o build do website em um container, execute o comando abaixo para criar a imagem do container e executa-lá:
-
-```
-make container-image
-make container-serve
-```
-
-Abra seu navegador em http://localhost:1313 para visualizar o website. Conforme você faz alterações nos arquivos fontes, o Hugo atualiza o website e força a atualização do navegador.
-
-## Executando o website localmente utilizando o Hugo
-
-Consulte a [documentação oficial do Hugo](https://gohugo.io/getting-started/installing/) para instruções de instalação do Hugo. Certifique-se de instalar a versão do Hugo especificada pela variável de ambiente `HUGO_VERSION` no arquivo [`netlify.toml`](netlify.toml#L9).
-
-Para executar o build e testar o website localmente, execute:
-
-```bash
-# instalar dependências
-npm ci
-make serve
-```
-
-Isso iniciará localmente o Hugo na porta 1313. Abra o seu navegador em http://localhost:1313 para visualizar o website. Conforme você faz alterações nos arquivos fontes, o Hugo atualiza o website e força uma atualização no navegador.
-
-## Construindo a página de referência da API
-
-A página de referência da API localizada em `content/en/docs/reference/kubernetes-api` é construída a partir da especificação do Swagger utilizando https://github.com/kubernetes-sigs/reference-docs/tree/master/gen-resourcesdocs.
-
-Siga os passos abaixo para atualizar a página de referência para uma nova versão do Kubernetes:
-
-OBS: modifique o "v1.20" no exemplo a seguir pela versão a ser atualizada
-
-1. Obter o submódulo `kubernetes-resources-reference`:
-
-```
-git submodule update --init --recursive --depth 1
-```
-
-2. Criar a nova versão da API no submódulo e adicionar à especificação do Swagger:
-
-```
-mkdir api-ref-generator/gen-resourcesdocs/api/v1.20
-curl 'https://raw.githubusercontent.com/kubernetes/kubernetes/master/api/openapi-spec/swagger.json' > api-ref-generator/gen-resourcesdocs/api/v1.20/swagger.json
-```
-
-3. Copiar o sumário e os campos de configuração para a nova versão a partir da versão anterior:
-
-```
-mkdir api-ref-generator/gen-resourcesdocs/api/v1.20
-cp api-ref-generator/gen-resourcesdocs/api/v1.19/* api-ref-generator/gen-resourcesdocs/api/v1.20/
-```
-
-4. Ajustar os arquivos `toc.yaml` e `fields.yaml` para refletir as mudanças entre as duas versões.
-
-5. Em seguida, gerar as páginas:
-
-```
-make api-reference
-```
-
-Você pode validar o resultado localmente gerando e disponibilizando o site a partir da imagem do container:
-
-```
-make container-image
-make container-serve
-```
-
-Abra o seu navegador em http://localhost:1313/docs/reference/kubernetes-api/ para visualizar a página de referência da API.
-
-6. Quando todas as mudanças forem refletidas nos arquivos de configuração `toc.yaml` e `fields.yaml`, crie um pull request com a nova página de referência de API.
-
-## Troubleshooting
-### error: failed to transform resource: TOCSS: failed to transform "scss/main.scss" (text/x-scss): this feature is not available in your current Hugo version
-
-Por motivos técnicos, o Hugo é disponibilizado em dois conjuntos de binários. O website atual funciona apenas na versão **Hugo Extended**. Na [página de releases](https://github.com/gohugoio/hugo/releases) procure por arquivos com `extended` no nome. Para confirmar, execute `hugo version` e procure pela palavra `extended`.
-
-### Troubleshooting macOS for too many open files
-
-Se você executar o comando `make serve` no macOS e retornar o seguinte erro:
-
-```
-ERROR 2020/08/01 19:09:18 Error: listen tcp 127.0.0.1:1313: socket: too many open files
-make: *** [serve] Error 1
-```
-
-Verifique o limite atual para arquivos abertos:
-
-`launchctl limit maxfiles`
-
-Em seguida, execute os seguintes comandos (adaptado de https://gist.github.com/tombigel/d503800a282fcadbee14b537735d202c):
-
-```shell
-#!/bin/sh
-
-# Esse são os links do gist original, vinculados ao meu gists agora.
-# curl -O https://gist.githubusercontent.com/a2ikm/761c2ab02b7b3935679e55af5d81786a/raw/ab644cb92f216c019a2f032bbf25e258b01d87f9/limit.maxfiles.plist
-# curl -O https://gist.githubusercontent.com/a2ikm/761c2ab02b7b3935679e55af5d81786a/raw/ab644cb92f216c019a2f032bbf25e258b01d87f9/limit.maxproc.plist
-
-curl -O https://gist.githubusercontent.com/tombigel/d503800a282fcadbee14b537735d202c/raw/ed73cacf82906fdde59976a0c8248cce8b44f906/limit.maxfiles.plist
-curl -O https://gist.githubusercontent.com/tombigel/d503800a282fcadbee14b537735d202c/raw/ed73cacf82906fdde59976a0c8248cce8b44f906/limit.maxproc.plist
-
-sudo mv limit.maxfiles.plist /Library/LaunchDaemons
-sudo mv limit.maxproc.plist /Library/LaunchDaemons
-
-sudo chown root:wheel /Library/LaunchDaemons/limit.maxfiles.plist
-sudo chown root:wheel /Library/LaunchDaemons/limit.maxproc.plist
-
-sudo launchctl load -w /Library/LaunchDaemons/limit.maxfiles.plist
-```
-
-Esta solução funciona tanto para o MacOS Catalina quanto para o MacOS Mojave.
-
-### Erro de "Out of Memory"
-
-Se você executar o comando `make container-serve` e retornar o seguinte erro:
-```
-make: *** [container-serve] Error 137
-```
-
-Verifique a quantidade de memória disponível para o agente de execução de contêiner. No caso do Docker Desktop para macOS, abra o menu "Preferences..." -> "Resources..." e tente disponibilizar mais memória.
-
-# Comunidade, discussão, contribuição e apoio
-
-Saiba mais sobre a comunidade Kubernetes SIG Docs e reuniões na [página da comunidade](http://kubernetes.io/community/).
-
-Você também pode entrar em contato com os mantenedores deste projeto em:
-
- [Slack](https://kubernetes.slack.com/messages/sig-docs) ([Obter o convide para o este slack](https://slack.k8s.io/))
- [Mailing List](https://groups.google.com/forum/#!forum/kubernetes-sig-docs)
-
-# Contribuindo com os documentos
-
-Você pode clicar no botão **Fork** na área superior direita da tela para criar uma cópia desse repositório na sua conta do GitHub. Esta cópia é chamada de *fork*. Faça as alterações desejadas no seu fork e, quando estiver pronto para enviar as alterações para nós, vá até o fork e crie um novo **pull request** para nos informar sobre isso.
-
-Depois que seu **pull request** for criado, um revisor do Kubernetes assumirá a responsabilidade de fornecer um feedback claro e objetivo. Como proprietário do pull request, **é sua responsabilidade modificar seu pull request para atender ao feedback que foi fornecido a você pelo revisor do Kubernetes.**
-
-Observe também que você pode acabar tendo mais de um revisor do Kubernetes para fornecer seu feedback ou você pode acabar obtendo feedback de um outro revisor do Kubernetes diferente daquele originalmente designado para lhe fornecer o feedback.
-
-Além disso, em alguns casos, um de seus revisores pode solicitar uma revisão técnica de um [revisor técnico do Kubernetes](https://github.com/kubernetes/website/wiki/Tech-reviewers) quando necessário. Os revisores farão o melhor para fornecer feedbacks em tempo hábil, mas o tempo de resposta pode variar de acordo com as circunstâncias.
+Depois que seu **pull request** for criado, um revisor do Kubernetes assumirá a responsabilidade de fornecer um feedback claro e objetivo. Como proprietário do pull request, **é sua responsabilidade modificar seu pull request para abordar o feedback que foi fornecido a você pelo revisor do Kubernetes.** Observe também que você pode acabar tendo mais de um revisor do Kubernetes para fornecer seu feedback ou você pode acabar obtendo feedback de um revisor do Kubernetes que é diferente daquele originalmente designado para lhe fornecer feedback. Além disso, em alguns casos, um de seus revisores pode solicitar uma revisão técnica de um [revisor de tecnologia Kubernetes](https://github.com/kubernetes/website/wiki/Tech-reviewers) quando necessário. Os revisores farão o melhor para fornecer feedback em tempo hábil, mas o tempo de resposta pode variar de acordo com as circunstâncias.

 Para mais informações sobre como contribuir com a documentação do Kubernetes, consulte:

-* [Contribua com a documentação do Kubernetes](https://kubernetes.io/docs/contribute/)
-* [Tipos de conteúdo de página](https://kubernetes.io/docs/contribute/style/page-content-types/)
+* [Comece a contribuir](https://kubernetes.io/docs/contribute/start/)
+* [Preparando suas alterações na documentação](http://kubernetes.io/docs/contribute/intermediate#view-your-changes-locally)
+* [Usando Modelos de Página](http://kubernetes.io/docs/contribute/style/page-templates/)
 * [Guia de Estilo da Documentação](http://kubernetes.io/docs/contribute/style/style-guide/)
 * [Localizando documentação do Kubernetes](https://kubernetes.io/docs/contribute/localization/)

-Você pode contatar os mantenedores da localização em Português em:
+Você pode contactar os mantenedores da localização em Português em:

 * Felipe ([GitHub - @femrtnz](https://github.com/femrtnz))
 * [Slack channel](https://kubernetes.slack.com/messages/kubernetes-docs-pt)

-# Código de conduta
+## Executando o site localmente usando o Docker
+
+A maneira recomendada de executar o site do Kubernetes localmente é executar uma imagem especializada do [Docker](https://docker.com) que inclui o gerador de site estático [Hugo](https://gohugo.io).
+
+> Se você está rodando no Windows, você precisará de mais algumas ferramentas que você pode instalar com o [Chocolatey](https://chocolatey.org). `choco install make`
+
+> Se você preferir executar o site localmente sem o Docker, consulte [Executando o site localmente usando o Hugo](#executando-o-site-localmente-usando-o-hugo) abaixo.
+
+Se você tiver o Docker [em funcionamento](https://www.docker.com/get-started), crie a imagem do Docker do `kubernetes-hugo` localmente:
+
+```bash
+make container-image
+```
+
+Depois que a imagem foi criada, você pode executar o site localmente:
+
+```bash
+make container-serve
+```
+
+Abra seu navegador para http://localhost:1313 para visualizar o site. Conforme você faz alterações nos arquivos de origem, Hugo atualiza o site e força a atualização do navegador.
+
+## Executando o site localmente usando o Hugo
+
+Veja a [documentação oficial do Hugo](https://gohugo.io/getting-started/installing/) para instruções de instalação do Hugo. Certifique-se de instalar a versão do Hugo especificada pela variável de ambiente `HUGO_VERSION` no arquivo [`netlify.toml`](netlify.toml#L9).
+
+Para executar o site localmente quando você tiver o Hugo instalado:
+
+```bash
+make serve
+```
+
+Isso iniciará o servidor Hugo local na porta 1313. Abra o navegador para http://localhost:1313 para visualizar o site. Conforme você faz alterações nos arquivos de origem, Hugo atualiza o site e força a atualização do navegador.
+
+## Comunidade, discussão, contribuição e apoio
+
+Aprenda a se envolver com a comunidade do Kubernetes na [página da comunidade](http://kubernetes.io/community/).
+
+Você pode falar com os mantenedores deste projeto:
+
+- [Slack](https://kubernetes.slack.com/messages/sig-docs)
+- [Mailing List](https://groups.google.com/forum/#!forum/kubernetes-sig-docs)
+
+### Código de conduta

 A participação na comunidade Kubernetes é regida pelo [Código de Conduta da Kubernetes](code-of-conduct.md).

-# Obrigado!
+## Obrigado!

-O Kubernetes prospera com a participação da comunidade e nós realmente agradecemos suas contribuições para o nosso website e nossa documentação!
+O Kubernetes conta com a participação da comunidade e nós realmente agradecemos suas contribuições para o nosso site e nossa documentação!
@@ -2,117 +2,38 @@

 [![Netlify Status](https://api.netlify.com/api/v1/badges/be93b718-a6df-402a-b4a4-855ba186c97d/deploy-status)](https://app.netlify.com/sites/kubernetes-io-master-staging/deploys) [![GitHub release](https://img.shields.io/github/release/kubernetes/website.svg)](https://github.com/kubernetes/website/releases/latest)

-Данный репозиторий содержит все необходимые файлы для сборки [сайта Kubernetes и документации](https://kubernetes.io/). Мы благодарим вас за желание внести свой вклад!
+Добро пожаловать! Данный репозиторий содержит все необходимые файлы для сборки [сайта Kubernetes и документации](https://kubernetes.io/). Мы благодарим вас за старания!

-# Использование этого репозитория
-
-Запустить сайт локально можно с помощью Hugo (Extended version) или же в исполняемой среде для контейнеров. Мы настоятельно рекомендуем воспользоваться контейнерной средой, поскольку она обеспечивает консистивность развёртывания с оригинальным сайтом.
-
-## Предварительные требования
-
-Чтобы работать с этим репозиторием, понадобятся следующие компоненты, установленные локально:
-
- [npm](https://www.npmjs.com/)
- [Go](https://golang.org/)
- [Hugo (Extended version)](https://gohugo.io/)
- Исполняемая среда для контейнеров вроде [Docker](https://www.docker.com/)
-
-Перед тем, как начать, установите зависимости. Склонируйте репозиторий и перейдите в его директорию:
-
-```
-git clone https://github.com/kubernetes/website.git
-cd website
-```
-
-Сайт Kubernetes использует [тему для Hugo под названием Docsy](https://github.com/google/docsy). Даже если вы планируете запускать сайт в контейнере, мы настоятельно рекомендуем загрузить соответствующий подмодуль и другие зависимости для разработки, выполнив следующую команду:
-
-```
-# загружаем Git-подмодуль Docsy
-git submodule update --init --recursive --depth 1
-```
-
-## Запуск сайта в контейнере
-
-Чтобы собрать сайт в контейнере, выполните следующие команды — они собирают образ контейнера и запускают его:
-
-```
-make container-image
-make container-serve
-```
-
-Откройте браузер и перейдите по ссылке http://localhost:1313, чтобы увидеть сайт. Если вы отредактируете исходные файлы сайта, Hugo автоматически обновит сам сайт и выполнит обновление страницы в браузере.
- 
 ## Запуск сайта с помощью Hugo

-Убедитесь, что вы установили расширенную версию Hugo (extended version): она определена в переменной окружения `HUGO_VERSION` в файле [`netlify.toml`](netlify.toml#L10).
+Обратитесь к [официальной документации Hugo](https://gohugo.io/getting-started/installing/), чтобы установить Hugo. Убедитесь, что вы установили правильную версию Hugo, которая устанавливается в переменной окружения `HUGO_VERSION` в файле [`netlify.toml`](netlify.toml#L10).

-Чтобы собрать и протестировать сайт локально, выполните:
+После установки Hugo, чтобы запустить сайт, выполните в консоли:

 ```bash
-# install dependencies
-npm ci
-make serve
+git clone https://github.com/kubernetes/website.git
+cd website
+hugo server --buildFuture
 ```

-Эти команды запустят локальный сервер Hugo на порту 1313. Откройте браузер и перейдите по ссылке http://localhost:1313, чтобы увидеть сайт. Если вы отредактируете исходные файлы сайта, Hugo автоматически обновит сам сайт и выполнит обновление страницы в браузере.
+Эта команда запустит сервер Hugo на порту 1313. Откройте браузер и перейдите по ссылке http://localhost:1313, чтобы открыть сайт. Если вы отредактируете исходные файлы сайта, Hugo автоматически применит изменения и обновит страницу в браузере.

-## Решение проблем
-### error: failed to transform resource: TOCSS: failed to transform "scss/main.scss" (text/x-scss): this feature is not available in your current Hugo version
+## Сообщество, обсуждение, вклад и поддержка

-По техническим причинам Hugo поставляется с двумя наборами бинарников. Текущий сайт Kubernetes работает только в версии **Hugo Extended**. На [странице релизов](https://github.com/gohugoio/hugo/releases) ищите архивы со словом `extended` в названии. Чтобы убедиться в корректности, запустите команду `hugo version` и найдите в выводе слово `extended`.
+Узнайте, как поучаствовать в жизни сообщества Kubernetes на [странице сообщества](http://kubernetes.io/community/).

-### Решение проблемы на macOS с "too many open files"
+Вы можете связаться с сопровождающими этого проекта по следующим ссылкам:

-Если вы запускаете `make serve` на macOS и получаете следующую ошибку:
+- [Канал в Slack](https://kubernetes.slack.com/messages/sig-docs)
+- [Рассылка](https://groups.google.com/forum/#!forum/kubernetes-sig-docs)

-```
-ERROR 2020/08/01 19:09:18 Error: listen tcp 127.0.0.1:1313: socket: too many open files
-make: *** [serve] Error 1
-```
+## Вклад в документацию

-Попробуйте проверить текущий лимит для открытых файлов:
+Нажмите на кнопку **Fork** в правом верхнем углу, чтобы создать копию этого репозитория в ваш GitHub-аккаунт. Эта копия называется *форк-репозиторием*. Делайте любые изменения в вашем форк-репозитории, и когда вы будете готовы опубликовать изменения, откройте форк-репозиторий и создайте новый пулреквест, чтобы уведомить нас.

-`launchctl limit maxfiles`
+После того, как вы отправите пулреквест, ревьювер Kubernetes даст по нему обратную связь. Вы, как автор пулреквеста, **должны обновить свой пулреквест после его рассмотрения ревьювером Kubernetes.**

-Затем выполните следующие команды (они взяты и адаптированы из https://gist.github.com/tombigel/d503800a282fcadbee14b537735d202c):
-
-```shell
-#!/bin/sh
-
-# Ссылки на оригинальные gist-файлы закомментированы в пользу моих адаптированных.
-# curl -O https://gist.githubusercontent.com/a2ikm/761c2ab02b7b3935679e55af5d81786a/raw/ab644cb92f216c019a2f032bbf25e258b01d87f9/limit.maxfiles.plist
-# curl -O https://gist.githubusercontent.com/a2ikm/761c2ab02b7b3935679e55af5d81786a/raw/ab644cb92f216c019a2f032bbf25e258b01d87f9/limit.maxproc.plist
-
-curl -O https://gist.githubusercontent.com/tombigel/d503800a282fcadbee14b537735d202c/raw/ed73cacf82906fdde59976a0c8248cce8b44f906/limit.maxfiles.plist
-curl -O https://gist.githubusercontent.com/tombigel/d503800a282fcadbee14b537735d202c/raw/ed73cacf82906fdde59976a0c8248cce8b44f906/limit.maxproc.plist
-
-sudo mv limit.maxfiles.plist /Library/LaunchDaemons
-sudo mv limit.maxproc.plist /Library/LaunchDaemons
-
-sudo chown root:wheel /Library/LaunchDaemons/limit.maxfiles.plist
-sudo chown root:wheel /Library/LaunchDaemons/limit.maxproc.plist
-
-sudo launchctl load -w /Library/LaunchDaemons/limit.maxfiles.plist
-```
-
-Данное решение работает для macOS Catalina и Mojave.
-
-# Участие в SIG Docs
-
-Узнайте о Kubernetes-сообществе SIG Docs и его встречах на [странице сообщества](https://github.com/kubernetes/community/tree/master/sig-docs#meetings).
-
-Вы можете связаться с сопровождающими этот проект по следующим ссылкам:
-
- [Канал в Slack](https://kubernetes.slack.com/messages/sig-docs) ([получите приглашение в этот Slack](https://slack.k8s.io/))
- [Почтовая рассылка](https://groups.google.com/forum/#!forum/kubernetes-sig-docs)
-
-# Вклад в документацию
-
-Нажмите на кнопку **Fork** в правом верхнем углу, чтобы создать копию этого репозитория для вашего GitHub-аккаунта. Эта копия называется *форк-репозиторием*. Делайте любые изменения в своем форк-репозитории и, когда будете готовы опубликовать изменения, зайдите в свой форк-репозиторий и создайте новый pull-запрос (PR), чтобы уведомить нас.
-
-После того, как вы отправите pull-запрос, ревьювер из проекта Kubernetes даст по нему обратную связь. Вы, как автор pull-запроса, **должны обновить свой PR после его рассмотрения ревьювером Kubernetes.**
-
-Вполне возможно, что более одного ревьювера Kubernetes оставят свои комментарии. Может быть даже так, что вы будете получать обратную связь уже не от того ревьювера, что был первоначально вам назначен. Кроме того, в некоторых случаях один из ревьюверов может запросить техническую рецензию от [технического ревьювера Kubernetes](https://github.com/kubernetes/website/wiki/Tech-reviewers), если это потребуется. Ревьюверы сделают все возможное, чтобы как можно оперативнее оставить свои предложения и пожелания, но время ответа может варьироваться в зависимости от обстоятельств.
+Вполне возможно, что более одного ревьювера Kubernetes оставят свои комментарии или даже может быть так, что новый комментарий ревьювера Kubernetes будет отличаться от первоначального назначенного ревьювера. Кроме того, в некоторых случаях один из ревьюверов может запросить технический обзор у [технического ревьювера Kubernetes](https://github.com/kubernetes/website/wiki/Tech-reviewers), если это будет необходимо. Ревьюверы сделают все возможное, чтобы как можно оперативно оставить свои предложения и пожелания, но время ответа может варьироваться в зависимости от обстоятельств.

 Узнать подробнее о том, как поучаствовать в документации Kubernetes, вы можете по ссылкам ниже:

@@ -121,22 +42,21 @@ sudo launchctl load -w /Library/LaunchDaemons/limit.maxfiles.plist
 * [Руководство по оформлению документации](https://kubernetes.io/docs/contribute/style/style-guide/)
 * [Руководство по локализации Kubernetes](https://kubernetes.io/docs/contribute/localization/)

-# Файл `README.md` на других языках
-
+## Файл `README.md` на других языках
 |           другие языки        |       другие языки            |
 |-------------------------------|-------------------------------|
-| [Английский](README.md)       | [Немецкий](README-de.md)      |
-| [Вьетнамский](README-vi.md)   | [Польский]( README-pl.md)     |
-| [Индонезийский](README-id.md) | [Португальский](README-pt.md) |
-| [Испанский](README-es.md)     | [Украинский](README-uk.md)    |
-| [Итальянский](README-it.md)   | [Французский](README-fr.md)   |
-| [Китайский](README-zh.md)     | [Хинди](README-hi.md)         |
-| [Корейский](README-ko.md)     | [Японский](README-ja.md)      |
+| [Английский](README.md)       | [Французский](README-fr.md)   |
+| [Корейский](README-ko.md)     | [Немецкий](README-de.md)      |
+| [Португальский](README-pt.md) | [Хинди](README-hi.md)         |
+| [Испанский](README-es.md)     | [Индонезийский](README-id.md) |
+| [Китайский](README-zh.md)     | [Японский](README-ja.md)      |
+| [Вьетнамский](README-vi.md)   | [Итальянский](README-it.md)   |
+| [Польский]( README-pl.md)     | [Украинский](README-uk.md)    |

-# Кодекс поведения
+### Кодекс поведения

-Участие в сообществе Kubernetes регулируется [кодексом поведения CNCF](https://github.com/cncf/foundation/blob/master/code-of-conduct-languages/ru.md).
+Участие в сообществе Kubernetes регулируется [кодексом поведения CNCF](https://github.com/cncf/foundation/blob/master/code-of-conduct.md).

-# Спасибо!
+## Спасибо!

 Kubernetes процветает благодаря сообществу и мы ценим ваш вклад в сайт и документацию!
@@ -18,8 +18,7 @@
 ```bash
 git clone https://github.com/kubernetes/website.git
 cd website
-git submodule update --init --recursive --depth 1
-make serve
+hugo server --buildFuture
 ```

 <!-- This will start the local Hugo server on port 1313. Open up your browser to http://localhost:1313 to view the website. As you make changes to the source files, Hugo updates the website and forces a browser refresh. -->
@@ -83,4 +82,4 @@ make serve
 ## Дякуємо!

 <!-- Kubernetes thrives on community participation, and we appreciate your contributions to our website and our documentation! -->
-Долучення до спільноти - запорука успішного розвитку Kubernetes. Ми цінуємо ваш внесок у наш сайт і документацію!
+Долучення до спільноти - запорука успішного розвитку Kubernetes. Ми цінуємо ваш внесок у наш сайт і документацію!
@@ -228,8 +228,8 @@ For more information about contributing to the Kubernetes documentation, see:
 有关为 Kubernetes 文档做出贡献的更多信息，请参阅：

 * [贡献 Kubernetes 文档](https://kubernetes.io/docs/contribute/)
-* [页面内容类型](https://kubernetes.io/docs/contribute/style/page-content-types/)
-* [文档风格指南](https://kubernetes.io/docs/contribute/style/style-guide/)
+* [页面内容类型](http://kubernetes.io/docs/contribute/style/page-content-types/)
+* [文档风格指南](http://kubernetes.io/docs/contribute/style/style-guide/)
 * [本地化 Kubernetes 文档](https://kubernetes.io/docs/contribute/localization/)

 # 中文本地化
@@ -4,9 +4,6 @@

 This repository contains the assets required to build the [Kubernetes website and documentation](https://kubernetes.io/). We're glad that you want to contribute!

-+ [Contributing to the docs](#contributing-to-the-docs)
-+ [Localization ReadMes](#localization-readmemds)
-
 # Using this repository

 You can run the website locally using Hugo (Extended version), or you can run it in a container runtime. We strongly recommend using the container runtime, as it gives deployment consistency with the live website.
@@ -43,8 +40,6 @@ make container-image
 make container-serve
 ```

-If you see errors, it probably means that the hugo container did not have enough computing resources available. To solve it, increase the amount of allowed CPU and memory usage for Docker on your machine ([MacOSX](https://docs.docker.com/docker-for-mac/#resources) and [Windows](https://docs.docker.com/docker-for-windows/#resources)).
-
 Open up your browser to http://localhost:1313 to view the website. As you make changes to the source files, Hugo updates the website and forces a browser refresh.

 ## Running the website locally using Hugo
@@ -61,51 +56,6 @@ make serve

 This will start the local Hugo server on port 1313. Open up your browser to http://localhost:1313 to view the website. As you make changes to the source files, Hugo updates the website and forces a browser refresh.

-## Building the API reference pages
-
-The API reference pages located in `content/en/docs/reference/kubernetes-api` are built from the Swagger specification, using https://github.com/kubernetes-sigs/reference-docs/tree/master/gen-resourcesdocs.
-
-To update the reference pages for a new Kubernetes release (replace v1.20 in the following examples with the release to update to):
-
-1. Pull the `kubernetes-resources-reference` submodule:
-
-```
-git submodule update --init --recursive --depth 1
-```
-
-2. Create a new API revision into the submodule, and add the Swagger specification:
-
-```
-mkdir api-ref-generator/gen-resourcesdocs/api/v1.20
-curl 'https://raw.githubusercontent.com/kubernetes/kubernetes/master/api/openapi-spec/swagger.json' > api-ref-generator/gen-resourcesdocs/api/v1.20/swagger.json
-```
-
-3. Copy the table of contents and fields configuration for the new release from a previous one:
-
-```
-mkdir api-ref-generator/gen-resourcesdocs/api/v1.20
-cp api-ref-generator/gen-resourcesdocs/api/v1.19/* api-ref-generator/gen-resourcesdocs/api/v1.20/
-```
-
-4. Adapt the files `toc.yaml` and `fields.yaml` to reflect the changes between the two releases
-
-5. Next, build the pages:
-
-```
-make api-reference
-```
-
-You can test the results locally by making and serving the site from a container image:
-
-```
-make container-image
-make container-serve
-```
-
-In a web browser, go to http://localhost:1313/docs/reference/kubernetes-api/ to view the API reference.
-
-6. When all changes of the new contract are reflected into the configuration files `toc.yaml` and `fields.yaml`, create a Pull Request with the newly generated API reference pages.
-
 ## Troubleshooting
 ### error: failed to transform resource: TOCSS: failed to transform "scss/main.scss" (text/x-scss): this feature is not available in your current Hugo version

@@ -126,7 +76,7 @@ Try checking the current limit for open files:

 Then run the following commands (adapted from https://gist.github.com/tombigel/d503800a282fcadbee14b537735d202c):

-```shell
+```
 #!/bin/sh

 # These are the original gist links, linking to my gists now.
@@ -810,13 +810,6 @@ section#cncf {
  }
 }

-.td-search {
-  header > .header-filler {
-    height: $hero-padding-top;
-    background-color: black;
-  }
-}
-
 // Docs specific

 #editPageButton {
@@ -578,64 +578,3 @@ body.td-documentation {
  color: black;
  text-decoration: none !important;
 }
-
-@media print {
-  /* Do not print announcements */
-  #announcement, section#announcement, #fp-announcement, section#fp-announcement {
-    display: none;
-  }
-}
-
-#announcement, #fp-announcement {
-  > * {
-    color: inherit;
-    background: inherit;
-  }
-
-  a {
-    color: inherit;
-    border-bottom: 1px solid #fff;
-  }
-
-  a:hover {
-    color: inherit;
-    border-bottom: none;
-  }
-}
-
-#announcement {
-  padding-top: 105px;
-  padding-bottom: 25px;
-}
-
-.header-hero {
-  padding-top: 40px;
-}
-
-/* Extra announcement height only for landscape viewports */
-@media (min-aspect-ratio: 8/9) {
-  #fp-announcement {
-    min-height: 25vh;
-  }
-}
-
-#fp-announcement aside {
-  padding-top: 115px;
-  padding-bottom: 25px;
-}
-
-.announcement {
-  .content {
-    margin-bottom: 0px;
-  }
-
-
-  > p {
-    .gridPage #announcement .content p,
-    .announcement > h4,
-    .announcement > h3 {
-      color: #ffffff;
-    }
-  }
-}
-
@@ -13,7 +13,7 @@ disableBrowserError = true

 disableKinds = ["taxonomy", "taxonomyTerm"]

-ignoreFiles = [ "(?:^|/)OWNERS$", "README[-]+[a-z]*\\.md", "^node_modules$", "content/en/docs/doc-contributor-tools" ]
+ignoreFiles = [ "^OWNERS$", "README[-]+[a-z]*\\.md", "^node_modules$", "content/en/docs/doc-contributor-tools" ]

 timeout = 3000

@@ -91,7 +91,7 @@ blog = "/:section/:year/:month/:day/:slug/"
 [outputs]
 home = [ "HTML", "RSS", "HEADERS" ]
 page = [ "HTML"]
-section = [ "HTML", "print" ]
+section = [ "HTML"]

 # Add a "text/netlify" media type for auto-generating the _headers file
 [mediaTypes]
@@ -140,10 +140,10 @@ showedit = true

 latest = "v1.20"

-fullversion = "v1.20.0"
-version = "v1.20"
-githubbranch = "master"
-docsbranch = "master"
+fullversion = "v1.19.4"
+version = "v1.19"
+githubbranch = "v1.19.4"
+docsbranch = "release-1.19"
 deprecated = false
 currentUrl = "https://kubernetes.io/docs/home/"
 nextUrl = "https://kubernetes-io-vnext-staging.netlify.com/"
@@ -154,6 +154,11 @@ githubWebsiteRaw = "raw.githubusercontent.com/kubernetes/website"
 # GitHub repository link for editing a page and opening issues.
 github_repo = "https://github.com/kubernetes/website"

+# param for displaying an announcement block on every page.
+# See /i18n/en.toml for message text and title.
+announcement = true
+announcement_bg = "#000000" #choose a dark color – text is white
+
 #Searching
 k8s_search = true

@@ -8,7 +8,7 @@ cid: community
    <main>
        <div class="content">
            <h3>Die Gewissheit, dass Kubernetes überall und für alle gut funktioniert.</h3>
-            <p>Verbinden Sie sich mit der Kubernetes-Community in unserem <a href="http://slack.k8s.io/">Slack Kanal</a>, <a href="https://discuss.kubernetes.io/">Diskussionsforum</a>, oder beteiligen Sie sich an der <a href="https://groups.google.com/g/kubernetes-dev"> Kubernetes-dev-Google-Gruppe</a>. Eine wöchentliches Community-Meeting findet per Videokonferenz statt, um den Stand der Dinge zu diskutieren, folgen Sie
+            <p>Verbinden Sie sich mit der Kubernetes-Community in unserem <a href="http://slack.k8s.io/">Slack Kanal</a>, <a href="https://discuss.kubernetes.io/">Diskussionsforum</a>, oder beteiligen Sie sich an der <a href="https://groups.google.com/forum/#!forum/kubernetes-dev"> Kubernetes-dev-Google-Gruppe</a>. Eine wöchentliches Community-Meeting findet per Videokonferenz statt, um den Stand der Dinge zu diskutieren, folgen Sie
 		<a href="https://github.com/kubernetes/community/blob/master/events/community-meeting.md">diesen Anweisungen</a> für Informationen wie Sie teilnehmen können.</p>
            <p>Sie können Kubernetes auch auf der ganzen Welt über unsere
                <a href="https://www.meetup.com/topics/kubernetes/">Kubernetes Meetup Community</a> und der
@@ -23,7 +23,7 @@ Dieser Verhaltenskodex gilt sowohl innerhalb von Projekträumen als auch in öff

 Fälle von missbräuchlichem, belästigendem oder anderweitig unzumutbarem Verhalten in Kubernetes können gemeldet werden, indem Sie sich an das [Kubernetes Komitee für Verhaltenskodex](https://git.k8s.io/community/committee-code-of-conduct) wenden unter <conduct@kubernetes.io>. Für andere Projekte wenden Sie sich bitte an einen CNCF-Projektbetreuer oder an unseren Mediator, Mishi Choudhary <mishi@linux.com>.

-Dieser Verhaltenskodex wurde aus dem Contributor Covenant übernommen (https://contributor-covenant.org), Version 1.2.0, verfügbar unter https://contributor-covenant.org/version/1/2/0/
+Dieser Verhaltenskodex wurde aus dem Contributor Covenant übernommen (http://contributor-covenant.org), Version 1.2.0, verfügbar unter http://contributor-covenant.org/version/1/2/0/

 ### CNCF Verhaltenskodex für Veranstaltungen

@@ -26,7 +26,7 @@ On the other hand, CNI is more philosophically aligned with Kubernetes. It's far

 Additionally, it's trivial to wrap a CNI plugin and produce a more customized CNI plugin — it can be done with a simple shell script. CNM is much more complex in this regard. This makes CNI an attractive option for rapid development and iteration. Early prototypes have proven that it's possible to eject almost 100% of the currently hard-coded network logic in kubelet into a plugin.  

-We investigated [writing a "bridge" CNM driver](https://groups.google.com/g/kubernetes-sig-network/c/5MWRPxsURUw) for Docker that ran CNI drivers. This turned out to be very complicated. First, the CNM and CNI models are very different, so none of the "methods" lined up. We still have the global vs. local and key-value issues discussed above. Assuming this driver would declare itself local, we have to get info about logical networks from Kubernetes.  
+We investigated [writing a "bridge" CNM driver](https://groups.google.com/forum/#!topic/kubernetes-sig-network/5MWRPxsURUw) for Docker that ran CNI drivers. This turned out to be very complicated. First, the CNM and CNI models are very different, so none of the "methods" lined up. We still have the global vs. local and key-value issues discussed above. Assuming this driver would declare itself local, we have to get info about logical networks from Kubernetes.  

 Unfortunately, Docker drivers are hard to map to other control planes like Kubernetes. Specifically, drivers are not told the name of the network to which a container is being attached — just an ID that Docker allocates internally. This makes it hard for a driver to map back to any concept of network that exists in another system.  

@@ -34,6 +34,6 @@ This and other issues have been brought up to Docker developers by network vendo

 For all of these reasons we have chosen to invest in CNI as the Kubernetes plugin model. There will be some unfortunate side-effects of this. Most of them are relatively minor (for example, `docker inspect` will not show an IP address), but some are significant. In particular, containers started by `docker run` might not be able to communicate with containers started by Kubernetes, and network integrators will have to provide CNI drivers if they want to fully integrate with Kubernetes. On the other hand, Kubernetes will get simpler and more flexible, and a lot of the ugliness of early bootstrapping (such as configuring Docker to use our bridge) will go away.  

-As we proceed down this path, we’ll certainly keep our eyes and ears open for better ways to integrate and simplify. If you have thoughts on how we can do that, we really would like to hear them — find us on [slack](http://slack.k8s.io/) or on our [network SIG mailing-list](https://groups.google.com/g/kubernetes-sig-network).  
+As we proceed down this path, we’ll certainly keep our eyes and ears open for better ways to integrate and simplify. If you have thoughts on how we can do that, we really would like to hear them — find us on [slack](http://slack.k8s.io/) or on our [network SIG mailing-list](https://groups.google.com/forum/#!forum/kubernetes-sig-network).  

 Tim Hockin, Software Engineer, Google
@@ -20,14 +20,21 @@ For example, if we want to require scheduling on a node that is in the us-centra


 ```
-  affinity:
-    nodeAffinity:
-      requiredDuringSchedulingIgnoredDuringExecution:
-        nodeSelectorTerms:
-          - matchExpressions:
-            - key: "failure-domain.beta.kubernetes.io/zone"
-              operator: In
-              values: ["us-central1-a"]
+affinity:
+
+  nodeAffinity:
+
+    requiredDuringSchedulingIgnoredDuringExecution:
+
+      nodeSelectorTerms:
+
+        - matchExpressions:
+
+          - key: "failure-domain.beta.kubernetes.io/zone"
+
+            operator: In
+
+            values: ["us-central1-a"]
 ```


@@ -37,14 +44,21 @@ Preferred rules mean that if nodes match the rules, they will be chosen first, a


 ```
-  affinity:
-    nodeAffinity:
-      preferredDuringSchedulingIgnoredDuringExecution:
-        nodeSelectorTerms:
-          - matchExpressions:
-            - key: "failure-domain.beta.kubernetes.io/zone"
-              operator: In
-              values: ["us-central1-a"]
+affinity:
+
+  nodeAffinity:
+
+    preferredDuringSchedulingIgnoredDuringExecution:
+
+      nodeSelectorTerms:
+
+        - matchExpressions:
+
+          - key: "failure-domain.beta.kubernetes.io/zone"
+
+            operator: In
+
+            values: ["us-central1-a"]
 ```


@@ -53,14 +67,21 @@ Node anti-affinity can be achieved by using negative operators. So for instance


 ```
-  affinity:
-    nodeAffinity:
-      requiredDuringSchedulingIgnoredDuringExecution:
-        nodeSelectorTerms:
-          - matchExpressions:
-            - key: "failure-domain.beta.kubernetes.io/zone"
-              operator: NotIn
-              values: ["us-central1-a"]
+affinity:
+
+  nodeAffinity:
+
+    requiredDuringSchedulingIgnoredDuringExecution:
+
+      nodeSelectorTerms:
+
+        - matchExpressions:
+
+          - key: "failure-domain.beta.kubernetes.io/zone"
+
+            operator: NotIn
+
+            values: ["us-central1-a"]
 ```


@@ -78,7 +99,7 @@ The kubectl command allows you to set taints on nodes, for example:

 ```
 kubectl taint nodes node1 key=value:NoSchedule
-```
+ ```


 creates a taint that marks the node as unschedulable by any pods that do not have a toleration for taint with key key, value value, and effect NoSchedule. (The other taint effects are PreferNoSchedule, which is the preferred version of NoSchedule, and NoExecute, which means any pods that are running on the node when the taint is applied will be evicted unless they tolerate the taint.) The toleration you would add to a PodSpec to have the corresponding pod tolerate this taint would look like this  
@@ -86,11 +107,15 @@ creates a taint that marks the node as unschedulable by any pods that do not hav


 ```
-  tolerations:
-  - key: "key"
-    operator: "Equal"
-    value: "value"
-    effect: "NoSchedule"
+tolerations:
+
+- key: "key"
+
+  operator: "Equal"
+
+  value: "value"
+
+  effect: "NoSchedule"
 ```


@@ -113,13 +138,21 @@ Let’s look at an example. Say you have front-ends in service S1, and they comm

 ```
 affinity:
+
    podAffinity:
+
      requiredDuringSchedulingIgnoredDuringExecution:
+
      - labelSelector:
+
          matchExpressions:
+
          - key: service
+
            operator: In
+
            values: [“S1”]
+
        topologyKey: failure-domain.beta.kubernetes.io/zone
 ```

@@ -139,15 +172,25 @@ Here we have a Pod where we specify the schedulerName field:

 ```
 apiVersion: v1
+
 kind: Pod
+
 metadata:
+
  name: nginx
+
  labels:
+
    app: nginx
+
 spec:
+
  schedulerName: my-scheduler
+
  containers:
+
  - name: nginx
+
    image: nginx:1.10
 ```

@@ -56,13 +56,13 @@ Cri-containerd uses containerd to manage the full container lifecycle and all co

 Let’s use an example to demonstrate how cri-containerd works for the case when Kubelet creates a single-container pod:  

-1. Kubelet calls cri-containerd, via the CRI runtime service API, to create a pod;
-2. cri-containerd uses containerd to create and start a special [pause container](https://www.ianlewis.org/en/almighty-pause-container) (the _sandbox container_) and put that container inside the pod’s cgroups and namespace (steps omitted for brevity);
-3. cri-containerd configures the pod’s network namespace using CNI;
-4. Kubelet subsequently calls cri-containerd, via the CRI image service API, to pull the application container image;
-5. cri-containerd further uses containerd to pull the image if the image is not present on the node;
-6. Kubelet then calls cri-containerd, via the CRI runtime service API, to create and start the application container inside the pod using the pulled container image;
-7. cri-containerd finally calls containerd to create the application container, put it inside the pod’s cgroups and namespace, then to start the pod’s new application container.
+1. 1.Kubelet calls cri-containerd, via the CRI runtime service API, to create a pod;
+2. 2.cri-containerd uses containerd to create and start a special [pause container](https://www.ianlewis.org/en/almighty-pause-container) (the _sandbox container_) and put that container inside the pod’s cgroups and namespace (steps omitted for brevity);
+3. 3.cri-containerd configures the pod’s network namespace using CNI;
+4. 4.Kubelet subsequently calls cri-containerd, via the CRI image service API, to pull the application container image;
+5. 5.cri-containerd further uses containerd to pull the image if the image is not present on the node;
+6. 6.Kubelet then calls cri-containerd, via the CRI runtime service API, to create and start the application container inside the pod using the pulled container image;
+7. 7.cri-containerd finally calls containerd to create the application container, put it inside the pod’s cgroups and namespace, then to start the pod’s new application container.
 After these steps, a pod and its corresponding application container is created and running.


@@ -176,7 +176,7 @@ Cluster-distributed stateful services (e.g., Cassandra) can benefit from splitti

 [Logs](/docs/concepts/cluster-administration/logging/) and [metrics](/docs/tasks/debug-application-cluster/resource-usage-monitoring/) (if collected and persistently retained) are valuable to diagnose outages, but given the variety of technologies available it will not be addressed in this blog. If Internet connectivity is available, it may be desirable to retain logs and metrics externally at a central location.

-Your production deployment should utilize an automated installation, configuration and update tool (e.g., [Ansible](https://github.com/kubernetes-incubator/kubespray), [BOSH](https://github.com/cloudfoundry-incubator/kubo-deployment), [Chef](https://github.com/chef-cookbooks/kubernetes), [Juju](/docs/getting-started-guides/ubuntu/installation/), [kubeadm](/docs/reference/setup-tools/kubeadm/), [Puppet](https://forge.puppet.com/puppetlabs/kubernetes), etc.). A manual process will have repeatability issues, be labor intensive, error prone, and difficult to scale. [Certified distributions](https://www.cncf.io/certification/software-conformance/#logos) are likely to include a facility for retaining configuration settings across updates, but if you implement your own install and config toolchain, then retention, backup and recovery of the configuration artifacts is essential. Consider keeping your deployment components and settings under a version control system such as Git.
+Your production deployment should utilize an automated installation, configuration and update tool (e.g., [Ansible](https://github.com/kubernetes-incubator/kubespray), [BOSH](https://github.com/cloudfoundry-incubator/kubo-deployment), [Chef](https://github.com/chef-cookbooks/kubernetes), [Juju](/docs/getting-started-guides/ubuntu/installation/), [kubeadm](/docs/reference/setup-tools/kubeadm/kubeadm/), [Puppet](https://forge.puppet.com/puppetlabs/kubernetes), etc.). A manual process will have repeatability issues, be labor intensive, error prone, and difficult to scale. [Certified distributions](https://www.cncf.io/certification/software-conformance/#logos) are likely to include a facility for retaining configuration settings across updates, but if you implement your own install and config toolchain, then retention, backup and recovery of the configuration artifacts is essential. Consider keeping your deployment components and settings under a version control system such as Git.

 ## Outage recovery

@@ -17,7 +17,7 @@ Let’s dive into the key features of this release:

 ## Simplified Kubernetes Cluster Management with kubeadm in GA

-Most people who have gotten hands-on with Kubernetes have at some point been hands-on with kubeadm. It's an essential tool for managing the cluster lifecycle, from creation to configuration to upgrade; and now kubeadm is officially GA. [kubeadm](/docs/reference/setup-tools/kubeadm/) handles the bootstrapping of production clusters on existing hardware and configuring the core Kubernetes components in a best-practice-manner to providing a secure yet easy joining flow for new nodes and supporting easy upgrades. What’s notable about this GA release are the now graduated advanced features, specifically around pluggability and configurability. The scope of kubeadm is to be a toolbox for both admins and automated, higher-level system and this release is a significant step in that direction.
+Most people who have gotten hands-on with Kubernetes have at some point been hands-on with kubeadm. It's an essential tool for managing the cluster lifecycle, from creation to configuration to upgrade; and now kubeadm is officially GA. [kubeadm](/docs/reference/setup-tools/kubeadm/kubeadm/) handles the bootstrapping of production clusters on existing hardware and configuring the core Kubernetes components in a best-practice-manner to providing a secure yet easy joining flow for new nodes and supporting easy upgrades. What’s notable about this GA release are the now graduated advanced features, specifically around pluggability and configurability. The scope of kubeadm is to be a toolbox for both admins and automated, higher-level system and this release is a significant step in that direction.

 ## Container Storage Interface (CSI) Goes GA

@@ -66,7 +66,6 @@ Vagrant.configure("2") do |config|
            end
        end
    end
-end
 ```

 ### Step 2: Create an Ansible playbook for Kubernetes master.
@@ -44,7 +44,7 @@ As mentioned above, with the promotion of Volume Snapshot to beta, the feature i

 In order to use the Kubernetes Volume Snapshot feature, you must ensure the following components have been deployed on your Kubernetes cluster:

- [Kubernetes Volume Snapshot CRDs](https://github.com/kubernetes-csi/external-snapshotter/tree/53469c21962339229dd150cbba50c34359acec73/config/crd)
+- [Kubernetes Volume Snapshot CRDs](https://github.com/kubernetes-csi/external-snapshotter/tree/master/config/crd)
 - [Volume snapshot controller](https://github.com/kubernetes-csi/external-snapshotter/tree/master/pkg/common-controller)
 - CSI Driver supporting Kubernetes volume snapshot beta

@@ -180,7 +180,7 @@ If your cluster does not come pre-installed with the correct components, you may
 #### Install Snapshot Beta CRDs

 - `kubectl create -f config/crd`
- [https://github.com/kubernetes-csi/external-snapshotter/tree/53469c21962339229dd150cbba50c34359acec73/config/crd](https://github.com/kubernetes-csi/external-snapshotter/tree/53469c21962339229dd150cbba50c34359acec73/config/crd)
+- [https://github.com/kubernetes-csi/external-snapshotter/tree/master/config/crd](https://github.com/kubernetes-csi/external-snapshotter/tree/master/config/crd)
 - Do this once per cluster


@@ -1,96 +0,0 @@
---
-layout: blog
-title: "A Custom Kubernetes Scheduler to Orchestrate Highly Available Applications"
-date: 2020-12-21
-slug: writing-crl-scheduler
---
-
-**Author**: Chris Seto (Cockroach Labs)
-
-As long as you're willing to follow the rules, deploying on Kubernetes and air travel can be quite pleasant. More often than not, things will "just work". However, if one is interested in travelling with an alligator that must remain alive or scaling a database that must remain available, the situation is likely to become a bit more complicated. It may even be easier to build one's own plane or database for that matter. Travelling with reptiles aside, scaling a highly available stateful system is no trivial task.
-
-Scaling any system has two main components:
-1. Adding or removing infrastructure that the system will run on, and
-2. Ensuring that the system knows how to handle additional instances of itself being added and removed.
-
-Most stateless systems, web servers for example, are created without the need to be aware of peers. Stateful systems, which includes databases like CockroachDB, have to coordinate with their peer instances and shuffle around data. As luck would have it, CockroachDB handles data redistribution and replication. The tricky part is being able to tolerate failures during these operations by ensuring that data and instances are distributed across many failure domains (availability zones).
-
-One of Kubernetes' responsibilities is to place "resources" (e.g, a disk or container) into the cluster and satisfy the constraints they request. For example: "I must be in availability zone _A_" (see [Running in multiple zones](/docs/setup/best-practices/multiple-zones/#nodes-are-labeled)), or "I can't be placed onto the same node as this other Pod" (see [Affinity and anti-affinity](/docs/concepts/scheduling-eviction/assign-pod-node/#affinity-and-anti-affinity)).
-
-As an addition to those constraints, Kubernetes offers [Statefulsets](/docs/concepts/workloads/controllers/statefulset/) that provide identity to Pods as well as persistent storage that "follows" these identified pods. Identity in a StatefulSet is handled by an increasing integer at the end of a pod's name. It's important to note that this integer must always be contiguous: in a StatefulSet, if pods 1 and 3 exist then pod 2 must also exist.
-
-Under the hood, CockroachCloud deploys each region of CockroachDB as a StatefulSet in its own Kubernetes cluster - see [Orchestrate CockroachDB in a Single Kubernetes Cluster](https://www.cockroachlabs.com/docs/stable/orchestrate-cockroachdb-with-kubernetes.html).
-In this article, I'll be looking at an individual region, one StatefulSet and one Kubernetes cluster which is distributed across at least three availability zones.
-
-A three-node CockroachCloud cluster would look something like this:
-
-![3-node, multi-zone cockroachdb cluster](image01.png)
-
-When adding additional resources to the cluster we also distribute them across zones. For the speediest user experience, we add all Kubernetes nodes at the same time and then scale up the StatefulSet.
-
-![illustration of phases: adding Kubernetes nodes to the multi-zone cockroachdb cluster](image02.png)
-
-Note that anti-affinities are satisfied no matter the order in which pods are assigned to Kubernetes nodes. In the example, pods 0, 1 and 2 were assigned to zones A, B, and C respectively, but pods 3 and 4 were assigned in a different order, to zones B and A respectively. The anti-affinity is still satisfied because the pods are still placed in different zones.
-
-To remove resources from a cluster, we perform these operations in reverse order.
-
-We first scale down the StatefulSet and then remove from the cluster any nodes lacking a CockroachDB pod.
-
-![illustration of phases: scaling down pods in a multi-zone cockroachdb cluster in Kubernetes](image03.png)
-
-Now, remember that pods in a StatefulSet of size _n_ must have ids in the range `[0,n)`. When scaling down a StatefulSet by _m_, Kubernetes removes _m_ pods, starting from the highest ordinals and moving towards the lowest, [the reverse in which they were added](/docs/concepts/workloads/controllers/statefulset/#deployment-and-scaling-guarantees).
-Consider the cluster topology below:
-
-![illustration: cockroachdb cluster: 6 nodes distributed across 3 availability zones](image04.png)
-
-As ordinals 5 through 3 are removed from this cluster, the statefulset continues to have a presence across all 3 availability zones.
-
-![illustration: removing 3 nodes from a 6-node, 3-zone cockroachdb cluster](image05.png)
-
-However, Kubernetes' scheduler doesn't _guarantee_ the placement above as we expected at first.
-
-Our combined knowledge of the following is what lead to this misconception.
-* Kubernetes' ability to [automatically spread Pods across zone](/docs/setup/best-practices/multiple-zones/#pods-are-spread-across-zones)
-* The behavior that a StatefulSet with _n_ replicas, when Pods are being deployed, they are created sequentially, in order from `{0..n-1}`. See [StatefulSet](https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/#deployment-and-scaling-guarantees) for more details.
-
-Consider the following topology:
-
-![illustration: 6-node cockroachdb cluster distributed across 3 availability zones](image06.png)
-
-These pods were created in order and they are spread across all availability zones in the cluster. When ordinals 5 through 3 are terminated, this cluster will lose its presence in zone C!
-
-![illustration: terminating 3 nodes in 6-node cluster spread across 3 availability zones, where 2/2 nodes in the same availability zone are terminated, knocking out that AZ](image07.png)
-
-Worse yet, our automation, at the time, would remove Nodes A-2, B-2, and C-2. Leaving CRDB-1 in an unscheduled state as persistent volumes are only available in the zone they are initially created in.
-
-To correct the latter issue, we now employ a "hunt and peck" approach to removing machines from a cluster. Rather than blindly removing Kubernetes nodes from the cluster, only nodes without a CockroachDB pod would be removed. The much more daunting task was to wrangle the Kubernetes scheduler.
-
-## A session of brainstorming left us with 3 options:
-
-### 1. Upgrade to kubernetes 1.18 and make use of Pod Topology Spread Constraints
-
-While this seems like it could have been the perfect solution, at the time of writing Kubernetes 1.18 was unavailable on the two most common managed Kubernetes services in public cloud, EKS and GKE.
-Furthermore, [pod topology spread constraints](/docs/concepts/workloads/pods/pod-topology-spread-constraints/) were still a [beta feature in 1.18](https://v1-18.docs.kubernetes.io/docs/concepts/workloads/pods/pod-topology-spread-constraints/) which meant that it [wasn't guaranteed to be available in managed clusters](https://cloud.google.com/kubernetes-engine/docs/concepts/types-of-clusters#kubernetes_feature_choices) even when v1.18 became available.
-The entire endeavour was concerningly reminiscent of checking [caniuse.com](https://caniuse.com/) when Internet Explorer 8 was still around.
-
-### 2. Deploy a statefulset _per zone_.
-
-Rather than having one StatefulSet distributed across all availability zones, a single StatefulSet with node affinities per zone would allow manual control over our zonal topology.
-Our team had considered this as an option in the past which made it particularly appealing.
-Ultimately, we decided to forego this option as it would have required a massive overhaul to our codebase and performing the migration on existing customer clusters would have been an equally large undertaking.
-
-### 3. Write a custom Kubernetes scheduler.
-
-Thanks to an example from [Kelsey Hightower](https://github.com/kelseyhightower/scheduler) and a blog post from [Banzai Cloud](https://banzaicloud.com/blog/k8s-custom-scheduler/), we decided to dive in head first and write our own [custom Kubernetes scheduler](/docs/tasks/extend-kubernetes/configure-multiple-schedulers/).
-Once our proof-of-concept was deployed and running, we quickly discovered that the Kubernetes' scheduler is also responsible for mapping persistent volumes to the Pods that it schedules.
-The output of [`kubectl get events`](/docs/tasks/extend-kubernetes/configure-multiple-schedulers/#verifying-that-the-pods-were-scheduled-using-the-desired-schedulers) had led us to believe there was another system at play.
-In our journey to find the component responsible for storage claim mapping, we discovered the [kube-scheduler plugin system](/docs/concepts/scheduling-eviction/scheduling-framework/). Our next POC was a `Filter` plugin that determined the appropriate availability zone by pod ordinal, and it worked flawlessly!
-
-Our [custom scheduler plugin](https://github.com/cockroachlabs/crl-scheduler) is open source and runs in all of our CockroachCloud clusters.
-Having control over how our StatefulSet pods are being scheduled has let us scale out with confidence.
-We may look into retiring our plugin once pod topology spread constraints are available in GKE and EKS, but the maintenance overhead has been surprisingly low.
-Better still: the plugin's implementation is orthogonal to our business logic. Deploying it, or retiring it for that matter, is as simple as changing the `schedulerName` field in our StatefulSet definitions.
-
---
-
-_[Chris Seto](https://twitter.com/_ostriches) is a software engineer at Cockroach Labs and works on their Kubernetes automation for [CockroachCloud](https://cockroachlabs.cloud), CockroachDB._
@@ -55,7 +55,7 @@ All your existing images will still work exactly the same.

 ### What about private images?

-Yes. All CRI runtimes support the same pull secrets configuration used in
+Also yes. All CRI runtimes support the same pull secrets configuration used in
 Kubernetes, either via the PodSpec or ServiceAccount.


@@ -82,7 +82,7 @@ usability of other container runtimes. As an example, OpenShift 4.x has been
 using the [CRI-O] runtime in production since June 2019.

 For other examples and references you can look at the adopters of containerd and
-CRI-O, two container runtimes under the Cloud Native Computing Foundation ([CNCF]).
+cri-o, two container runtimes under the Cloud Native Computing Foundation ([CNCF]).
 - [containerd](https://github.com/containerd/containerd/blob/master/ADOPTERS.md)
 - [CRI-O](https://github.com/cri-o/cri-o/blob/master/ADOPTERS.md)

@@ -110,11 +110,11 @@ provide an end-to-end standard for managing containers.

 That’s a complex question and it depends on a lot of factors. If Docker is
 working for you, moving to containerd should be a relatively easy swap and
-will have strictly better performance and less overhead. However, we encourage you
+has have strictly better performance and less overhead. However we encourage you
 to explore all the options from the [CNCF landscape] in case another would be an
 even better fit for your environment.

-[CNCF landscape]: https://landscape.cncf.io/card-mode?category=container-runtime&grouping=category
+[CNCF landscape]: https://landscape.cncf.io/category=container-runtime&format=card-mode&grouping=category


 ### What should I look out for when changing CRI implementations?
@@ -129,7 +129,7 @@ common things to consider when migrating are:
 - Kubectl plugins that require docker CLI or the control socket
 - Kubernetes tools that require direct access to Docker (e.g. kube-imagepuller)
 - Configuration of functionality like `registry-mirrors` and insecure registries 
- Other support scripts or daemons that expect Docker to be available and are run
+- Other support scripts or daemons that expect docker to be available and are run
  outside of Kubernetes (e.g. monitoring or security agents)
 - GPUs or special hardware and how they integrate with your runtime and Kubernetes

@@ -140,15 +140,14 @@ runtime where possible.

 Another thing to look out for is anything expecting to run for system maintenance
 or nested inside a container when building images will no longer work. For the
-former, you can use the [`crictl`][cr] tool as a drop-in replacement (see [mapping from docker cli to crictl](https://kubernetes.io/docs/tasks/debug-application-cluster/crictl/#mapping-from-docker-cli-to-crictl)) and for the
-latter you can use newer container build options like [img], [buildah],
-[kaniko], or [buildkit-cli-for-kubectl] that don’t require Docker.
+former, you can use the [`crictl`][cr] tool as a drop-in replacement and for the
+latter you can use newer container build options like [img], [buildah], or
+[kaniko] that don’t require Docker.

 [cr]: https://github.com/kubernetes-sigs/cri-tools
 [img]: https://github.com/genuinetools/img
 [buildah]: https://github.com/containers/buildah
 [kaniko]: https://github.com/GoogleContainerTools/kaniko
-[buildkit-cli-for-kubectl]: https://github.com/vmware-tanzu/buildkit-cli-for-kubectl

 For containerd, you can start with their [documentation] to see what configuration
 options are available as you migrate things over.
@@ -13,8 +13,8 @@ as a container runtime after v1.20.

 **You do not need to panic. It’s not as dramatic as it sounds.**

-TL;DR Docker as an underlying runtime is being deprecated in favor of runtimes
-that use the [Container Runtime Interface (CRI)](https://kubernetes.io/blog/2016/12/container-runtime-interface-cri-in-kubernetes/)
+tl;dr Docker as an underlying runtime is being deprecated in favor of runtimes
+that use the [Container Runtime Interface(CRI)](https://kubernetes.io/blog/2016/12/container-runtime-interface-cri-in-kubernetes/)
 created for Kubernetes. Docker-produced images will continue to work in your
 cluster with all runtimes, as they always have.

@@ -48,7 +48,7 @@ is a popular choice for that runtime (other common options include containerd
 and CRI-O), but Docker was not designed to be embedded inside Kubernetes, and
 that causes a problem. 

-You see, the thing we call “Docker” isn’t actually one thing&mdash;it’s an entire
+You see, the thing we call “Docker” isn’t actually one thing -- it’s an entire
 tech stack, and one part of it is a thing called “containerd,” which is a
 high-level container runtime by itself. Docker is cool and useful because it has
 a lot of UX enhancements that make it really easy for humans to interact with
@@ -66,11 +66,11 @@ does Kubernetes need the Dockershim?

 Docker isn’t compliant with CRI, the [Container Runtime Interface](https://kubernetes.io/blog/2016/12/container-runtime-interface-cri-in-kubernetes/).
 If it were, we wouldn’t need the shim, and this wouldn’t be a thing. But it’s
-not the end of the world, and you don’t need to panic&mdash;you just need to change
+not the end of the world, and you don’t need to panic -- you just need to change
 your container runtime from Docker to another supported container runtime.

 One thing to note: If you are relying on the underlying docker socket
-(`/var/run/docker.sock`) as part of a workflow within your cluster today, moving
+(/var/run/docker.sock) as part of a workflow within your cluster today, moving
 to a different runtime will break your ability to use it. This pattern is often
 called Docker in Docker. There are lots of options out there for this specific
 use case including things like
@@ -82,10 +82,10 @@ use case including things like
 
 This change addresses a different environment than most folks use to interact
 with Docker. The Docker installation you’re using in development is unrelated to
-the Docker runtime inside your Kubernetes cluster. It’s confusing, we understand.
-As a developer, Docker is still useful to you in all the ways it was before this
+the Docker runtime inside your Kubernetes cluster. It’s confusing, I know. As a
+developer, Docker is still useful to you in all the ways it was before this
 change was announced. The image that Docker produces isn’t really a
-Docker-specific image&mdash;it’s an OCI ([Open Container Initiative](https://opencontainers.org/)) image. 
+Docker-specific image -- it’s an OCI ([Open Container Initiative](https://opencontainers.org/)) image. 
 Any OCI-compliant image, regardless of the tool you use to build it, will look
 the same to Kubernetes. Both [containerd](https://containerd.io/) and
 [CRI-O](https://cri-o.io/) know how to pull those images and run them. This is
@@ -95,10 +95,10 @@ So, this change is coming. It’s going to cause issues for some, but it isn’t
 catastrophic, and generally it’s a good thing. Depending on how you interact
 with Kubernetes, this could mean nothing to you, or it could mean a bit of work.
 In the long run, it’s going to make things easier. If this is still confusing
-for you, that’s okay&mdash;there’s a lot going on here; Kubernetes has a lot of
+for you, that’s okay -- there’s a lot going on here, Kubernetes has a lot of
 moving parts, and nobody is an expert in 100% of it. We encourage any and all
 questions regardless of experience level or complexity! Our goal is to make sure
-everyone is educated as much as possible on the upcoming changes. We hope
-this has answered most of your questions and soothed some anxieties! ❤️
+everyone is educated as much as possible on the upcoming changes. `<3` We hope
+this has answered most of your questions and soothed some anxieties!

 Looking for more answers? Check out our accompanying [Dockershim Deprecation FAQ](/blog/2020/12/02/dockershim-faq/).
@@ -1,144 +0,0 @@
---
-layout: blog
-title: 'Kubernetes 1.20: The Raddest Release'
-date: 2020-12-08
-slug: kubernetes-1-20-release-announcement
---
-
-**Authors:** [Kubernetes 1.20 Release Team](https://github.com/kubernetes/sig-release/blob/master/releases/release-1.20/release_team.md)
-
-We’re pleased to announce the release of Kubernetes 1.20, our third and final release of 2020! This release consists of 42 enhancements: 11 enhancements have graduated to stable, 15 enhancements are moving to beta, and 16 enhancements are entering alpha.
-
-The 1.20 release cycle returned to its normal cadence of 11 weeks following the previous extended release cycle. This is one of the most feature dense releases in a while: the Kubernetes innovation cycle is still trending upward. This release has more alpha than stable enhancements, showing that there is still much to explore in the cloud native ecosystem.
-
-## Major Themes
-
-### Volume Snapshot Operations Goes Stable
-
-This feature provides a standard way to trigger volume snapshot operations and allows users to incorporate snapshot operations in a portable manner on any Kubernetes environment and supported storage providers.
-
-Additionally, these Kubernetes snapshot primitives act as basic building blocks that unlock the ability to develop advanced, enterprise-grade, storage administration features for Kubernetes, including application or cluster level backup solutions.
-
-Note that snapshot support requires Kubernetes distributors to bundle the Snapshot controller, Snapshot CRDs, and validation webhook. A CSI driver supporting the snapshot functionality must also be deployed on the cluster.
-
-### Kubectl Debug Graduates to Beta
-
-The `kubectl alpha debug` features graduates to beta in 1.20, becoming `kubectl debug`. The feature provides support for common debugging workflows directly from kubectl. Troubleshooting scenarios supported in this release of kubectl include:
-
-* Troubleshoot workloads that crash on startup by creating a copy of the pod that uses a different container image or command.
-* Troubleshoot distroless containers by adding a new container with debugging tools, either in a new copy of the pod or using an ephemeral container. (Ephemeral containers are an alpha feature that are not enabled by default.)
-* Troubleshoot on a node by creating a container running in the host namespaces and with access to the host’s filesystem.
-
-Note that as a new built-in command, `kubectl debug` takes priority over any kubectl plugin named “debug”. You must rename the affected plugin.
-
-Invocations using `kubectl alpha debug` are now deprecated and will be removed in a subsequent release. Update your scripts to use `kubectl debug`. For more information about `kubectl debug`, see [Debugging Running Pods](https://kubernetes.io/docs/tasks/debug-application-cluster/debug-running-pod/).
-
-### Beta: API Priority and Fairness
-
-Introduced in 1.18, Kubernetes 1.20 now enables API Priority and Fairness (APF) by default. This allows `kube-apiserver` to categorize incoming requests by priority levels.
-
-### Alpha with updates: IPV4/IPV6
-
-The IPv4/IPv6 dual stack has been reimplemented to support dual stack services based on user and community feedback. This allows both IPv4 and IPv6 service cluster IP addresses to be assigned to a single service, and also enables a service to be transitioned from single to dual IP stack and vice versa.
-
-### GA: Process PID Limiting for Stability
-
-Process IDs (pids) are a fundamental resource on Linux hosts. It is trivial to hit the task limit without hitting any other resource limits and cause instability to a host machine.
-
-Administrators require mechanisms to ensure that user pods cannot induce pid exhaustion that prevents host daemons (runtime, kubelet, etc) from running. In addition, it is important to ensure that pids are limited among pods in order to ensure they have limited impact to other workloads on the node.
-After being enabled-by-default for a year, SIG Node graduates PID Limits to GA on both `SupportNodePidsLimit` (node-to-pod PID isolation) and `SupportPodPidsLimit` (ability to limit PIDs per pod).
-
-### Alpha: Graceful node shutdown
-
-Users and cluster administrators expect that pods will adhere to expected pod lifecycle including pod termination. Currently, when a node shuts down, pods do not follow the expected pod termination lifecycle and are not terminated gracefully which can cause issues for some workloads.
-The `GracefulNodeShutdown` feature is now in Alpha. `GracefulNodeShutdown` makes the kubelet aware of node system shutdowns, enabling graceful termination of pods during a system shutdown.
-
-## Major Changes
-
-### Dockershim Deprecation
-
-Dockershim, the container runtime interface (CRI) shim for Docker is being deprecated. Support for Docker is deprecated and will be removed in a future release. Docker-produced images will continue to work in your cluster with all CRI compliant runtimes as Docker images follow the Open Container Initiative (OCI) image specification.
-The Kubernetes community has written a [detailed blog post about deprecation](https://blog.k8s.io/2020/12/02/dont-panic-kubernetes-and-docker/) with [a dedicated FAQ page for it](https://blog.k8s.io/2020/12/02/dockershim-faq/).
-
-### Exec Probe Timeout Handling
-
-A longstanding bug regarding exec probe timeouts that may impact existing pod definitions has been fixed. Prior to this fix, the field `timeoutSeconds` was not respected for exec probes. Instead, probes would run indefinitely, even past their configured deadline, until a result was returned. With this change, the default value of `1 second` will be applied if a value is not specified and existing pod definitions may no longer be sufficient if a probe takes longer than one second. A feature gate, called `ExecProbeTimeout`, has been added with this fix that enables cluster operators to revert to the previous behavior, but this will be locked and removed in subsequent releases. In order to revert to the previous behavior, cluster operators should set this feature gate to `false`.
-
-Please review the updated documentation regarding [configuring probes](docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-probes) for more details.
-
-## Other Updates
-
-### Graduated to Stable
-
-* [RuntimeClass](https://github.com/kubernetes/enhancements/issues/585)
-* [Built-in API Types Defaults](https://github.com/kubernetes/enhancements/issues/1929)
-* [Add Pod-Startup Liveness-Probe Holdoff](https://github.com/kubernetes/enhancements/issues/950)
-* [Support CRI-ContainerD On Windows](https://github.com/kubernetes/enhancements/issues/1001)
-* [SCTP Support for Services](https://github.com/kubernetes/enhancements/issues/614)
-* [Adding AppProtocol To Services And Endpoints](https://github.com/kubernetes/enhancements/issues/1507)
-
-### Notable Feature Updates
-
-* [CronJobs](https://github.com/kubernetes/enhancements/issues/19)
-
-# Release notes
-
-You can check out the full details of the 1.20 release in the [release notes](https://github.com/kubernetes/kubernetes/blob/master/CHANGELOG/CHANGELOG-1.20.md).
-
-# Availability of release
-
-Kubernetes 1.20 is available for [download on GitHub](https://github.com/kubernetes/kubernetes/releases/tag/v1.20.0). There are some great resources out there for getting started with Kubernetes. You can check out some [interactive tutorials](https://kubernetes.io/docs/tutorials/) on the main Kubernetes site, or run a local cluster on your machine using Docker containers with [kind](https://kind.sigs.k8s.io). If you’d like to try building a cluster from scratch, check out the [Kubernetes the Hard Way](https://github.com/kelseyhightower/kubernetes-the-hard-way) tutorial by Kelsey Hightower.
-
-# Release Team
-
-This release was made possible by a very dedicated group of individuals, who came together as a team in the midst of a lot of things happening out in the world. A huge thank you to the release lead Jeremy Rickard, and to everyone else on the release team for supporting each other, and working so hard to deliver the 1.20 release for the community.
-
-# Release Logo
-
-![Kubernetes 1.20 Release Logo](/images/blog/2020-12-08-kubernetes-1.20-release-announcement/laser.png)
-
-[raddest](https://www.dictionary.com/browse/rad): *adjective*, Slang. excellent; wonderful; cool:
-
-> The Kubernetes 1.20 Release has been the raddest release yet.
-
-2020 has been a challenging year for many of us, but Kubernetes contributors have delivered a record-breaking number of enhancements in this release. That is a great accomplishment, so the release lead wanted to end the year with a little bit of levity and pay homage to [Kubernetes 1.14 - Caturnetes](https://github.com/kubernetes/sig-release/tree/master/releases/release-1.14) with a "rad" cat named Humphrey.
-
-Humphrey is the release lead's cat and has a permanent [`blep`](https://www.inverse.com/article/42316-why-do-cats-blep-science-explains). *Rad* was pretty common slang in the 1990s in the United States, and so were laser backgrounds. Humphrey in a 1990s style school picture felt like a fun way to end the year. Hopefully, Humphrey and his *blep* bring you a little joy at the end of 2020!
-
-The release logo was created by [Henry Hsu - @robotdancebattle](https://www.instagram.com/robotdancebattle/).
-
-# User Highlights
-
- Apple is operating multi-thousand node Kubernetes clusters in data centers all over the world. Watch [Alena Prokharchyk's KubeCon NA Keynote](https://youtu.be/Tx8qXC-U3KM) to learn more about their cloud native journey.
-
-# Project Velocity
-
-The [CNCF K8s DevStats project](https://k8s.devstats.cncf.io/) aggregates a number of interesting data points related to the velocity of Kubernetes and various sub-projects. This includes everything from individual contributions to the number of companies that are contributing, and is a neat illustration of the depth and breadth of effort that goes into evolving this ecosystem.
-
-In the v1.20 release cycle, which ran for 11 weeks (September 25 to December 9), we saw contributions from [967 companies](https://k8s.devstats.cncf.io/d/9/companies-table?orgId=1&var-period_name=v1.19.0%20-%20now&var-metric=contributions) and [1335 individuals](https://k8s.devstats.cncf.io/d/66/developer-activity-counts-by-companies?orgId=1&var-period_name=v1.19.0%20-%20now&var-metric=contributions&var-repogroup_name=Kubernetes&var-country_name=All&var-companies=All) ([44 of whom](https://k8s.devstats.cncf.io/d/52/new-contributors?orgId=1&from=1601006400000&to=1607576399000&var-repogroup_name=Kubernetes) made their first Kubernetes contribution) from [26 countries](https://k8s.devstats.cncf.io/d/50/countries-stats?orgId=1&from=1601006400000&to=1607576399000&var-period_name=Quarter&var-countries=All&var-repogroup_name=Kubernetes&var-metric=rcommitters&var-cum=countries).
-
-# Ecosystem Updates
-
- KubeCon North America just wrapped up three weeks ago, the second such event to be virtual! All talks are [now available to all on-demand](https://www.youtube.com/playlist?list=PLj6h78yzYM2Pn8RxfLh2qrXBDftr6Qjut) for anyone still needing to catch up!
- In June, the Kubernetes community formed a new working group as a direct response to the Black Lives Matter protests occurring across America. WG Naming's goal is to remove harmful and unclear language in the Kubernetes project as completely as possible and to do so in a way that is portable to other CNCF projects. A great introductory talk on this important work and how it is conducted was given [at KubeCon 2020 North America](https://sched.co/eukp), and the initial impact of this labor [can actually be seen in the v1.20 release](https://github.com/kubernetes/enhancements/issues/2067).
- Previously announced this summer, [The Certified Kubernetes Security Specialist (CKS) Certification](https://www.cncf.io/announcements/2020/11/17/kubernetes-security-specialist-certification-now-available/) was released during Kubecon NA for immediate scheduling!  Following the model of CKA and CKAD, the CKS is a performance-based exam, focused on security-themed competencies and domains.  This exam is targeted at current CKA holders, particularly those who want to round out their baseline knowledge in securing cloud workloads (which is all of us, right?).
-
-# Event Updates
-
-KubeCon + CloudNativeCon Europe 2021 will take place May 4 - 7, 2021! Registration will open on January 11. You can find more information about the conference [here](https://events.linuxfoundation.org/kubecon-cloudnativecon-europe/). Remember that [the CFP](https://events.linuxfoundation.org/kubecon-cloudnativecon-europe/program/cfp/) closes on Sunday, December 13, 11:59pm PST!
-
-# Upcoming release webinar
-
-Stay tuned for the upcoming release webinar happening this January.
-
-# Get Involved
-
-If you’re interested in contributing to the Kubernetes community, Special Interest Groups (SIGs) are a great starting point. Many of them may align with your interests! If there are things you’d like to share with the community, you can join the weekly community meeting, or use any of the following channels:
-
-* Find out more about contributing to Kubernetes at the new [Kubernetes Contributor website](https://www.kubernetes.dev/)
-* Follow us on Twitter [@Kubernetesio](https://twitter.com/kubernetesio) for latest updates
-* Join the community discussion on [Discuss](https://discuss.kubernetes.io/)
-* Join the community on [Slack](http://slack.k8s.io/)
-* Share your Kubernetes [story](https://docs.google.com/a/linuxfoundation.org/forms/d/e/1FAIpQLScuI7Ye3VQHQTwBASrgkjQDSS5TP0g3AXfFhwSM9YpHgxRKFA/viewform)
-* Read more about what’s happening with Kubernetes on the [blog](https://kubernetes.io/blog/)
-* Learn more about the [Kubernetes Release Team](https://github.com/kubernetes/sig-release/tree/master/release-team)
@@ -1,224 +0,0 @@
---
-layout: blog
-title: 'Kubernetes 1.20: Kubernetes Volume Snapshot Moves to GA'
-date: 2020-12-10
-slug: kubernetes-1.20-volume-snapshot-moves-to-ga
---
-
-**Authors**: Xing Yang, VMware & Xiangqian Yu, Google
-
-The Kubernetes Volume Snapshot feature is now GA in Kubernetes v1.20. It was introduced as [alpha](https://kubernetes.io/blog/2018/10/09/introducing-volume-snapshot-alpha-for-kubernetes/) in Kubernetes v1.12, followed by a [second alpha](https://kubernetes.io/blog/2019/01/17/update-on-volume-snapshot-alpha-for-kubernetes/) with breaking changes in Kubernetes v1.13, and promotion to [beta](https://kubernetes.io/blog/2019/12/09/kubernetes-1-17-feature-cis-volume-snapshot-beta/) in Kubernetes 1.17. This blog post summarizes the changes releasing the feature from beta to GA.
-
-## What is a volume snapshot?
-
-Many storage systems (like Google Cloud Persistent Disks, Amazon Elastic Block Storage, and many on-premise storage systems) provide the ability to create a “snapshot” of a persistent volume. A snapshot represents a point-in-time copy of a volume. A snapshot can be used either to rehydrate a new volume (pre-populated with the snapshot data) or to restore an existing volume to a previous state (represented by the snapshot).
-
-## Why add volume snapshots to Kubernetes?
-
-Kubernetes aims to create an abstraction layer between distributed applications and underlying clusters so that applications can be agnostic to the specifics of the cluster they run on and application deployment requires no “cluster-specific” knowledge.
-
-The Kubernetes Storage SIG identified snapshot operations as critical functionality for many stateful workloads. For example, a database administrator may want to snapshot a database’s volumes before starting a database operation.
-
-By providing a standard way to trigger volume snapshot operations in Kubernetes, this feature allows Kubernetes users to incorporate snapshot operations in a portable manner on any Kubernetes environment regardless of the underlying storage.
-
-Additionally, these Kubernetes snapshot primitives act as basic building blocks that unlock the ability to develop advanced enterprise-grade storage administration features for Kubernetes,  including application or cluster level backup solutions.
-
-## What’s new since beta?
-
-With the promotion of Volume Snapshot to GA, the feature is enabled by default on standard Kubernetes deployments and cannot be turned off.
-
-Many enhancements have been made to improve the quality of this feature and to make it production-grade.
-
- The Volume Snapshot APIs and client library were moved to a separate Go module.
-
- A snapshot validation webhook has been added to perform necessary validation on volume snapshot objects. More details can be found in the [Volume Snapshot Validation Webhook Kubernetes Enhancement Proposal](https://github.com/kubernetes/enhancements/tree/master/keps/sig-storage/1900-volume-snapshot-validation-webhook).
-
- Along with the validation webhook, the volume snapshot controller will start labeling invalid snapshot objects that already existed. This allows users to identify, remove any invalid objects, and correct their workflows. Once the API is switched to the v1 type, those invalid objects will not be deletable from the system.
-
- To provide better insights into how the snapshot feature is performing, an initial set of operation metrics has been added to the volume snapshot controller.
-
- There are more end-to-end tests, running on GCP, that validate the feature in a real Kubernetes cluster. Stress tests (based on Google Persistent Disk and `hostPath` CSI Drivers) have been introduced to test the robustness of the system.
-
-Other than introducing tightening validation, there is no difference between the v1beta1 and v1 Kubernetes volume snapshot API. In this release (with Kubernetes 1.20), both v1 and v1beta1 are served while the stored API version is still v1beta1. Future releases will switch the stored version to v1 and gradually remove v1beta1 support.
-
-## Which CSI drivers support volume snapshots?
-
-Snapshots are only supported for CSI drivers, not for in-tree or FlexVolume drivers. Ensure the deployed CSI driver on your cluster has implemented the snapshot interfaces. For more information, see [Container Storage Interface (CSI) for Kubernetes GA](https://kubernetes.io/blog/2019/01/15/container-storage-interface-ga/).
-
-Currently more than [50 CSI drivers](https://kubernetes-csi.github.io/docs/drivers.html) support the Volume Snapshot feature. The [GCE Persistent Disk CSI Driver](https://github.com/kubernetes-sigs/gcp-compute-persistent-disk-csi-driver) has gone through the tests for upgrading from volume snapshots beta to GA. GA level support for other CSI drivers should be available soon.
-
-## Who builds products using volume snapshots?
-
-As of the publishing of this blog, the following participants from the [Kubernetes Data Protection Working Group](https://github.com/kubernetes/community/tree/master/wg-data-protection) are building products or have already built products using Kubernetes volume snapshots.
-
- [Dell-EMC: PowerProtect](https://www.delltechnologies.com/en-us/data-protection/powerprotect-data-manager.htm)
- [Druva](https://www.druva.com/)
- [Kasten K10](https://www.kasten.io/)
- [NetApp: Project Astra](https://cloud.netapp.com/project-astra)
- [Portworx (PX-Backup)](https://portworx.com/products/px-backup/)
- [Pure Storage (Pure Service Orchestrator)](https://github.com/purestorage/pso-csi)
- [Red Hat OpenShift Container Storage](https://www.redhat.com/en/technologies/cloud-computing/openshift-container-storage)
- [Robin Cloud Native Storage](https://robin.io/storage/)
- [TrilioVault for Kubernetes](https://docs.trilio.io/kubernetes/)
- [Velero plugin for CSI](https://github.com/vmware-tanzu/velero-plugin-for-csi)
-
-## How to deploy volume snapshots?
-
-Volume Snapshot feature contains the following components:
-
- [Kubernetes Volume Snapshot CRDs](https://github.com/kubernetes-csi/external-snapshotter/tree/master/client/config/crd)
- [Volume snapshot controller](https://github.com/kubernetes-csi/external-snapshotter/tree/master/pkg/common-controller)
- [Snapshot validation webhook](https://github.com/kubernetes-csi/external-snapshotter/tree/master/pkg/validation-webhook)
- CSI Driver along with [CSI Snapshotter sidecar](https://github.com/kubernetes-csi/external-snapshotter/tree/master/pkg/sidecar-controller)
-
-It is strongly recommended that Kubernetes distributors bundle and deploy the volume snapshot controller, CRDs, and validation webhook as part of their Kubernetes cluster management process (independent of any CSI Driver).
-
-{{< warning >}}
-
-The snapshot validation webhook serves as a critical component to transition smoothly from using v1beta1 to v1 API. Not installing the snapshot validation webhook makes prevention of invalid volume snapshot objects from creation/updating impossible, which in turn will block deletion of invalid volume snapshot objects in coming upgrades.
-
-{{< /warning >}}
-
-If your cluster does not come pre-installed with the correct components, you may manually install them. See the [CSI Snapshotter](https://github.com/kubernetes-csi/external-snapshotter#readme) README for details.
-
-## How to use volume snapshots?
-
-Assuming all the required components (including CSI driver) have been already deployed and running on your cluster, you can create volume snapshots using the `VolumeSnapshot` API object, or use an existing `VolumeSnapshot` to restore a PVC by specifying the VolumeSnapshot data source on it. For more details, see the [volume snapshot documentation](/docs/concepts/storage/volume-snapshots/).
-
-{{< note >}} The Kubernetes Snapshot API does not provide any application consistency guarantees. You have to prepare your application (pause application, freeze filesystem etc.) before taking the snapshot for data consistency either manually or using higher level APIs/controllers. {{< /note >}}
-
-### Dynamically provision a volume snapshot
-
-To dynamically provision a volume snapshot, create a `VolumeSnapshotClass` API object first.
-
-```yaml
-apiVersion: snapshot.storage.k8s.io/v1
-kind: VolumeSnapshotClass
-metadata:
-  name: test-snapclass
-driver: testdriver.csi.k8s.io
-deletionPolicy: Delete
-parameters:
-  csi.storage.k8s.io/snapshotter-secret-name: mysecret
-  csi.storage.k8s.io/snapshotter-secret-namespace: mysecretnamespace
-```  
-
-Then create a `VolumeSnapshot` API object from a PVC by specifying the volume snapshot class.
-
-```yaml
-apiVersion: snapshot.storage.k8s.io/v1
-kind: VolumeSnapshot
-metadata:
-  name: test-snapshot
-  namespace: ns1
-spec:
-  volumeSnapshotClassName: test-snapclass
-  source:
-    persistentVolumeClaimName: test-pvc
-```
-
-### Importing an existing volume snapshot with Kubernetes
-
-To import a pre-existing volume snapshot into Kubernetes, manually create a `VolumeSnapshotContent` object first.
-
-```yaml
-apiVersion: snapshot.storage.k8s.io/v1
-kind: VolumeSnapshotContent
-metadata:
-  name: test-content
-spec:
-  deletionPolicy: Delete
-  driver: testdriver.csi.k8s.io
-  source:
-    snapshotHandle: 7bdd0de3-xxx
-  volumeSnapshotRef:
-    name: test-snapshot
-    namespace: default
-```
-
-Then create a `VolumeSnapshot` object pointing to the `VolumeSnapshotContent` object.
-
-```yaml
-apiVersion: snapshot.storage.k8s.io/v1
-kind: VolumeSnapshot
-metadata:
-  name: test-snapshot
-spec:
-  source:
-        volumeSnapshotContentName: test-content
-```
-
-### Rehydrate volume from snapshot
-
-A bound and ready `VolumeSnapshot` object can be used to rehydrate a new volume with data pre-populated from snapshotted data as shown here:
-
-```yaml
-apiVersion: v1
-kind: PersistentVolumeClaim
-metadata:
-  name: pvc-restore
-  namespace: demo-namespace
-spec:
-  storageClassName: test-storageclass
-  dataSource:
-    name: test-snapshot
-    kind: VolumeSnapshot
-    apiGroup: snapshot.storage.k8s.io
-  accessModes:
-    - ReadWriteOnce
-  resources:
-    requests:
-      storage: 1Gi
-```
-
-## How to add support for snapshots in a CSI driver?
-
-See the [CSI spec](https://github.com/container-storage-interface/spec/blob/master/spec.md) and the [Kubernetes-CSI Driver Developer Guide](https://kubernetes-csi.github.io/docs/snapshot-restore-feature.html) for more details on how to implement the snapshot feature in a CSI driver.
-
-## What are the limitations?
-
-The GA implementation of volume snapshots for Kubernetes has the following limitations:
-
- Does not support reverting an existing PVC to an earlier state represented by a snapshot (only supports provisioning a new volume from a snapshot).
-
-### How to learn more?
-
-The code repository for snapshot APIs and controller is here: https://github.com/kubernetes-csi/external-snapshotter
-
-Check out additional documentation on the snapshot feature here: http://k8s.io/docs/concepts/storage/volume-snapshots and https://kubernetes-csi.github.io/docs/
-
-## How to get involved?
-
-This project, like all of Kubernetes, is the result of hard work by many contributors from diverse backgrounds working together.
-
-We offer a huge thank you to the contributors who stepped up these last few quarters to help the project reach GA. We want to thank Saad Ali, Michelle Au, Tim Hockin, and Jordan Liggitt for their insightful reviews and thorough consideration with the design, thank Andi Li for his work on adding the support of the snapshot validation webhook, thank Grant Griffiths on implementing metrics support in the snapshot controller and handling password rotation in the validation webhook, thank Chris Henzie, Raunak Shah, and Manohar Reddy for writing critical e2e tests to meet the scalability and stability requirements for graduation, thank Kartik Sharma for moving snapshot APIs and client lib to a separate go module, and thank Raunak Shah and Prafull Ladha for their help with upgrade testing from beta to GA.
-
-There are many more people who have helped to move the snapshot feature from beta to GA. We want to thank everyone who has contributed to this effort:
- [Andi Li](https://github.com/AndiLi99)
- [Ben Swartzlander](https://github.com/bswartz)
- [Chris Henzie](https://github.com/chrishenzie)
- [Christian Huffman](https://github.com/huffmanca)
- [Grant Griffiths](https://github.com/ggriffiths)
- [Humble Devassy Chirammal](https://github.com/humblec)
- [Jan Šafránek](https://github.com/jsafrane)
- [Jiawei Wang](https://github.com/Jiawei0227)
- [Jing Xu](https://github.com/jingxu97)
- [Jordan Liggitt](https://github.com/liggitt)
- [Kartik Sharma](https://github.com/Kartik494)
- [Madhu Rajanna](https://github.com/Madhu-1)
- [Manohar Reddy](https://github.com/boddumanohar)
- [Michelle Au](https://github.com/msau42)
- [Patrick Ohly](https://github.com/pohly)
- [Prafull Ladha](https://github.com/prafull01)
- [Prateek Pandey](https://github.com/prateekpandey14)
- [Raunak Shah](https://github.com/RaunakShah)
- [Saad Ali](https://github.com/saad-ali)
- [Saikat Roychowdhury](https://github.com/saikat-royc)
- [Tim Hockin](https://github.com/thockin)
- [Xiangqian Yu](https://github.com/yuxiangqian)
- [Xing Yang](https://github.com/xing-yang)
- [Zhu Can](https://github.com/zhucan)
-
-For those interested in getting involved with the design and development of CSI or any part of the Kubernetes Storage system, join the [Kubernetes Storage Special Interest Group](https://github.com/kubernetes/community/tree/master/sig-storage)  (SIG). We’re rapidly growing and always welcome new contributors.
-
-We also hold regular [Data Protection Working Group meetings](https://docs.google.com/document/d/15tLCV3csvjHbKb16DVk-mfUmFry_Rlwo-2uG6KNGsfw/edit#). New attendees are welcome to join in discussions.
@@ -1,53 +0,0 @@
---
-layout: blog
-title: 'Kubernetes 1.20: Pod Impersonation and Short-lived Volumes in CSI Drivers'
-date: 2020-12-18
-slug: kubernetes-1.20-pod-impersonation-short-lived-volumes-in-csi
---
-
-**Author**: Shihang Zhang (Google)
-
-Typically when a [CSI](https://github.com/container-storage-interface/spec/blob/baa71a34651e5ee6cb983b39c03097d7aa384278/spec.md) driver mounts credentials such as secrets and certificates, it has to authenticate against storage providers to access the credentials. However, the access to those credentials are controlled on the basis of the pods' identities rather than the CSI driver's identity. CSI drivers, therefore, need some way to retrieve pod's service account token. 
-
-Currently there are two suboptimal approaches to achieve this, either by granting CSI drivers the permission to use TokenRequest API or by reading tokens directly from the host filesystem. 
-
-Both of them exhibit the following drawbacks:
-
- Violating the principle of least privilege
- Every CSI driver needs to re-implement the logic of getting the pod’s service account token
-
-The second approach is more problematic due to:
-
- The audience of the token defaults to the kube-apiserver
- The token is not guaranteed to be available (e.g. `AutomountServiceAccountToken=false`)
- The approach does not work for CSI drivers that run as a different (non-root) user from the pods. See [file permission section for service account token](https://github.com/kubernetes/enhancements/blob/f40c24a5da09390bd521be535b38a4dbab09380c/keps/sig-storage/20180515-svcacct-token-volumes.md#file-permission)
- The token might be legacy Kubernetes service account token which doesn’t expire if `BoundServiceAccountTokenVolume=false`
-
-Kubernetes 1.20 introduces an alpha feature, `CSIServiceAccountToken`, to improve the security posture. The new feature allows CSI drivers to receive pods' [bound service account tokens](https://github.com/kubernetes/enhancements/blob/master/keps/sig-auth/1205-bound-service-account-tokens/README.md).
-
-This feature also provides a knob to re-publish volumes so that short-lived volumes can be refreshed.
-
-## Pod Impersonation
-
-### Using GCP APIs
-
-Using [Workload Identity](https://cloud.google.com/kubernetes-engine/docs/how-to/workload-identity), a Kubernetes service account can authenticate as a Google service account when accessing Google Cloud APIs. If a CSI driver needs to access GCP APIs on behalf of the pods that it is mounting volumes for, it can use the pod's service account token to [exchange for GCP tokens](https://cloud.google.com/iam/docs/reference/sts/rest). The pod's service account token is plumbed through the volume context in `NodePublishVolume` RPC calls when the feature `CSIServiceAccountToken` is enabled. For example: accessing [Google Secret Manager](https://cloud.google.com/secret-manager/) via a [secret store CSI driver](https://github.com/GoogleCloudPlatform/secrets-store-csi-driver-provider-gcp).
-
-### Using Vault
-
-If users configure [Kubernetes as an auth method](https://www.vaultproject.io/docs/auth/kubernetes), Vault uses the `TokenReview` API to validate the Kubernetes service account token. For CSI drivers using Vault as resources provider, they need to present the pod's service account to Vault. For example, [secrets store CSI driver](https://github.com/hashicorp/secrets-store-csi-driver-provider-vault) and [cert manager CSI driver](https://github.com/jetstack/cert-manager-csi).
-
-## Short-lived Volumes
-
-To keep short-lived volumes such as certificates effective, CSI drivers can specify `RequiresRepublish=true` in their`CSIDriver` object to have the kubelet periodically call `NodePublishVolume` on mounted volumes. These republishes allow CSI drivers to ensure that the volume content is up-to-date.
-
-## Next steps
-
-This feature is alpha and projected to move to beta in 1.21. See more in the following KEP and CSI documentation:
-
- [KEP-1855: Service Account Token for CSI Driver](https://github.com/kubernetes/enhancements/blob/master/keps/sig-storage/1855-csi-driver-service-account-token/README.md)
- [Token Requests](https://kubernetes-csi.github.io/docs/token-requests.html)
-
-Your feedback is always welcome!
- SIG-Auth [meets regularly](https://github.com/kubernetes/community/tree/master/sig-auth#meetings) and can be reached via [Slack and the mailing list](https://github.com/kubernetes/community/tree/master/sig-auth#contact)
- SIG-Storage [meets regularly](https://github.com/kubernetes/community/tree/master/sig-storage#meetings) and can be reached via [Slack and the mailing list](https://github.com/kubernetes/community/tree/master/sig-storage#contact).
@@ -1,59 +0,0 @@
--- 
-layout: blog 
-title: 'Kubernetes 1.20: Granular Control of Volume Permission Changes'
-date: 2020-12-14 
-slug: kubernetes-release-1.20-fsGroupChangePolicy-fsGroupPolicy
---
-
-**Authors**: Hemant Kumar, Red Hat & Christian Huffman, Red Hat
-
-Kubernetes 1.20 brings two important beta features, allowing Kubernetes admins and users alike to have more adequate control over how volume permissions are applied when a volume is mounted inside a Pod.
-
-### Allow users to skip recursive permission changes on mount
-Traditionally if your pod is running as a non-root user ([which you should](https://twitter.com/thockin/status/1333892204490735617)), you must specify a `fsGroup` inside the pod’s security context so that the volume can be readable and writable by the Pod. This requirement is covered in more detail in [here](https://kubernetes.io/docs/tasks/configure-pod-container/security-context/).
-
-But one side-effect of setting `fsGroup` is that, each time a volume is mounted, Kubernetes must recursively `chown()` and `chmod()` all the files and directories inside the volume - with a few exceptions noted below. This happens even if group ownership of the volume already matches the requested `fsGroup`, and can be pretty expensive for larger volumes with lots of small files, which causes pod startup to take a long time. This scenario has been a [known problem](https://github.com/kubernetes/kubernetes/issues/69699) for a while, and in Kubernetes 1.20 we are providing knobs to opt-out of recursive permission changes if the volume already has the correct permissions.
-
-When configuring a pod’s security context, set `fsGroupChangePolicy` to "OnRootMismatch" so if the root of the volume already has the correct permissions, the recursive permission change can be skipped. Kubernetes ensures that permissions of the top-level directory are changed last the first time it applies permissions.
-
-```yaml
-securityContext:
-  runAsUser: 1000
-  runAsGroup: 3000
-  fsGroup: 2000
-  fsGroupChangePolicy: "OnRootMismatch"
-```
-You can learn more about this in [Configure volume permission and ownership change policy for Pods](https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#configure-volume-permission-and-ownership-change-policy-for-pods).
-
-### Allow CSI Drivers to declare support for fsGroup based permissions
-
-Although the previous section implied that Kubernetes _always_ recursively changes permissions of a volume if a Pod has a `fsGroup`, this is not strictly true. For certain multi-writer volume types, such as NFS or Gluster, the cluster doesn’t perform recursive permission changes even if the pod has a `fsGroup`. Other volume types may not even support `chown()`/`chmod()`, which rely on Unix-style permission control primitives. 
-
-So how do we know when to apply recursive permission changes and when we shouldn't? For in-tree storage drivers, this was relatively simple. For [CSI](https://kubernetes-csi.github.io/docs/introduction.html#introduction) drivers that could span a multitude of platforms and storage types, this problem can be a bigger challenge.
-
-Previously, whenever a CSI volume was mounted to a Pod, Kubernetes would attempt to automatically determine if the permissions and ownership should be modified. These methods were imprecise and could cause issues as we already mentioned, depending on the storage type.
-
-The CSIDriver custom resource now has a `.spec.fsGroupPolicy` field, allowing storage drivers to explicitly opt in or out of these recursive modifications. By having the CSI driver specify a policy for the backing volumes, Kubernetes can avoid needless modification attempts. This optimization helps to reduce volume mount time and also cuts own reporting errors about modifications that would never succeed.
-
-#### CSIDriver FSGroupPolicy API
-
-Three FSGroupPolicy values are available as of Kubernetes 1.20, with more planned for future releases.
-
- **ReadWriteOnceWithFSType** - This is the default policy, applied if no `fsGroupPolicy` is defined; this preserves the behavior from previous Kubernetes releases. Each volume is examined at mount time to determine if permissions should be recursively applied.
- **File** - Always attempt to apply permission modifications, regardless of the filesystem type or PersistentVolumeClaim’s access mode.
- **None** - Never apply permission modifications.
-
-#### How do I use it?
-The only configuration needed is defining `fsGroupPolicy` inside of the `.spec` for a CSIDriver. Once that element is defined, any subsequently mounted volumes will automatically use the defined policy. There’s no additional deployment required!
-
-#### What’s next?
-
-Depending on feedback and adoption, the Kubernetes team plans to push these implementations to GA in either 1.21 or 1.22. 
-
-### How can I learn more?
-This feature is explained in more detail in Kubernetes project documentation: [CSI Driver fsGroup Support](https://kubernetes-csi.github.io/docs/support-fsgroup.html) and [Configure volume permission and ownership change policy for Pods ](https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#configure-volume-permission-and-ownership-change-policy-for-pods).
-
-### How do I get involved?
-The [Kubernetes Slack channel #csi](https://kubernetes.slack.com/messages/csi) and any of the [standard SIG Storage communication channels](https://github.com/kubernetes/community/blob/master/sig-storage/README.md#contact) are great mediums to reach out to the SIG Storage and the CSI team.
-
-Those interested in getting involved with the design and development of CSI or any part of the Kubernetes Storage system, join the [Kubernetes Storage Special Interest Group (SIG)](https://github.com/kubernetes/community/tree/master/sig-storage). We’re rapidly growing and always welcome new contributors.
@@ -1,134 +0,0 @@
---
-layout: blog
-title: 'Third Party Device Metrics Reaches GA'
-date: 2020-12-16
-slug: third-party-device-metrics-reaches-ga
---
-
- **Authors:** Renaud Gaubert (NVIDIA), David Ashpole (Google), and Pramod Ramarao (NVIDIA)
-
- With Kubernetes 1.20, infrastructure teams who manage large scale Kubernetes clusters, are seeing the graduation of two exciting and long awaited features:
- * The Pod Resources API (introduced in 1.13) is finally graduating to GA. This allows Kubernetes plugins to obtain information about the node’s resource usage and assignment; for example: which pod/container consumes which device.
- * The `DisableAcceleratorMetrics` feature (introduced in 1.19) is graduating to beta and will be enabled by default. This removes device metrics reported by the kubelet in favor of the new plugin architecture.
-
-Many of the features related to fundamental device support (device discovery, plugin, and monitoring) are reaching a strong level of stability.
-Kubernetes users should see these features as stepping stones to enable more complex use cases (networking, scheduling, storage, etc.)!
-
-One such example is Non Uniform Memory Access (NUMA) placement where, when selecting a device, an application typically wants to ensure that data transfer between CPU Memory and Device Memory is as fast as possible. In some cases, incorrect NUMA placement can nullify the benefit of offloading compute to an external device.
-
-If these are topics of interest to you, consider joining the [Kubernetes Node Special Insterest Group](https://github.com/kubernetes/community/tree/master/sig-node) (SIG) for all topics related to the Kubernetes node, the COD (container orchestrated device) workgroup for topics related to runtimes, or the resource management forum for topics related to resource management!
-
-## The Pod Resources API - Why does it need to exist?
-
-Kubernetes is a vendor neutral platform. If we want it to support device monitoring, adding vendor-specific code in the Kubernetes code base is not an ideal solution. Ultimately, devices are a domain where deep expertise is needed and the best people to add and maintain code in that area are the device vendors themselves.
-
-The Pod Resources API was built as a solution to this issue. Each vendor can build and maintain their own out-of-tree monitoring plugin. This monitoring plugin, often deployed as a separate pod within a cluster, can then associate the metrics a device emits with the associated pod that's using it. 
-
-For example, use the NVIDIA GPU dcgm-exporter to scrape metrics in Prometheus format:
-
-```
-$ curl -sL http://127.0.01:8080/metrics
-
-
-# HELP DCGM_FI_DEV_SM_CLOCK SM clock frequency (in MHz).
-# TYPE DCGM_FI_DEV_SM_CLOCK gauge
-# HELP DCGM_FI_DEV_MEM_CLOCK Memory clock frequency (in MHz).
-# TYPE DCGM_FI_DEV_MEM_CLOCK gauge
-# HELP DCGM_FI_DEV_MEMORY_TEMP Memory temperature (in C).
-# TYPE DCGM_FI_DEV_MEMORY_TEMP gauge
-...
-DCGM_FI_DEV_SM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52",container="foo",namespace="bar",pod="baz"} 139
-DCGM_FI_DEV_MEM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52",container="foo",namespace="bar",pod="baz"} 405
-DCGM_FI_DEV_MEMORY_TEMP{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52",container="foo",namespace="bar",pod="baz"} 9223372036854775794
-```
-
-Each agent is expected to adhere to the node monitoring guidelines. In other words, plugins are expected to generate metrics in Prometheus format, and new metrics should not have any dependency on the Kubernetes base directly.
-
-This allows consumers of the metrics to use a compatible monitoring pipeline to collect and analyze metrics from a variety of agents, even if they are maintained by different vendors.
-
-![Device metrics flowchart](/images/blog/2020-12-16-third-party-device-metrics-hits-ga/metrics-chart.png)
-
-## Disabling the NVIDIA GPU metrics - Warning {#nvidia-gpu-metrics-deprecated}
-
-With the graduation of the plugin monitoring system, Kubernetes is deprecating the NVIDIA GPU metrics that are being reported by the kubelet.
-
-With the [DisableAcceleratorMetrics](/docs/concepts/cluster-administration/system-metrics/#disable-accelerator-metrics) feature being enabled by default in Kubernetes 1.20, NVIDIA GPUs are no longer special citizens  in Kubernetes. This is a good thing in the spirit of being vendor-neutral, and enables the most suited people to maintain their plugin on their own release schedule!
-
-Users will now need to either install the [NVIDIA GDGM exporter](https://github.com/NVIDIA/gpu-monitoring-tools) or use [bindings](https://github.com/nvidia/go-nvml) to gather more accurate and complete metrics about NVIDIA GPUs. This deprecation means that you can no longer rely on metrics that were reported by kubelet, such as `container_accelerator_duty_cycle` or `container_accelerator_memory_used_bytes` which were used to gather NVIDIA GPU memory utilization.
-
-This means that users who used to rely on the NVIDIA GPU metrics reported by the kubelet, will need to update their reference and deploy the NVIDIA plugin. Namely the different metrics reported by Kubernetes map to the following metrics:
-
-| Kubernetes Metrics                         | NVIDIA dcgm-exporter metric                 |
-| ------------------------------------------ | ------------------------------------------- |
-| `container_accelerator_duty_cycle`         | `DCGM_FI_DEV_GPU_UTIL`                      |
-| `container_accelerator_memory_used_bytes`  | `DCGM_FI_DEV_FB_USED`                       |
-| `container_accelerator_memory_total_bytes` | `DCGM_FI_DEV_FB_FREE + DCGM_FI_DEV_FB_USED` |
-
-You might also be interested in other metrics such as `DCGM_FI_DEV_GPU_TEMP` (the GPU temperature) or DCGM_FI_DEV_POWER_USAGE (the power usage). The [default set](https://github.com/NVIDIA/gpu-monitoring-tools/blob/d5c9bb55b4d1529ca07068b7f81e690921ce2b59/etc/dcgm-exporter/default-counters.csv) is available in Nvidia's [Data Center GPU Manager documentation](https://docs.nvidia.com/datacenter/dcgm/latest/dcgm-api/group__dcgmFieldIdentifiers.html).
-
-Note that for this release you can still set the `DisableAcceleratorMetrics` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) to _false_, effectively re-enabling the ability for the kubelet to report NVIDIA GPU metrics.
-
-Paired with the graduation of the Pod Resources API, these tools can be used to generate GPU telemetry [that can be used in visualization dashboards](https://grafana.com/grafana/dashboards/12239), below is an example: 
-
-![Grafana visualization of device metrics](/images/blog/2020-12-16-third-party-device-metrics-hits-ga/grafana.png)
-
-## The Pod Resources API - What can I go on to do with this?
-
-As soon as this interface was introduced, many vendors started using it for widely different use cases! To list a few examples:
-
-The [kuryr-kubernetes](https://github.com/openstack/kuryr-kubernetes) CNI plugin in tandem with [intel-sriov-device-plugin](https://github.com/intel/sriov-network-device-plugin). This allowed the CNI plugin to know which allocation of SR-IOV Virtual Functions (VFs) the kubelet made and use that information to correctly setup the container network namespace and use a device with the appropriate NUMA node. We also expect this interface to be used to track the allocated and available resources with information about the NUMA topology of the worker node.
-
-Another use-case is GPU telemetry, where GPU metrics can be associated with the containers and pods that the GPU is assigned to. One such example is the NVIDIA `dcgm-exporter`, but others can be easily built in the same paradigm.
-
-The Pod Resources API is a simple gRPC service which informs clients of the pods the kubelet knows. The information concerns the devices assignment the kubelet made and the assignment of CPUs. This information is obtained from the internal state of the kubelet's Device Manager and CPU Manager respectively.
-
-You can see below a sample example of the API and how a go client could use that information in a few lines:
-
-```
-service PodResourcesLister {
-    rpc List(ListPodResourcesRequest) returns (ListPodResourcesResponse) {}
-    rpc GetAllocatableResources(AllocatableResourcesRequest) returns (AllocatableResourcesResponse) {}
-
-    // Kubernetes 1.21
-    rpc Watch(WatchPodResourcesRequest) returns (stream WatchPodResourcesResponse) {}
-}
-```
-
-```go
-func main() {
-	ctx, cancel := context.WithTimeout(context.Background(), connectionTimeout)
-	defer cancel()
-
-	socket := "/var/lib/kubelet/pod-resources/kubelet.sock"
-	conn, err := grpc.DialContext(ctx, socket, grpc.WithInsecure(), grpc.WithBlock(),
-		grpc.WithDialer(func(addr string, timeout time.Duration) (net.Conn, error) {
-			return net.DialTimeout("unix", addr, timeout)
-		}),
-	)
-
-	if err != nil {
-		panic(err)
-	}
-
-    client := podresourcesapi.NewPodResourcesListerClient(conn)
-    resp, err := client.List(ctx, &podresourcesapi.ListPodResourcesRequest{})
-	if err != nil {
-		panic(err)
-	}
-	net.Printf("%+v\n", resp)
-}
-```
-
-Finally, note that you can watch the number of requests made to the Pod Resources endpoint by watching the new kubelet metric called `pod_resources_endpoint_requests_total` on the kubelet's `/metrics` endpoint.
-
-## Is device monitoring suitable for production? Can I extend it? Can I contribute?
-
-Yes! This feature released in 1.13, almost 2 years ago, has seen broad adoption, is already used by different cloud managed services, and with its graduation to G.A in Kubernetes 1.20 is production ready!
-
-If you are a device vendor, you can start using it today! If you just want to monitor the devices in your cluster, go get the latest version of your monitoring plugin!
-
-If you feel passionate about that area, join the kubernetes community, help improve the API or contribute the device monitoring plugins!
-
-## Acknowledgements
-
-We thank the members of the community who have contributed to this feature or given feedback including members of WG-Resource-Management, SIG-Node and the Resource management forum!
@@ -1,63 +0,0 @@
---
-layout: blog
-title: "The Evolution of Kubernetes Dashboard"
-date: 2021-03-09
-slug: the-evolution-of-kubernetes-dashboard
---
-
-Authors: Marcin Maciaszczyk, Kubermatic & Sebastian Florek, Kubermatic
-
-In October 2020, the Kubernetes Dashboard officially turned five. As main project maintainers, we can barely believe that so much time has passed since our very first commits to the project. However, looking back with a bit of nostalgia, we realize that quite a lot has happened since then. Now it’s due time to celebrate “our baby” with a short recap.
-
-## How It All Began
-
-The initial idea behind the Kubernetes Dashboard project was to provide a web interface for Kubernetes. We wanted to reflect the kubectl functionality through an intuitive web UI. The main benefit from using the UI is to be able to quickly see things that do not work as expected (monitoring and troubleshooting). Also, the Kubernetes Dashboard is a great starting point for users that are new to the Kubernetes ecosystem.
-
-The very [first commit](https://github.com/kubernetes/dashboard/commit/5861187fa807ac1cc2d9b2ac786afeced065076c) to the Kubernetes Dashboard was made by Filip Grządkowski from Google on 16th October 2015 – just a few months from the initial commit to the Kubernetes repository. Our initial commits go back to November 2015 ([Sebastian committed on 16 November 2015](https://github.com/kubernetes/dashboard/commit/09e65b6bb08c49b926253de3621a73da05e400fd); [Marcin committed on 23 November 2015](https://github.com/kubernetes/dashboard/commit/1da4b1c25ef040818072c734f71333f9b4733f55)). Since that time, we’ve become regular contributors to the project. For the next two years, we worked closely with the Googlers, eventually becoming main project maintainers ourselves.
-
-{{< figure src="first-ui.png" caption="The First Version of the User Interface" >}}
-
-{{< figure src="along-the-way-ui.png" caption="Prototype of the New User Interface" >}}
-
-{{< figure src="current-ui.png" caption="The Current User Interface" >}}
-
-As you can see, the initial look and feel of the project were completely different from the current one. We have changed the design multiple times. The same has happened with the code itself.
-
-## Growing Up - The Big Migration
-
-At [the beginning of 2018](https://github.com/kubernetes/dashboard/pull/2727), we reached a point where AngularJS was getting closer to the end of its life, while the new Angular versions were published quite often. A lot of the libraries and the modules that we were using were following the trend. That forced us to spend a lot of the time rewriting the frontend part of the project to make it work with newer technologies.
-
-The migration came with many benefits like being able to refactor a lot of the code, introduce design patterns, reduce code complexity, and benefit from the new modules. However, you can imagine that the scale of the migration was huge. Luckily, there were a number of contributions from the community helping us with the resource support, new Kubernetes version support, i18n, and much more. After many long days and nights, we finally released the [first beta version](https://github.com/kubernetes/dashboard/releases/tag/v2.0.0-beta1) in July 2019, followed by the [2.0 release](https://github.com/kubernetes/dashboard/releases/tag/v2.0.0) in April 2020 — our baby had grown up.
-
-## Where Are We Standing in 2021?
-
-Due to limited resources, unfortunately, we were not able to offer extensive support for many different Kubernetes versions. So, we’ve decided to always try and support the latest Kubernetes version available at the time of the Kubernetes Dashboard release. The latest release, [Dashboard v2.2.0](https://github.com/kubernetes/dashboard/releases/tag/v2.2.0) provides support for Kubernetes v1.20.
-
-On top of that, we put in a great deal of effort into [improving resource support](https://github.com/kubernetes/dashboard/issues/5232). Meanwhile, we do offer support for most of the Kubernetes resources. Also, the Kubernetes Dashboard supports multiple languages: English, German, French, Japanese, Korean, Chinese (Traditional, Simplified, Traditional Hong Kong). Persian and Russian localizations are currently in progress. Moreover, we are working on the support for 3rd party themes and the design of the app in general. As you can see, quite a lot of things are going on.
-
-Luckily, we do have regular contributors with domain knowledge who are taking care of the project, updating the Helm charts, translations, Go modules, and more. But as always, there could be many more hands on deck. So if you are thinking about contributing to Kubernetes, keep us in mind ;)
-
-## What’s Next
-
-The Kubernetes Dashboard has been growing and prospering for more than 5 years now. It provides the community with an intuitive Web UI, thereby decreasing the complexity of Kubernetes and increasing its accessibility to new community members. We are proud of what the project has achieved so far, but this is by far not the end. These are our priorities for the future:
-
-*   Keep providing support for the new Kubernetes versions
-*   Keep improving the support for the existing resources
-*   Keep working on auth system improvements
-*   [Rewrite the API to use gRPC and shared informers](https://github.com/kubernetes/dashboard/pull/5449): This will allow us to improve the performance of the application but, most importantly, to support live updates coming from the Kubernetes project. It is one of the most requested features from the community.
-*   Split the application into two containers, one with the UI and the second with the API running inside.
-
-## The Kubernetes Dashboard in Numbers
-
-* Initial commit made on October 16, 2015
-* Over 100 million pulls from Dockerhub since the v2 release
-* 8 supported languages and the next 2 in progress
-* Over 3360 closed PRs
-* Over 2260 closed issues
-* 100% coverage of the supported core Kubernetes resources
-* Over 9000 stars on GitHub
-* Over 237 000 lines of code
-
-## Join Us
-
-As mentioned earlier, we are currently looking for more people to help us further develop and grow the project. We are open to contributions in multiple areas, i.e., [issues with help wanted label](https://github.com/kubernetes/dashboard/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22). Please feel free to reach out via GitHub or the #sig-ui channel in the [Kubernetes Slack](https://slack.k8s.io/).
@@ -13,7 +13,7 @@ new_case_study_styles: true
 heading_background: /images/case-studies/appdirect/banner1.jpg
 heading_title_logo: /images/appdirect_logo.png
 subheading: >
-  AppDirect: How AppDirect Supported the 10x Growth of Its Engineering Staff with Kubernetes
+  AppDirect: How AppDirect Supported the 10x Growth of Its Engineering Staff with Kubernetess
 case_study_details:
  - Company: AppDirect
  - Location: San Francisco, California
@@ -19,7 +19,6 @@ cid: community

 <div class="community__navbar">

-<a href="#values">Community Values</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 <a href="#conduct">Code of conduct </a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 <a href="#videos">Videos</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 <a href="#discuss">Discussions</a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
@@ -42,27 +41,9 @@ cid: community
    <img src="/images/community/kubernetes-community-final-05.jpg" alt="Kubernetes Conference Gallery" style="width:100%;margin-right:0% important" class="desktop">
  </div>
  <img src="/images/community/kubernetes-community-04-mobile.jpg" alt="Kubernetes Conference Gallery" style="width:100%;margin-bottom:3%" class="mobile">
-<a name="values"></a>
-</div>

-<div><a name="values"></a></div>
-<div class="conduct">
-<div class="conducttext">
-<br class="mobile"><br class="mobile">
-<br class="tablet"><br class="tablet">
-<div class="conducttextnobutton" style="margin-bottom:2%"><h1>Community Values</h1>
-The Kubernetes Community values are the keystone to the ongoing success of the project.<br>
-These principles guide every aspect of the Kubernetes project.
-<br>
-<a href="/community/values/">
-<br class="mobile"><br class="mobile">
-<span class="fullbutton">
-  READ MORE
-  </span>
-  </a>
-  </div><a name="conduct"></a>
-  </div>
-  </div>
+<a name="conduct"></a>
+</div>



@@ -37,8 +37,8 @@ when an individual is representing the project or its community.
 Instances of abusive, harassing, or otherwise unacceptable behavior in Kubernetes may be reported by contacting the [Kubernetes Code of Conduct Committee](https://git.k8s.io/community/committee-code-of-conduct) via <conduct@kubernetes.io>. For other projects, please contact a CNCF project maintainer or our mediator, Mishi Choudhary <mishi@linux.com>.

 This Code of Conduct is adapted from the Contributor Covenant
-(https://contributor-covenant.org), version 1.2.0, available at
-https://contributor-covenant.org/version/1/2/0/
+(http://contributor-covenant.org), version 1.2.0, available at
+http://contributor-covenant.org/version/1/2/0/

 ### CNCF Events Code of Conduct

@@ -1,28 +0,0 @@
-<!-- Do not edit this file directly. Get the latest from
-     https://git.k8s.io/community/values.md -->
-
-# Kubernetes Community Values
-
-Kubernetes Community culture is frequently cited as a substantial contributor to the meteoric rise of this Open Source project.  Below are the distilled values which have evolved over the last many years in our community pushing our project and peers toward constant improvement.
-
-## Distribution is better than centralization
-
-The scale of the Kubernetes project is only viable through high-trust and high-visibility distribution of work, which includes delegation of authority, decision making, technical design, code ownership, and documentation.  Distributed asynchronous ownership, collaboration, communication and decision making are the cornerstone of our world-wide community.
-
-## Community over product or company
-
-We are here as a community first, our allegiance is to the intentional stewardship of the Kubernetes project for the benefit of all its members and users everywhere.  We support working together publicly for the common goal of a vibrant interoperable ecosystem providing an excellent experience for our users. Individuals gain status through work, companies gain status through their commitments to support this community and fund the resources necessary for the project  to operate.
-
-## Automation over process
-
-Large projects have a lot of less exciting, yet, hard work.  We value time spent automating repetitive work more highly than toil. Where that work cannot be automated, it is our culture to recognize and reward all types of contributions. However, heroism is not sustainable.
-
-## Inclusive is better than exclusive
-
-Broadly successful and useful technology requires different perspectives and skill sets which can only be heard in a welcoming and respectful environment.  Community membership is a privilege, not a right. Community Leadership is earned through effort, scope, quality, quantity, and duration of contributions. Our community shows respect for the time and effort put into a discussion regardless of where a contributor is on their growth path.
-
-## Evolution is better than stagnation
-
-Openness to new ideas and studied technological evolution make Kubernetes a stronger project.  Continual improvement, servant leadership, mentorship and respect are the foundations of the Kubernetes project culture. It is the duty for leaders in the Kubernetes community to find, sponsor, and promote new community members. Leaders should expect to step aside. Community members should expect to step up.
-
-**"Culture eats strategy for breakfast."   --Peter Drucker**
@@ -1,13 +0,0 @@
---
-title: Community
-layout: basic
-cid: community
-css: /css/community.css
---
-
-<div class="community_main">
-
-<div class="cncf_coc_container">
-{{< include "/static/community-values.md" >}}
-</div>
-</div>
@@ -11,20 +11,20 @@ aliases:

 <!-- overview -->

-This document catalogs the communication paths between the control plane (apiserver) and the Kubernetes cluster. The intent is to allow users to customize their installation to harden the network configuration such that the cluster can be run on an untrusted network (or on fully public IPs on a cloud provider).
+This document catalogs the communication paths between the control plane (really the apiserver) and the Kubernetes cluster. The intent is to allow users to customize their installation to harden the network configuration such that the cluster can be run on an untrusted network (or on fully public IPs on a cloud provider).



 <!-- body -->

 ## Node to Control Plane
-Kubernetes has a "hub-and-spoke" API pattern. All API usage from nodes (or the pods they run) terminates at the apiserver. None of the other control plane components are designed to expose remote services. The apiserver is configured to listen for remote connections on a secure HTTPS port (typically 443) with one or more forms of client [authentication](/docs/reference/access-authn-authz/authentication/) enabled.
+Kubernetes has a "hub-and-spoke" API pattern. All API usage from nodes (or the pods they run) terminate at the apiserver (none of the other control plane components are designed to expose remote services). The apiserver is configured to listen for remote connections on a secure HTTPS port (typically 443) with one or more forms of client [authentication](/docs/reference/access-authn-authz/authentication/) enabled.
 One or more forms of [authorization](/docs/reference/access-authn-authz/authorization/) should be enabled, especially if [anonymous requests](/docs/reference/access-authn-authz/authentication/#anonymous-requests) or [service account tokens](/docs/reference/access-authn-authz/authentication/#service-account-tokens) are allowed.

 Nodes should be provisioned with the public root certificate for the cluster such that they can connect securely to the apiserver along with valid client credentials. A good approach is that the client credentials provided to the kubelet are in the form of a client certificate. See [kubelet TLS bootstrapping](/docs/reference/command-line-tools-reference/kubelet-tls-bootstrapping/) for automated provisioning of kubelet client certificates.

 Pods that wish to connect to the apiserver can do so securely by leveraging a service account so that Kubernetes will automatically inject the public root certificate and a valid bearer token into the pod when it is instantiated.
-The `kubernetes` service (in `default` namespace) is configured with a virtual IP address that is redirected (via kube-proxy) to the HTTPS endpoint on the apiserver.
+The `kubernetes` service (in all namespaces) is configured with a virtual IP address that is redirected (via kube-proxy) to the HTTPS endpoint on the apiserver.

 The control plane components also communicate with the cluster apiserver over the secure port.

@@ -42,7 +42,7 @@ The connections from the apiserver to the kubelet are used for:
 * Attaching (through kubectl) to running pods.
 * Providing the kubelet's port-forwarding functionality.

-These connections terminate at the kubelet's HTTPS endpoint. By default, the apiserver does not verify the kubelet's serving certificate, which makes the connection subject to man-in-the-middle attacks and **unsafe** to run over untrusted and/or public networks.
+These connections terminate at the kubelet's HTTPS endpoint. By default, the apiserver does not verify the kubelet's serving certificate, which makes the connection subject to man-in-the-middle attacks, and **unsafe** to run over untrusted and/or public networks.

 To verify this connection, use the `--kubelet-certificate-authority` flag to provide the apiserver with a root certificate bundle to use to verify the kubelet's serving certificate.

@@ -53,20 +53,20 @@ Finally, [Kubelet authentication and/or authorization](/docs/reference/command-l

 ### apiserver to nodes, pods, and services

-The connections from the apiserver to a node, pod, or service default to plain HTTP connections and are therefore neither authenticated nor encrypted. They can be run over a secure HTTPS connection by prefixing `https:` to the node, pod, or service name in the API URL, but they will not validate the certificate provided by the HTTPS endpoint nor provide client credentials. So while the connection will be encrypted, it will not provide any guarantees of integrity. These connections **are not currently safe** to run over untrusted or public networks.
+The connections from the apiserver to a node, pod, or service default to plain HTTP connections and are therefore neither authenticated nor encrypted. They can be run over a secure HTTPS connection by prefixing `https:` to the node, pod, or service name in the API URL, but they will not validate the certificate provided by the HTTPS endpoint nor provide client credentials so while the connection will be encrypted, it will not provide any guarantees of integrity. These connections **are not currently safe** to run over untrusted and/or public networks.

 ### SSH tunnels

 Kubernetes supports SSH tunnels to protect the control plane to nodes communication paths. In this configuration, the apiserver initiates an SSH tunnel to each node in the cluster (connecting to the ssh server listening on port 22) and passes all traffic destined for a kubelet, node, pod, or service through the tunnel.
 This tunnel ensures that the traffic is not exposed outside of the network in which the nodes are running.

-SSH tunnels are currently deprecated, so you shouldn't opt to use them unless you know what you are doing. The Konnectivity service is a replacement for this communication channel.
+SSH tunnels are currently deprecated so you shouldn't opt to use them unless you know what you are doing. The Konnectivity service is a replacement for this communication channel.

 ### Konnectivity service

 {{< feature-state for_k8s_version="v1.18" state="beta" >}}

-As a replacement to the SSH tunnels, the Konnectivity service provides TCP level proxy for the control plane to cluster communication. The Konnectivity service consists of two parts: the Konnectivity server in the control plane network and the Konnectivity agents in the nodes network. The Konnectivity agents initiate connections to the Konnectivity server and maintain the network connections.
+As a replacement to the SSH tunnels, the Konnectivity service provides TCP level proxy for the control plane to cluster communication. The Konnectivity service consists of two parts: the Konnectivity server and the Konnectivity agents, running in the control plane network and the nodes network respectively. The Konnectivity agents initiate connections to the Konnectivity server and maintain the network connections.
 After enabling the Konnectivity service, all control plane to nodes traffic goes through these connections.

 Follow the [Konnectivity service task](/docs/tasks/extend-kubernetes/setup-konnectivity/) to set up the Konnectivity service in your cluster.
@@ -102,7 +102,7 @@ Other control loops can observe that reported data and take their own actions.
 In the thermostat example, if the room is very cold then a different controller
 might also turn on a frost protection heater. With Kubernetes clusters, the control
 plane indirectly works with IP address management tools, storage services,
-cloud provider APIs, and other services by
+cloud provider APIS, and other services by
 [extending Kubernetes](/docs/concepts/extend-kubernetes/) to implement that.

 ## Desired versus current state {#desired-vs-current}
@@ -115,7 +115,7 @@ control loops automatically fix failures. This means that,
 potentially, your cluster never reaches a stable state.

 As long as the controllers for your cluster are running and able to make
-useful changes, it doesn't matter if the overall state is stable or not.
+useful changes, it doesn't matter if the overall state is or is not stable.

 ## Design

@@ -11,13 +11,12 @@ weight: 10

 Kubernetes runs your workload by placing containers into Pods to run on _Nodes_.
 A node may be a virtual or physical machine, depending on the cluster. Each node
-is managed by the
-{{< glossary_tooltip text="control plane" term_id="control-plane" >}}
-and contains the services necessary to run
-{{< glossary_tooltip text="Pods" term_id="pod" >}}
+contains the services necessary to run
+{{< glossary_tooltip text="Pods" term_id="pod" >}}, managed by the
+{{< glossary_tooltip text="control plane" term_id="control-plane" >}}.

 Typically you have several nodes in a cluster; in a learning or resource-limited
-environment, you might have only one node.
+environment, you might have just one.

 The [components](/docs/concepts/overview/components/#node-components) on a node include the
 {{< glossary_tooltip text="kubelet" term_id="kubelet" >}}, a
@@ -31,7 +30,7 @@ The [components](/docs/concepts/overview/components/#node-components) on a node
 There are two main ways to have Nodes added to the {{< glossary_tooltip text="API server" term_id="kube-apiserver" >}}:

 1. The kubelet on a node self-registers to the control plane
-2. You (or another human user) manually add a Node object
+2. You, or another human user, manually add a Node object

 After you create a Node object, or the kubelet on a node self-registers, the
 control plane checks whether the new Node object is valid. For example, if you
@@ -52,8 +51,8 @@ try to create a Node from the following JSON manifest:

 Kubernetes creates a Node object internally (the representation). Kubernetes checks
 that a kubelet has registered to the API server that matches the `metadata.name`
-field of the Node. If the node is healthy (i.e. all necessary services are running),
-then it is eligible to run a Pod. Otherwise, that node is ignored for any cluster activity
+field of the Node. If the node is healthy (if all necessary services are running),
+it is eligible to run a Pod. Otherwise, that node is ignored for any cluster activity
 until it becomes healthy.

 {{< note >}}
@@ -96,14 +95,14 @@ You can create and modify Node objects using
 When you want to create Node objects manually, set the kubelet flag `--register-node=false`.

 You can modify Node objects regardless of the setting of `--register-node`.
-For example, you can set labels on an existing Node or mark it unschedulable.
+For example, you can set labels on an existing Node, or mark it unschedulable.

 You can use labels on Nodes in conjunction with node selectors on Pods to control
 scheduling. For example, you can constrain a Pod to only be eligible to run on
 a subset of the available nodes.

 Marking a node as unschedulable prevents the scheduler from placing new pods onto
-that Node but does not affect existing Pods on the Node. This is useful as a
+that Node, but does not affect existing Pods on the Node. This is useful as a
 preparatory step before a node reboot or other maintenance.

 To mark a Node unschedulable, run:
@@ -179,14 +178,14 @@ The node condition is represented as a JSON object. For example, the following s
 ]
 ```

-If the Status of the Ready condition remains `Unknown` or `False` for longer than the `pod-eviction-timeout` (an argument passed to the {{< glossary_tooltip text="kube-controller-manager" term_id="kube-controller-manager" >}}), then all the Pods on the node are scheduled for deletion by the node controller. The default eviction timeout duration is **five minutes**. In some cases when the node is unreachable, the API server is unable to communicate with the kubelet on the node. The decision to delete the pods cannot be communicated to the kubelet until communication with the API server is re-established. In the meantime, the pods that are scheduled for deletion may continue to run on the partitioned node.
+If the Status of the Ready condition remains `Unknown` or `False` for longer than the `pod-eviction-timeout` (an argument passed to the {{< glossary_tooltip text="kube-controller-manager" term_id="kube-controller-manager" >}}), all the Pods on the node are scheduled for deletion by the node controller. The default eviction timeout duration is **five minutes**. In some cases when the node is unreachable, the API server is unable to communicate with the kubelet on the node. The decision to delete the pods cannot be communicated to the kubelet until communication with the API server is re-established. In the meantime, the pods that are scheduled for deletion may continue to run on the partitioned node.

 The node controller does not force delete pods until it is confirmed that they have stopped
 running in the cluster. You can see the pods that might be running on an unreachable node as
 being in the `Terminating` or `Unknown` state. In cases where Kubernetes cannot deduce from the
 underlying infrastructure if a node has permanently left a cluster, the cluster administrator
-may need to delete the node object by hand. Deleting the node object from Kubernetes causes
-all the Pod objects running on the node to be deleted from the API server and frees up their
+may need to delete the node object by hand.  Deleting the node object from Kubernetes causes
+all the Pod objects running on the node to be deleted from the API server, and frees up their
 names.

 The node lifecycle controller automatically creates
@@ -199,7 +198,7 @@ for more details.

 ### Capacity and Allocatable {#capacity}

-Describes the resources available on the node: CPU, memory, and the maximum
+Describes the resources available on the node: CPU, memory and the maximum
 number of pods that can be scheduled onto the node.

 The fields in the capacity block indicate the total amount of resources that a
@@ -225,27 +224,25 @@ CIDR block to the node when it is registered (if CIDR assignment is turned on).

 The second is keeping the node controller's internal list of nodes up to date with
 the cloud provider's list of available machines. When running in a cloud
-environment and whenever a node is unhealthy, the node controller asks the cloud
+environment, whenever a node is unhealthy, the node controller asks the cloud
 provider if the VM for that node is still available. If not, the node
 controller deletes the node from its list of nodes.

 The third is monitoring the nodes' health. The node controller is
-responsible for:
- Updating the NodeReady condition of NodeStatus to ConditionUnknown when a node
-  becomes unreachable, as the node controller stops receiving heartbeats for some
-  reason such as the node being down.
- Evicting all the pods from the node using graceful termination if
-  the node continues to be unreachable. The default timeouts are 40s to start
-  reporting ConditionUnknown and 5m after that to start evicting pods.
-
-The node controller checks the state of each node every `--node-monitor-period` seconds.
+responsible for updating the NodeReady condition of NodeStatus to
+ConditionUnknown when a node becomes unreachable (i.e. the node controller stops
+receiving heartbeats for some reason, for example due to the node being down), and then later evicting
+all the pods from the node (using graceful termination) if the node continues
+to be unreachable. (The default timeouts are 40s to start reporting
+ConditionUnknown and 5m after that to start evicting pods.) The node controller
+checks the state of each node every `--node-monitor-period` seconds.

 #### Heartbeats

 Heartbeats, sent by Kubernetes nodes, help determine the availability of a node.

 There are two forms of heartbeats: updates of `NodeStatus` and the
-[Lease object](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#lease-v1-coordination-k8s-io).
+[Lease object](/docs/reference/generated/kubernetes-api/{{< latest-version >}}/#lease-v1-coordination-k8s-io).
 Each Node has an associated Lease object in the `kube-node-lease`
 {{< glossary_tooltip term_id="namespace" text="namespace">}}.
 Lease is a lightweight resource, which improves the performance
@@ -254,14 +251,13 @@ of the node heartbeats as the cluster scales.
 The kubelet is responsible for creating and updating the `NodeStatus` and
 a Lease object.

- The kubelet updates the `NodeStatus` either when there is change in status
+- The kubelet updates the `NodeStatus` either when there is change in status,
  or if there has been no update for a configured interval. The default interval
-  for `NodeStatus` updates is 5 minutes, which is much longer than the 40 second default
-  timeout for unreachable nodes.
+  for `NodeStatus` updates is 5 minutes (much longer than the 40 second default
+  timeout for unreachable nodes).
 - The kubelet creates and then updates its Lease object every 10 seconds
  (the default update interval). Lease updates occur independently from the
-  `NodeStatus` updates. If the Lease update fails, the kubelet retries with
-  exponential backoff starting at 200 milliseconds and capped at 7 seconds.
+  `NodeStatus` updates. If the Lease update fails, the kubelet retries with exponential backoff starting at 200 milliseconds and capped at 7 seconds.

 #### Reliability

@@ -272,25 +268,23 @@ from more than 1 node per 10 seconds.
 The node eviction behavior changes when a node in a given availability zone
 becomes unhealthy. The node controller checks what percentage of nodes in the zone
 are unhealthy (NodeReady condition is ConditionUnknown or ConditionFalse) at
-the same time:
- If the fraction of unhealthy nodes is at least `--unhealthy-zone-threshold` 
-  (default 0.55), then the eviction rate is reduced.
- If the cluster is small (i.e. has less than or equal to
-  `--large-cluster-size-threshold` nodes - default 50), then evictions are stopped.
- Otherwise, the eviction rate is reduced to `--secondary-node-eviction-rate`
-  (default 0.01) per second.
-
-The reason these policies are implemented per availability zone is because one
-availability zone might become partitioned from the master while the others remain
-connected. If your cluster does not span multiple cloud provider availability zones,
-then there is only one availability zone (i.e. the whole cluster).
+the same time. If the fraction of unhealthy nodes is at least
+`--unhealthy-zone-threshold` (default 0.55) then the eviction rate is reduced:
+if the cluster is small (i.e. has less than or equal to
+`--large-cluster-size-threshold` nodes - default 50) then evictions are
+stopped, otherwise the eviction rate is reduced to
+`--secondary-node-eviction-rate` (default 0.01) per second. The reason these
+policies are implemented per availability zone is because one availability zone
+might become partitioned from the master while the others remain connected. If
+your cluster does not span multiple cloud provider availability zones, then
+there is only one availability zone (the whole cluster).

 A key reason for spreading your nodes across availability zones is so that the
 workload can be shifted to healthy zones when one entire zone goes down.
-Therefore, if all nodes in a zone are unhealthy, then the node controller evicts at
+Therefore, if all nodes in a zone are unhealthy then the node controller evicts at
 the normal rate of `--node-eviction-rate`.  The corner case is when all zones are
 completely unhealthy (i.e. there are no healthy nodes in the cluster). In such a
-case, the node controller assumes that there is some problem with master
+case, the node controller assumes that there's some problem with master
 connectivity and stops all evictions until some connectivity is restored.

 The node controller is also responsible for evicting pods running on nodes with
@@ -308,8 +302,8 @@ eligible for, effectively removing incoming load balancer traffic from the cordo

 ### Node capacity

-Node objects track information about the Node's resource capacity: for example, the amount
-of memory available and the number of CPUs.
+Node objects track information about the Node's resource capacity (for example: the amount
+of memory available, and the number of CPUs).
 Nodes that [self register](#self-registration-of-nodes) report their capacity during
 registration. If you [manually](#manual-node-administration) add a Node, then
 you need to set the node's capacity information when you add it.
@@ -336,26 +330,6 @@ the kubelet can use topology hints when making resource assignment decisions.
 See [Control Topology Management Policies on a Node](/docs/tasks/administer-cluster/topology-manager/)
 for more information.

-## Graceful Node Shutdown {#graceful-node-shutdown}
-
-{{< feature-state state="alpha" for_k8s_version="v1.20" >}}
-
-If you have enabled the `GracefulNodeShutdown` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/), then the kubelet attempts to detect the node system shutdown and terminates pods running on the node.
-Kubelet ensures that pods follow the normal [pod termination process](/docs/concepts/workloads/pods/pod-lifecycle/#pod-termination) during the node shutdown.
-
-When the `GracefulNodeShutdown` feature gate is enabled, kubelet uses [systemd inhibitor locks](https://www.freedesktop.org/wiki/Software/systemd/inhibit/) to delay the node shutdown with a given duration. During a shutdown, kubelet terminates pods in two phases:
-
-1. Terminate regular pods running on the node.
-2. Terminate [critical pods](/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/#marking-pod-as-critical) running on the node.
-
-Graceful Node Shutdown feature is configured with two [`KubeletConfiguration`](/docs/tasks/administer-cluster/kubelet-config-file/) options:
-* `ShutdownGracePeriod`:
-  * Specifies the total duration that the node should delay the shutdown by. This is the total grace period for pod termination for both regular and [critical pods](/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/#marking-pod-as-critical).
-* `ShutdownGracePeriodCriticalPods`:
-  * Specifies the duration used to terminate [critical pods](/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/#marking-pod-as-critical) during a node shutdown. This should be less than `ShutdownGracePeriod`.
-
-For example, if `ShutdownGracePeriod=30s`, and `ShutdownGracePeriodCriticalPods=10s`, kubelet will delay the node shutdown by 30 seconds. During the shutdown, the first 20 (30-10) seconds would be reserved for gracefully terminating normal pods, and the last 10 seconds would be reserved for terminating [critical pods](/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/#marking-pod-as-critical).
-

 ## {{% heading "whatsnext" %}}

@@ -26,12 +26,12 @@ See the guides in [Setup](/docs/setup/) for examples of how to plan, set up, and

 Before choosing a guide, here are some considerations:

- - Do you want to try out Kubernetes on your computer, or do you want to build a high-availability, multi-node cluster? Choose distros best suited for your needs.
+ - Do you just want to try out Kubernetes on your computer, or do you want to build a high-availability, multi-node cluster? Choose distros best suited for your needs.
 - Will you be using **a hosted Kubernetes cluster**, such as [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine/), or **hosting your own cluster**?
 - Will your cluster be **on-premises**, or **in the cloud (IaaS)**? Kubernetes does not directly support hybrid clusters. Instead, you can set up multiple clusters.
 - **If you are configuring Kubernetes on-premises**, consider which [networking model](/docs/concepts/cluster-administration/networking/) fits best.
 - Will you be running Kubernetes on **"bare metal" hardware** or on **virtual machines (VMs)**?
- - Do you **want to run a cluster**, or do you expect to do **active development of Kubernetes project code**? If the
+ - Do you **just want to run a cluster**, or do you expect to do **active development of Kubernetes project code**? If the
   latter, choose an actively-developed distro. Some distros only use binary releases, but
   offer a greater variety of choices.
 - Familiarize yourself with the [components](/docs/concepts/overview/components/) needed to run a cluster.
@@ -45,7 +45,7 @@ Before choosing a guide, here are some considerations:

 ## Securing a cluster

-* [Generate Certificates](/docs/tasks/administer-cluster/certificates/) describes the steps to generate certificates using different tool chains.
+* [Certificates](/docs/concepts/cluster-administration/certificates/) describes the steps to generate certificates using different tool chains.

 * [Kubernetes Container Environment](/docs/concepts/containers/container-environment/) describes the environment for Kubelet managed containers on a Kubernetes node.

@@ -4,6 +4,249 @@ content_type: concept
 weight: 20
 ---

+
 <!-- overview -->

-To learn how to generate certificates for your cluster, see [Certificates](/docs/tasks/administer-cluster/certificates/).
+When using client certificate authentication, you can generate certificates
+manually through `easyrsa`, `openssl` or `cfssl`.
+
+
+
+
+<!-- body -->
+
+### easyrsa
+
+**easyrsa** can manually generate certificates for your cluster.
+
+1.  Download, unpack, and initialize the patched version of easyrsa3.
+
+        curl -LO https://storage.googleapis.com/kubernetes-release/easy-rsa/easy-rsa.tar.gz
+        tar xzf easy-rsa.tar.gz
+        cd easy-rsa-master/easyrsa3
+        ./easyrsa init-pki
+1.  Generate a new certificate authority (CA). `--batch` sets automatic mode;
+    `--req-cn` specifies the Common Name (CN) for the CA's new root certificate.
+
+        ./easyrsa --batch "--req-cn=${MASTER_IP}@`date +%s`" build-ca nopass
+1.  Generate server certificate and key.
+    The argument `--subject-alt-name` sets the possible IPs and DNS names the API server will
+    be accessed with. The `MASTER_CLUSTER_IP` is usually the first IP from the service CIDR
+    that is specified as the `--service-cluster-ip-range` argument for both the API server and
+    the controller manager component. The argument `--days` is used to set the number of days
+    after which the certificate expires.
+    The sample below also assumes that you are using `cluster.local` as the default
+    DNS domain name.
+
+        ./easyrsa --subject-alt-name="IP:${MASTER_IP},"\
+        "IP:${MASTER_CLUSTER_IP},"\
+        "DNS:kubernetes,"\
+        "DNS:kubernetes.default,"\
+        "DNS:kubernetes.default.svc,"\
+        "DNS:kubernetes.default.svc.cluster,"\
+        "DNS:kubernetes.default.svc.cluster.local" \
+        --days=10000 \
+        build-server-full server nopass
+1.  Copy `pki/ca.crt`, `pki/issued/server.crt`, and `pki/private/server.key` to your directory.
+1.  Fill in and add the following parameters into the API server start parameters:
+
+        --client-ca-file=/yourdirectory/ca.crt
+        --tls-cert-file=/yourdirectory/server.crt
+        --tls-private-key-file=/yourdirectory/server.key
+
+### openssl
+
+**openssl** can manually generate certificates for your cluster.
+
+1.  Generate a ca.key with 2048bit:
+
+        openssl genrsa -out ca.key 2048
+1.  According to the ca.key generate a ca.crt (use -days to set the certificate effective time):
+
+        openssl req -x509 -new -nodes -key ca.key -subj "/CN=${MASTER_IP}" -days 10000 -out ca.crt
+1.  Generate a server.key with 2048bit:
+
+        openssl genrsa -out server.key 2048
+1.  Create a config file for generating a Certificate Signing Request (CSR).
+    Be sure to substitute the values marked with angle brackets (e.g. `<MASTER_IP>`)
+    with real values before saving this to a file (e.g. `csr.conf`).
+    Note that the value for `MASTER_CLUSTER_IP` is the service cluster IP for the
+    API server as described in previous subsection.
+    The sample below also assumes that you are using `cluster.local` as the default
+    DNS domain name.
+
+        [ req ]
+        default_bits = 2048
+        prompt = no
+        default_md = sha256
+        req_extensions = req_ext
+        distinguished_name = dn
+
+        [ dn ]
+        C = <country>
+        ST = <state>
+        L = <city>
+        O = <organization>
+        OU = <organization unit>
+        CN = <MASTER_IP>
+
+        [ req_ext ]
+        subjectAltName = @alt_names
+
+        [ alt_names ]
+        DNS.1 = kubernetes
+        DNS.2 = kubernetes.default
+        DNS.3 = kubernetes.default.svc
+        DNS.4 = kubernetes.default.svc.cluster
+        DNS.5 = kubernetes.default.svc.cluster.local
+        IP.1 = <MASTER_IP>
+        IP.2 = <MASTER_CLUSTER_IP>
+
+        [ v3_ext ]
+        authorityKeyIdentifier=keyid,issuer:always
+        basicConstraints=CA:FALSE
+        keyUsage=keyEncipherment,dataEncipherment
+        extendedKeyUsage=serverAuth,clientAuth
+        subjectAltName=@alt_names
+1.  Generate the certificate signing request based on the config file:
+
+        openssl req -new -key server.key -out server.csr -config csr.conf
+1.  Generate the server certificate using the ca.key, ca.crt and server.csr:
+
+        openssl x509 -req -in server.csr -CA ca.crt -CAkey ca.key \
+        -CAcreateserial -out server.crt -days 10000 \
+        -extensions v3_ext -extfile csr.conf
+1.  View the certificate:
+
+        openssl x509  -noout -text -in ./server.crt
+
+Finally, add the same parameters into the API server start parameters.
+
+### cfssl
+
+**cfssl** is another tool for certificate generation.
+
+1.  Download, unpack and prepare the command line tools as shown below.
+    Note that you may need to adapt the sample commands based on the hardware
+    architecture and cfssl version you are using.
+
+        curl -L https://github.com/cloudflare/cfssl/releases/download/v1.4.1/cfssl_1.4.1_linux_amd64 -o cfssl
+        chmod +x cfssl
+        curl -L https://github.com/cloudflare/cfssl/releases/download/v1.4.1/cfssljson_1.4.1_linux_amd64 -o cfssljson
+        chmod +x cfssljson
+        curl -L https://github.com/cloudflare/cfssl/releases/download/v1.4.1/cfssl-certinfo_1.4.1_linux_amd64 -o cfssl-certinfo
+        chmod +x cfssl-certinfo
+1.  Create a directory to hold the artifacts and initialize cfssl:
+
+        mkdir cert
+        cd cert
+        ../cfssl print-defaults config > config.json
+        ../cfssl print-defaults csr > csr.json
+1.  Create a JSON config file for generating the CA file, for example, `ca-config.json`:
+
+        {
+          "signing": {
+            "default": {
+              "expiry": "8760h"
+            },
+            "profiles": {
+              "kubernetes": {
+                "usages": [
+                  "signing",
+                  "key encipherment",
+                  "server auth",
+                  "client auth"
+                ],
+                "expiry": "8760h"
+              }
+            }
+          }
+        }
+1.  Create a JSON config file for CA certificate signing request (CSR), for example,
+    `ca-csr.json`. Be sure to replace the values marked with angle brackets with
+    real values you want to use.
+
+        {
+          "CN": "kubernetes",
+          "key": {
+            "algo": "rsa",
+            "size": 2048
+          },
+          "names":[{
+            "C": "<country>",
+            "ST": "<state>",
+            "L": "<city>",
+            "O": "<organization>",
+            "OU": "<organization unit>"
+          }]
+        }
+1.  Generate CA key (`ca-key.pem`) and certificate (`ca.pem`):
+
+        ../cfssl gencert -initca ca-csr.json | ../cfssljson -bare ca
+1.  Create a JSON config file for generating keys and certificates for the API
+    server, for example, `server-csr.json`. Be sure to replace the values in angle brackets with
+    real values you want to use. The `MASTER_CLUSTER_IP` is the service cluster
+    IP for the API server as described in previous subsection.
+    The sample below also assumes that you are using `cluster.local` as the default
+    DNS domain name.
+
+        {
+          "CN": "kubernetes",
+          "hosts": [
+            "127.0.0.1",
+            "<MASTER_IP>",
+            "<MASTER_CLUSTER_IP>",
+            "kubernetes",
+            "kubernetes.default",
+            "kubernetes.default.svc",
+            "kubernetes.default.svc.cluster",
+            "kubernetes.default.svc.cluster.local"
+          ],
+          "key": {
+            "algo": "rsa",
+            "size": 2048
+          },
+          "names": [{
+            "C": "<country>",
+            "ST": "<state>",
+            "L": "<city>",
+            "O": "<organization>",
+            "OU": "<organization unit>"
+          }]
+        }
+1.  Generate the key and certificate for the API server, which are by default
+    saved into file `server-key.pem` and `server.pem` respectively:
+
+        ../cfssl gencert -ca=ca.pem -ca-key=ca-key.pem \
+        --config=ca-config.json -profile=kubernetes \
+        server-csr.json | ../cfssljson -bare server
+
+
+## Distributing Self-Signed CA Certificate
+
+A client node may refuse to recognize a self-signed CA certificate as valid.
+For a non-production deployment, or for a deployment that runs behind a company
+firewall, you can distribute a self-signed CA certificate to all clients and
+refresh the local list for valid certificates.
+
+On each client, perform the following operations:
+
+```bash
+sudo cp ca.crt /usr/local/share/ca-certificates/kubernetes.crt
+sudo update-ca-certificates
+```
+
+```
+Updating certificates in /etc/ssl/certs...
+1 added, 0 removed; done.
+Running hooks in /etc/ca-certificates/update.d....
+done.
+```
+
+## Certificates API
+
+You can use the `certificates.k8s.io` API to provision
+x509 certificates to use for authentication as documented
+[here](/docs/tasks/tls/managing-tls-in-a-cluster).
+
+
@@ -6,7 +6,7 @@ min-kubernetes-server-version: v1.18

 <!-- overview -->

-{{< feature-state state="beta"  for_k8s_version="v1.20" >}}
+{{< feature-state state="alpha"  for_k8s_version="v1.18" >}}

 Controlling the behavior of the Kubernetes API server in an overload situation
 is a key task for cluster administrators. The {{< glossary_tooltip
@@ -37,30 +37,25 @@ Fairness feature enabled.

 <!-- body -->

-## Enabling/Disabling API Priority and Fairness
+## Enabling API Priority and Fairness

 The API Priority and Fairness feature is controlled by a feature gate
-and is enabled by default.  See
+and is not enabled by default.  See
 [Feature Gates](/docs/reference/command-line-tools-reference/feature-gates/)
-for a general explanation of feature gates and how to enable and
-disable them.  The name of the feature gate for APF is
-"APIPriorityAndFairness".  This feature also involves an {{<
-glossary_tooltip term_id="api-group" text="API Group" >}} with: (a) a
-`v1alpha1` version, disabled by default, and (b) a `v1beta1`
-version,  enabled by default.  You can disable the feature
-gate and API group v1beta1 version by adding the following
-command-line flags to your `kube-apiserver` invocation:
+for a general explanation of feature gates and how to enable and disable them.  The
+name of the feature gate for APF is "APIPriorityAndFairness".  This
+feature also involves an {{< glossary_tooltip term_id="api-group"
+text="API Group" >}} that must be enabled.  You can do these
+things by adding the following command-line flags to your
+`kube-apiserver` invocation:

 ```shell
 kube-apiserver \
--feature-gates=APIPriorityAndFairness=false \
--runtime-config=flowcontrol.apiserver.k8s.io/v1beta1=false \
+--feature-gates=APIPriorityAndFairness=true \
+--runtime-config=flowcontrol.apiserver.k8s.io/v1alpha1=true \
 # …and other flags as usual
 ```

-Alternatively, you can enable the v1alpha1 version of the API group
-with `--runtime-config=flowcontrol.apiserver.k8s.io/v1alpha1=true`.
-
 The command-line flag `--enable-priority-and-fairness=false` will disable the
 API Priority and Fairness feature, even if other flags have enabled it.

@@ -194,14 +189,12 @@ that originate from outside your cluster.

 ## Resources
 The flow control API involves two kinds of resources.
-[PriorityLevelConfigurations](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#prioritylevelconfiguration-v1beta1-flowcontrol-apiserver-k8s-io)
+[PriorityLevelConfigurations](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#prioritylevelconfiguration-v1alpha1-flowcontrol-apiserver-k8s-io)
 define the available isolation classes, the share of the available concurrency
 budget that each can handle, and allow for fine-tuning queuing behavior.
-[FlowSchemas](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#flowschema-v1beta1-flowcontrol-apiserver-k8s-io)
-are used to classify individual inbound requests, matching each to a
-single PriorityLevelConfiguration.  There is also a `v1alpha1` version
-of the same API group, and it has the same Kinds with the same syntax and
-semantics.
+[FlowSchemas](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#flowschema-v1alpha1-flowcontrol-apiserver-k8s-io)
+are used to classify individual inbound requests, matching each to a single
+PriorityLevelConfiguration.

 ### PriorityLevelConfiguration
 A PriorityLevelConfiguration represents a single isolation class. Each
@@ -338,13 +331,6 @@ PriorityLevelConfigurations.

 ### Metrics

-{{< note >}}
-In versions of Kubernetes before v1.20, the labels `flow_schema` and
-`priority_level` were inconsistently named `flowSchema` and `priorityLevel`,
-respectively. If you're running Kubernetes versions v1.19 and earlier, you
-should refer to the documentation for your version.
-{{< /note >}}
-
 When you enable the API Priority and Fairness feature, the kube-apiserver
 exports additional metrics. Monitoring these can help you determine whether your
 configuration is inappropriately throttling important traffic, or find
@@ -352,8 +338,8 @@ poorly-behaved workloads that may be harming system health.

 * `apiserver_flowcontrol_rejected_requests_total` is a counter vector
  (cumulative since server start) of requests that were rejected,
-  broken down by the labels `flow_schema` (indicating the one that
-  matched the request), `priority_level` (indicating the one to which
+  broken down by the labels `flowSchema` (indicating the one that
+  matched the request), `priorityLevel` (indicating the one to which
  the request was assigned), and `reason`.  The `reason` label will be
  have one of the following values:
    * `queue-full`, indicating that too many requests were already
@@ -366,8 +352,8 @@ poorly-behaved workloads that may be harming system health.

 * `apiserver_flowcontrol_dispatched_requests_total` is a counter
  vector (cumulative since server start) of requests that began
-  executing, broken down by the labels `flow_schema` (indicating the
-  one that matched the request) and `priority_level` (indicating the
+  executing, broken down by the labels `flowSchema` (indicating the
+  one that matched the request) and `priorityLevel` (indicating the
  one to which the request was assigned).

 * `apiserver_current_inqueue_requests` is a gauge vector of recent
@@ -398,17 +384,17 @@ poorly-behaved workloads that may be harming system health.

 * `apiserver_flowcontrol_current_inqueue_requests` is a gauge vector
  holding the instantaneous number of queued (not executing) requests,
-  broken down by the labels `priority_level` and `flow_schema`.
+  broken down by the labels `priorityLevel` and `flowSchema`.

 * `apiserver_flowcontrol_current_executing_requests` is a gauge vector
  holding the instantaneous number of executing (not waiting in a
-  queue) requests, broken down by the labels `priority_level` and
-  `flow_schema`.
+  queue) requests, broken down by the labels `priorityLevel` and
+  `flowSchema`.

 * `apiserver_flowcontrol_priority_level_request_count_samples` is a
  histogram vector of observations of the then-current number of
  requests broken down by the labels `phase` (which takes on the
-  values `waiting` and `executing`) and `priority_level`.  Each
+  values `waiting` and `executing`) and `priorityLevel`.  Each
  histogram gets observations taken periodically, up through the last
  activity of the relevant sort.  The observations are made at a high
  rate.
@@ -416,7 +402,7 @@ poorly-behaved workloads that may be harming system health.
 * `apiserver_flowcontrol_priority_level_request_count_watermarks` is a
  histogram vector of high or low water marks of the number of
  requests broken down by the labels `phase` (which takes on the
-  values `waiting` and `executing`) and `priority_level`; the label
+  values `waiting` and `executing`) and `priorityLevel`; the label
  `mark` takes on values `high` and `low`.  The water marks are
  accumulated over windows bounded by the times when an observation
  was added to
@@ -425,9 +411,9 @@ poorly-behaved workloads that may be harming system health.

 * `apiserver_flowcontrol_request_queue_length_after_enqueue` is a
  histogram vector of queue lengths for the queues, broken down by
-  the labels `priority_level` and `flow_schema`, as sampled by the
+  the labels `priorityLevel` and `flowSchema`, as sampled by the
  enqueued requests.  Each request that gets queued contributes one
-  sample to its histogram, reporting the length of the queue immediately
+  sample to its histogram, reporting the length of the queue just
  after the request was added.  Note that this produces different
  statistics than an unbiased survey would.
    {{< note >}}
@@ -442,12 +428,12 @@ poorly-behaved workloads that may be harming system health.
 * `apiserver_flowcontrol_request_concurrency_limit` is a gauge vector
  holding the computed concurrency limit (based on the API server's
  total concurrency limit and PriorityLevelConfigurations' concurrency
-  shares), broken down by the label `priority_level`.
+  shares), broken down by the label `priorityLevel`.

 * `apiserver_flowcontrol_request_wait_duration_seconds` is a histogram
  vector of how long requests spent queued, broken down by the labels
-  `flow_schema` (indicating which one matched the request),
-  `priority_level` (indicating the one to which the request was
+  `flowSchema` (indicating which one matched the request),
+  `priorityLevel` (indicating the one to which the request was
  assigned), and `execute` (indicating whether the request started
  executing).
    {{< note >}}
@@ -459,8 +445,8 @@ poorly-behaved workloads that may be harming system health.

 * `apiserver_flowcontrol_request_execution_seconds` is a histogram
  vector of how long requests took to actually execute, broken down by
-  the labels `flow_schema` (indicating which one matched the request)
-  and `priority_level` (indicating the one to which the request was
+  the labels `flowSchema` (indicating which one matched the request)
+  and `priorityLevel` (indicating the one to which the request was
  assigned).

 ### Debug endpoints
@@ -527,5 +513,6 @@ When you enable the API Priority and Fairness feature, the kube-apiserver serves

 For background information on design details for API priority and fairness, see
 the [enhancement proposal](https://github.com/kubernetes/enhancements/blob/master/keps/sig-api-machinery/20190228-priority-and-fairness.md).
-You can make suggestions and feature requests via [SIG API Machinery](https://github.com/kubernetes/community/tree/master/sig-api-machinery) 
-or the feature's [slack channel](http://kubernetes.slack.com/messages/api-priority-and-fairness).
+You can make suggestions and feature requests via [SIG API
+Machinery](https://github.com/kubernetes/community/tree/master/sig-api-machinery).
+
@@ -1,13 +1,13 @@
 ---
 reviewers:
-title: Garbage collection for container images
+title: Configuring kubelet Garbage Collection
 content_type: concept
 weight: 70
 ---

 <!-- overview -->

-Garbage collection is a helpful function of kubelet that will clean up unused [images](/docs/concepts/containers/#container-images) and unused [containers](/docs/concepts/containers/). Kubelet will perform garbage collection for containers every minute and garbage collection for images every five minutes.
+Garbage collection is a helpful function of kubelet that will clean up unused images and unused containers. Kubelet will perform garbage collection for containers every minute and garbage collection for images every five minutes.

 External garbage collection tools are not recommended as these tools can potentially break the behavior of kubelet by removing containers expected to exist.

@@ -37,14 +37,14 @@ Containers that are not managed by kubelet are not subject to container garbage

 ## User Configuration

-You can adjust the following thresholds to tune image garbage collection with the following kubelet flags :
+Users can adjust the following thresholds to tune image garbage collection with the following kubelet flags :

 1. `image-gc-high-threshold`, the percent of disk usage which triggers image garbage collection.
 Default is 85%.
 2. `image-gc-low-threshold`, the percent of disk usage to which image garbage collection attempts
 to free. Default is 80%.

-You can customize the garbage collection policy through the following kubelet flags:
+We also allow users to customize garbage collection policy through the following kubelet flags:

 1. `minimum-container-ttl-duration`, minimum age for a finished container before it is
 garbage collected. Default is 0 minute, which means every finished container will be garbage collected.
@@ -84,3 +84,4 @@ Including:

 See [Configuring Out Of Resource Handling](/docs/tasks/administer-cluster/out-of-resource/) for more details.

+
@@ -9,22 +9,23 @@ weight: 60

 <!-- overview -->

-Application logs can help you understand what is happening inside your application. The logs are particularly useful for debugging problems and monitoring cluster activity. Most modern applications have some kind of logging mechanism. Likewise, container engines are designed to support logging. The easiest and most adopted logging method for containerized applications is writing to standard output and standard error streams.
+Application logs can help you understand what is happening inside your application. The logs are particularly useful for debugging problems and monitoring cluster activity. Most modern applications have some kind of logging mechanism; as such, most container engines are likewise designed to support some kind of logging. The easiest and most embraced logging method for containerized applications is to write to the standard output and standard error streams.

-However, the native functionality provided by a container engine or runtime is usually not enough for a complete logging solution.
-For example, you may want access your application's logs if a container crashes; a pod gets evicted; or a node dies.
-In a cluster, logs should have a separate storage and lifecycle independent of nodes, pods, or containers. This concept is called _cluster-level logging_.
+However, the native functionality provided by a container engine or runtime is usually not enough for a complete logging solution. For example, if a container crashes, a pod is evicted, or a node dies, you'll usually still want to access your application's logs. As such, logs should have a separate storage and lifecycle independent of nodes, pods, or containers. This concept is called _cluster-level-logging_. Cluster-level logging requires a separate backend to store, analyze, and query logs. Kubernetes provides no native storage solution for log data, but you can integrate many existing logging solutions into your Kubernetes cluster.

 <!-- body -->

-Cluster-level logging architectures require a separate backend to store, analyze, and query logs. Kubernetes
-does not provide a native storage solution for log data. Instead, there are many logging solutions that
-integrate with Kubernetes. The following sections describe how to handle and store logs on nodes.
+Cluster-level logging architectures are described in assumption that
+a logging backend is present inside or outside of your cluster. If you're
+not interested in having cluster-level logging, you might still find
+the description of how logs are stored and handled on the node to be useful.

 ## Basic logging in Kubernetes

-This example uses a `Pod` specification with a container
-to write text to the standard output stream once per second.
+In this section, you can see an example of basic logging in Kubernetes that
+outputs data to the standard output stream. This demonstration uses
+a pod specification with a container that writes some text to standard output
+once per second.

 {{< codenew file="debug/counter-pod.yaml" >}}

@@ -33,10 +34,8 @@ To run this pod, use the following command:
 ```shell
 kubectl apply -f https://k8s.io/examples/debug/counter-pod.yaml
 ```
-
 The output is:
-
-```console
+```
 pod/counter created
 ```

@@ -45,73 +44,73 @@ To fetch the logs, use the `kubectl logs` command, as follows:
 ```shell
 kubectl logs counter
 ```
-
 The output is:
-
-```console
+```
 0: Mon Jan  1 00:00:00 UTC 2001
 1: Mon Jan  1 00:00:01 UTC 2001
 2: Mon Jan  1 00:00:02 UTC 2001
 ...
 ```

-You can use `kubectl logs --previous` to retrieve logs from a previous instantiation of a container. If your pod has multiple containers, specify which container's logs you want to access by appending a container name to the command. See the [`kubectl logs` documentation](/docs/reference/generated/kubectl/kubectl-commands#logs) for more details.
+You can use `kubectl logs` to retrieve logs from a previous instantiation of a container with `--previous` flag, in case the container has crashed. If your pod has multiple containers, you should specify which container's logs you want to access by appending a container name to the command. See the [`kubectl logs` documentation](/docs/reference/generated/kubectl/kubectl-commands#logs) for more details.

 ## Logging at the node level

 ![Node level logging](/images/docs/user-guide/logging/logging-node-level.png)

-A container engine handles and redirects any output generated to a containerized application's `stdout` and `stderr` streams.
-For example, the Docker container engine redirects those two streams to [a logging driver](https://docs.docker.com/engine/admin/logging/overview), which is configured in Kubernetes to write to a file in JSON format.
+Everything a containerized application writes to `stdout` and `stderr` is handled and redirected somewhere by a container engine. For example, the Docker container engine redirects those two streams to [a logging driver](https://docs.docker.com/engine/admin/logging/overview), which is configured in Kubernetes to write to a file in json format.

 {{< note >}}
-The Docker JSON logging driver treats each line as a separate message. When using the Docker logging driver, there is no direct support for multi-line messages. You need to handle multi-line messages at the logging agent level or higher.
+The Docker json logging driver treats each line as a separate message. When using the Docker logging driver, there is no direct support for multi-line messages. You need to handle multi-line messages at the logging agent level or higher.
 {{< /note >}}

 By default, if a container restarts, the kubelet keeps one terminated container with its logs. If a pod is evicted from the node, all corresponding containers are also evicted, along with their logs.

 An important consideration in node-level logging is implementing log rotation,
 so that logs don't consume all available storage on the node. Kubernetes
-is not responsible for rotating logs, but rather a deployment tool
+currently is not responsible for rotating logs, but rather a deployment tool
 should set up a solution to address that.
 For example, in Kubernetes clusters, deployed by the `kube-up.sh` script,
 there is a [`logrotate`](https://linux.die.net/man/8/logrotate)
 tool configured to run each hour. You can also set up a container runtime to
-rotate an application's logs automatically.
+rotate application's logs automatically, for example by using Docker's `log-opt`.
+In the `kube-up.sh` script, the latter approach is used for COS image on GCP,
+and the former approach is used in any other environment. In both cases, by
+default rotation is configured to take place when log file exceeds 10MB.

 As an example, you can find detailed information about how `kube-up.sh` sets
 up logging for COS image on GCP in the corresponding
-[`configure-helper` script](https://github.com/kubernetes/kubernetes/blob/{{< param "githubbranch" >}}/cluster/gce/gci/configure-helper.sh).
+[script](https://github.com/kubernetes/kubernetes/blob/{{< param "githubbranch" >}}/cluster/gce/gci/configure-helper.sh).

 When you run [`kubectl logs`](/docs/reference/generated/kubectl/kubectl-commands#logs) as in
 the basic logging example, the kubelet on the node handles the request and
-reads directly from the log file. The kubelet returns the content of the log file.
+reads directly from the log file, returning the contents in the response.

 {{< note >}}
-If an external system has performed the rotation,
+Currently, if some external system has performed the rotation,
 only the contents of the latest log file will be available through
-`kubectl logs`. For example, if there's a 10MB file, `logrotate` performs
-the rotation and there are two files: one file that is 10MB in size and a second file that is empty.
-`kubectl logs` returns the latest log file which in this example is an empty response.
+`kubectl logs`. E.g. if there's a 10MB file, `logrotate` performs
+the rotation and there are two files, one 10MB in size and one empty,
+`kubectl logs` will return an empty response.
 {{< /note >}}

+[cosConfigureHelper]: https://github.com/kubernetes/kubernetes/blob/{{< param "githubbranch" >}}/cluster/gce/gci/configure-helper.sh
 ### System component logs

 There are two types of system components: those that run in a container and those
 that do not run in a container. For example:

 * The Kubernetes scheduler and kube-proxy run in a container.
-* The kubelet and container runtime do not run in containers.
+* The kubelet and container runtime, for example Docker, do not run in containers.

 On machines with systemd, the kubelet and container runtime write to journald. If
-systemd is not present, the kubelet and container runtime write to `.log` files
-in the `/var/log` directory. System components inside containers always write
-to the `/var/log` directory, bypassing the default logging mechanism.
-They use the [`klog`](https://github.com/kubernetes/klog)
+systemd is not present, they write to `.log` files in the `/var/log` directory.
+System components inside containers always write to the `/var/log` directory,
+bypassing the default logging mechanism. They use the [klog](https://github.com/kubernetes/klog)
 logging library. You can find the conventions for logging severity for those
 components in the [development docs on logging](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-instrumentation/logging.md).

-Similar to the container logs, system component logs in the `/var/log`
+Similarly to the container logs, system component logs in the `/var/log`
 directory should be rotated. In Kubernetes clusters brought up by
 the `kube-up.sh` script, those logs are configured to be rotated by
 the `logrotate` tool daily or once the size exceeds 100MB.
@@ -130,14 +129,13 @@ While Kubernetes does not provide a native solution for cluster-level logging, t

 You can implement cluster-level logging by including a _node-level logging agent_ on each node. The logging agent is a dedicated tool that exposes logs or pushes logs to a backend. Commonly, the logging agent is a container that has access to a directory with log files from all of the application containers on that node.

-Because the logging agent must run on every node, it is recommended to run the agent
-as a `DaemonSet`.
+Because the logging agent must run on every node, it's common to implement it as either a DaemonSet replica, a manifest pod, or a dedicated native process on the node. However the latter two approaches are deprecated and highly discouraged.

-Node-level logging creates only one agent per node and doesn't require any changes to the applications running on the node.
+Using a node-level logging agent is the most common and encouraged approach for a Kubernetes cluster, because it creates only one agent per node, and it doesn't require any changes to the applications running on the node. However, node-level logging _only works for applications' standard output and standard error_.

-Containers write stdout and stderr, but with no agreed format. A node-level agent collects these logs and forwards them for aggregation.
+Kubernetes doesn't specify a logging agent, but two optional logging agents are packaged with the Kubernetes release: [Stackdriver Logging](/docs/tasks/debug-application-cluster/logging-stackdriver/) for use with Google Cloud Platform, and [Elasticsearch](/docs/tasks/debug-application-cluster/logging-elasticsearch-kibana/). You can find more information and instructions in the dedicated documents. Both use [fluentd](https://www.fluentd.org/) with custom configuration as an agent on the node.

-### Using a sidecar container with the logging agent {#sidecar-container-with-logging-agent}
+### Using a sidecar container with the logging agent

 You can use a sidecar container in one of the following ways:

@@ -148,27 +146,28 @@ You can use a sidecar container in one of the following ways:

 ![Sidecar container with a streaming container](/images/docs/user-guide/logging/logging-with-streaming-sidecar.png)

-By having your sidecar containers write to their own `stdout` and `stderr`
+By having your sidecar containers stream to their own `stdout` and `stderr`
 streams, you can take advantage of the kubelet and the logging agent that
 already run on each node. The sidecar containers read logs from a file, a socket,
-or journald. Each sidecar container prints a log to its own `stdout` or `stderr` stream.
+or the journald. Each individual sidecar container prints log to its own `stdout`
+or `stderr` stream.

 This approach allows you to separate several log streams from different
 parts of your application, some of which can lack support
 for writing to `stdout` or `stderr`. The logic behind redirecting logs
-is minimal, so it's not a significant overhead. Additionally, because
+is minimal, so it's hardly a significant overhead. Additionally, because
 `stdout` and `stderr` are handled by the kubelet, you can use built-in tools
 like `kubectl logs`.

-For example, a pod runs a single container, and the container
-writes to two different log files using two different formats. Here's a
+Consider the following example. A pod runs a single container, and the container
+writes to two different log files, using two different formats. Here's a
 configuration file for the Pod:

 {{< codenew file="admin/logging/two-files-counter-pod.yaml" >}}

-It is not recommended to write log entries with different formats to the same log
+It would be a mess to have log entries of different formats in the same log
 stream, even if you managed to redirect both components to the `stdout` stream of
-the container. Instead, you can create two sidecar containers. Each sidecar
+the container. Instead, you could introduce two sidecar containers. Each sidecar
 container could tail a particular log file from a shared volume and then redirect
 the logs to its own `stdout` stream.

@@ -182,10 +181,7 @@ running the following commands:
 ```shell
 kubectl logs counter count-log-1
 ```
-
-The output is:
-
-```console
+```
 0: Mon Jan  1 00:00:00 UTC 2001
 1: Mon Jan  1 00:00:01 UTC 2001
 2: Mon Jan  1 00:00:02 UTC 2001
@@ -195,10 +191,7 @@ The output is:
 ```shell
 kubectl logs counter count-log-2
 ```
-
-The output is:
-
-```console
+```
 Mon Jan  1 00:00:00 UTC 2001 INFO 0
 Mon Jan  1 00:00:01 UTC 2001 INFO 1
 Mon Jan  1 00:00:02 UTC 2001 INFO 2
@@ -209,15 +202,16 @@ The node-level agent installed in your cluster picks up those log streams
 automatically without any further configuration. If you like, you can configure
 the agent to parse log lines depending on the source container.

-Note, that despite low CPU and memory usage (order of a couple of millicores
+Note, that despite low CPU and memory usage (order of couple of millicores
 for cpu and order of several megabytes for memory), writing logs to a file and
 then streaming them to `stdout` can double disk usage. If you have
-an application that writes to a single file, it's recommended to set
-`/dev/stdout` as the destination rather than implement the streaming sidecar
+an application that writes to a single file, it's generally better to set
+`/dev/stdout` as destination rather than implementing the streaming sidecar
 container approach.

 Sidecar containers can also be used to rotate log files that cannot be
-rotated by the application itself. An example of this approach is a small container running `logrotate` periodically.
+rotated by the application itself. An example
+of this approach is a small container running logrotate periodically.
 However, it's recommended to use `stdout` and `stderr` directly and leave rotation
 and retention policies to the kubelet.

@@ -232,17 +226,21 @@ configured specifically to run with your application.
 {{< note >}}
 Using a logging agent in a sidecar container can lead
 to significant resource consumption. Moreover, you won't be able to access
-those logs using `kubectl logs` because they are not controlled
+those logs using `kubectl logs` command, because they are not controlled
 by the kubelet.
 {{< /note >}}

-Here are two configuration files that you can use to implement a sidecar container with a logging agent. The first file contains
-a [`ConfigMap`](/docs/tasks/configure-pod-container/configure-pod-configmap/) to configure fluentd.
+As an example, you could use [Stackdriver](/docs/tasks/debug-application-cluster/logging-stackdriver/),
+which uses fluentd as a logging agent. Here are two configuration files that
+you can use to implement this approach. The first file contains
+a [ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/) to configure fluentd.

 {{< codenew file="admin/logging/fluentd-sidecar-config.yaml" >}}

 {{< note >}}
-For information about configuring fluentd, see the [fluentd documentation](https://docs.fluentd.org/).
+The configuration of fluentd is beyond the scope of this article. For
+information about configuring fluentd, see the
+[official fluentd documentation](https://docs.fluentd.org/).
 {{< /note >}}

 The second file describes a pod that has a sidecar container running fluentd.
@@ -250,10 +248,18 @@ The pod mounts a volume where fluentd can pick up its configuration data.

 {{< codenew file="admin/logging/two-files-counter-pod-agent-sidecar.yaml" >}}

-In the sample configurations, you can replace fluentd with any logging agent, reading from any source inside an application container.
+After some time you can find log messages in the Stackdriver interface.
+
+Remember, that this is just an example and you can actually replace fluentd
+with any logging agent, reading from any source inside an application
+container.

 ### Exposing logs directly from the application

 ![Exposing logs directly from the application](/images/docs/user-guide/logging/logging-from-application.png)

-Cluster-logging that exposes or pushes logs directly from every application is outside the scope of Kubernetes.
+You can implement cluster-level logging by exposing or pushing logs directly from
+every application; however, the implementation for such a logging mechanism
+is outside the scope of Kubernetes.
+
+
@@ -45,9 +45,9 @@ kubectl apply -f https://k8s.io/examples/application/nginx/

 `kubectl` will read any files with suffixes `.yaml`, `.yml`, or `.json`.

-It is a recommended practice to put resources related to the same microservice or application tier into the same file, and to group all of the files associated with your application in the same directory. If the tiers of your application bind to each other using DNS, you can deploy all of the components of your stack together.
+It is a recommended practice to put resources related to the same microservice or application tier into the same file, and to group all of the files associated with your application in the same directory. If the tiers of your application bind to each other using DNS, then you can then simply deploy all of the components of your stack en masse.

-A URL can also be specified as a configuration source, which is handy for deploying directly from configuration files checked into GitHub:
+A URL can also be specified as a configuration source, which is handy for deploying directly from configuration files checked into github:

 ```shell
 kubectl apply -f https://raw.githubusercontent.com/kubernetes/website/master/content/en/examples/application/nginx/nginx-deployment.yaml
@@ -70,7 +70,7 @@ deployment.apps "my-nginx" deleted
 service "my-nginx-svc" deleted
 ```

-In the case of two resources, you can specify both resources on the command line using the resource/name syntax:
+In the case of just two resources, it's also easy to specify both on the command line using the resource/name syntax:

 ```shell
 kubectl delete deployments/my-nginx services/my-nginx-svc
@@ -87,11 +87,10 @@ deployment.apps "my-nginx" deleted
 service "my-nginx-svc" deleted
 ```

-Because `kubectl` outputs resource names in the same syntax it accepts, you can chain operations using `$()` or `xargs`:
+Because `kubectl` outputs resource names in the same syntax it accepts, it's easy to chain operations using `$()` or `xargs`:

 ```shell
 kubectl get $(kubectl create -f docs/concepts/cluster-administration/nginx/ -o name | grep service)
-kubectl create -f docs/concepts/cluster-administration/nginx/ -o name | grep service | xargs -i kubectl get {}
 ```

 ```shell
@@ -265,7 +264,7 @@ For a more concrete example, check the [tutorial of deploying Ghost](https://git
 ## Updating labels

 Sometimes existing pods and other resources need to be relabeled before creating new resources. This can be done with `kubectl label`.
-For example, if you want to label all your nginx pods as frontend tier, run:
+For example, if you want to label all your nginx pods as frontend tier, simply run:

 ```shell
 kubectl label pods -l app=nginx tier=fe
@@ -278,7 +277,7 @@ pod/my-nginx-2035384211-u3t6x labeled
 ```

 This first filters all pods with the label "app=nginx", and then labels them with the "tier=fe".
-To see the pods you labeled, run:
+To see the pods you just labeled, run:

 ```shell
 kubectl get pods -l app=nginx -L tier
@@ -302,7 +301,6 @@ Sometimes you would want to attach annotations to resources. Annotations are arb
 kubectl annotate pods my-nginx-v4-9gw19 description='my frontend running nginx'
 kubectl get pods my-nginx-v4-9gw19 -o yaml
 ```
-
 ```shell
 apiVersion: v1
 kind: pod
@@ -316,12 +314,11 @@ For more information, please see [annotations](/docs/concepts/overview/working-w

 ## Scaling your application

-When load on your application grows or shrinks, use `kubectl` to scale your application. For instance, to decrease the number of nginx replicas from 3 to 1, do:
+When load on your application grows or shrinks, it's easy to scale with `kubectl`. For instance, to decrease the number of nginx replicas from 3 to 1, do:

 ```shell
 kubectl scale deployment/my-nginx --replicas=1
 ```
-
 ```shell
 deployment.apps/my-nginx scaled
 ```
@@ -331,7 +328,6 @@ Now you only have one pod managed by the deployment.
 ```shell
 kubectl get pods -l app=nginx
 ```
-
 ```shell
 NAME                        READY     STATUS    RESTARTS   AGE
 my-nginx-2035384211-j5fhi   1/1       Running   0          30m
@@ -342,7 +338,6 @@ To have the system automatically choose the number of nginx replicas as needed,
 ```shell
 kubectl autoscale deployment/my-nginx --min=1 --max=3
 ```
-
 ```shell
 horizontalpodautoscaler.autoscaling/my-nginx autoscaled
 ```
@@ -411,12 +406,11 @@ and

 ## Disruptive updates

-In some cases, you may need to update resource fields that cannot be updated once initialized, or you may want to make a recursive change immediately, such as to fix broken pods created by a Deployment. To change such fields, use `replace --force`, which deletes and re-creates the resource. In this case, you can modify your original configuration file:
+In some cases, you may need to update resource fields that cannot be updated once initialized, or you may just want to make a recursive change immediately, such as to fix broken pods created by a Deployment. To change such fields, use `replace --force`, which deletes and re-creates the resource. In this case, you can simply modify your original configuration file:

 ```shell
 kubectl replace -f https://k8s.io/examples/application/nginx/nginx-deployment.yaml --force
 ```
-
 ```shell
 deployment.apps/my-nginx deleted
 deployment.apps/my-nginx replaced
@@ -433,22 +427,19 @@ Let's say you were running version 1.14.2 of nginx:
 ```shell
 kubectl create deployment my-nginx --image=nginx:1.14.2
 ```
-
 ```shell
 deployment.apps/my-nginx created
 ```

 with 3 replicas (so the old and new revisions can coexist):
-
 ```shell
 kubectl scale deployment my-nginx --current-replicas=1 --replicas=3
 ```
-
 ```
 deployment.apps/my-nginx scaled
 ```

-To update to version 1.16.1, change `.spec.template.spec.containers[0].image` from `nginx:1.14.2` to `nginx:1.16.1` using the previous kubectl commands.
+To update to version 1.16.1, simply change `.spec.template.spec.containers[0].image` from `nginx:1.14.2` to `nginx:1.16.1`, with the kubectl commands we learned above.

 ```shell
 kubectl edit deployment/my-nginx
@@ -114,7 +114,7 @@ Additionally, the CNI can be run alongside [Calico for network policy enforcemen
 ### Azure CNI for Kubernetes
 [Azure CNI](https://docs.microsoft.com/en-us/azure/virtual-network/container-networking-overview) is an [open source](https://github.com/Azure/azure-container-networking/blob/master/docs/cni.md) plugin that integrates Kubernetes Pods with an Azure Virtual Network (also known as VNet) providing network performance at par with VMs. Pods can connect to peered VNet and to on-premises over Express Route or site-to-site VPN and are also directly reachable from these networks. Pods can access Azure services, such as storage and SQL, that are protected by Service Endpoints or Private Link. You can use VNet security policies and routing to filter Pod traffic. The plugin assigns VNet IPs to Pods by utilizing a pool of secondary IPs pre-configured on the Network Interface of a Kubernetes node.

-Azure CNI is available natively in the [Azure Kubernetes Service (AKS)](https://docs.microsoft.com/en-us/azure/aks/configure-azure-cni).
+Azure CNI is available natively in the [Azure Kubernetes Service (AKS)] (https://docs.microsoft.com/en-us/azure/aks/configure-azure-cni).


 ### Big Cloud Fabric from Big Switch Networks
@@ -39,7 +39,7 @@ There are several different proxies you may encounter when using Kubernetes:
    - proxies UDP, TCP and SCTP
    - does not understand HTTP
    - provides load balancing
-    - is only used to reach services
+    - is just used to reach services

 1.  A Proxy/Load-balancer in front of apiserver(s):

@@ -31,24 +31,22 @@ I1025 00:15:15.525108       1 httplog.go:79] GET /api/v1/namespaces/kube-system/

 {{< feature-state for_k8s_version="v1.19" state="alpha" >}}

-{{< warning >}}
+{{<warning>}}
 Migration to structured log messages is an ongoing process. Not all log messages are structured in this version. When parsing log files, you must also handle unstructured log messages.

 Log formatting and value serialization are subject to change.
 {{< /warning>}}

-Structured logging introduces a uniform structure in log messages allowing for programmatic extraction of information. You can store and process structured logs with less effort and cost.
+Structured logging is a effort to introduce a uniform structure in log messages allowing for easy extraction of information, making logs easier and cheaper to store and process.
 New message format is backward compatible and enabled by default.

 Format of structured logs:
-
-```ini
+```
 <klog header> "<message>" <key1>="<value1>" <key2>="<value2>" ...
 ```

 Example:
-
-```ini
+```
 I1025 00:15:15.525108       1 controller_utils.go:116] "Pod status updated" pod="kube-system/kubedns" status="ready"
 ```

@@ -93,27 +91,6 @@ List of components currently supporting JSON format:
 * {{< glossary_tooltip term_id="kube-scheduler" text="kube-scheduler" >}}
 * {{< glossary_tooltip term_id="kubelet" text="kubelet" >}}

-### Log sanitization
-
-{{< feature-state for_k8s_version="v1.20" state="alpha" >}}
-
-{{<warning >}}
-Log sanitization might incur significant computation overhead and therefore should not be enabled in production.
-{{< /warning >}}
-
-The `--experimental-logging-sanitization` flag enables the klog sanitization filter.
-If enabled all log arguments are inspected for fields tagged as sensitive data (e.g. passwords, keys, tokens) and logging of these fields will be prevented.
-
-List of components currently supporting log sanitization:
-* kube-controller-manager
-* kube-apiserver
-* kube-scheduler
-* kubelet
-
-{{< note >}}
-The Log sanitization filter does not prevent user workload logs from leaking sensitive data.
-{{< /note >}}
-
 ### Log verbosity level

 The `-v` flag controls log verbosity. Increasing the value increases the number of logged events. Decreasing the value decreases the number of logged events.
@@ -50,41 +50,39 @@ rules:

 ## Metric lifecycle

-Alpha metric →  Stable metric →  Deprecated metric →  Hidden metric → Deleted metric
+Alpha metric →  Stable metric →  Deprecated metric →  Hidden metric → Deletion

-Alpha metrics have no stability guarantees. These metrics can be modified or deleted at any time.
+Alpha metrics have no stability guarantees; as such they can be modified or deleted at any time.

-Stable metrics are guaranteed to not change. This means:
-* A stable metric without a deprecated signature will not be deleted or renamed
-* A stable metric's type will not be modified
+Stable metrics can be guaranteed to not change; Specifically, stability means:

-Deprecated metrics are slated for deletion, but are still available for use.
-These metrics include an annotation about the version in which they became deprecated.
+* the metric itself will not be deleted (or renamed)
+* the type of metric will not be modified

-For example:
+Deprecated metric signal that the metric will eventually be deleted; to find which version, you need to check annotation, which includes from which kubernetes version that metric will be considered deprecated.

-* Before deprecation
+Before deprecation:

-  ```
-  # HELP some_counter this counts things
-  # TYPE some_counter counter
-  some_counter 0
-  ```
+```
+# HELP some_counter this counts things
+# TYPE some_counter counter
+some_counter 0
+```

-* After deprecation
+After deprecation:

-  ```
-  # HELP some_counter (Deprecated since 1.15.0) this counts things
-  # TYPE some_counter counter
-  some_counter 0
-  ```
+```
+# HELP some_counter (Deprecated since 1.15.0) this counts things
+# TYPE some_counter counter
+some_counter 0
+```

-Hidden metrics are no longer published for scraping, but are still available for use. To use a hidden metric, please refer to the [Show hidden metrics](#show-hidden-metrics) section. 
+Once a metric is hidden then by default the metrics is not published for scraping. To use a hidden metric, you need to override the configuration for the relevant cluster component.

-Deleted metrics are no longer published and cannot be used.
+Once a metric is deleted, the metric is not published. You cannot change this using an override.


-## Show hidden metrics
+## Show Hidden Metrics

 As described above, admins can enable hidden metrics through a command-line flag on a specific binary. This intends to be used as an escape hatch for admins if they missed the migration of the metrics deprecated in the last release.

@@ -131,29 +129,8 @@ cloudprovider_gce_api_request_duration_seconds { request = "detach_disk"}
 cloudprovider_gce_api_request_duration_seconds { request = "list_disk"}
 ```

-
-### kube-scheduler metrics
-
-{{< feature-state for_k8s_version="v1.20" state="alpha" >}}
-
-The scheduler exposes optional metrics that reports the requested resources and the desired limits of all running pods. These metrics can be used to build capacity planning dashboards, assess current or historical scheduling limits, quickly identify workloads that cannot schedule due to lack of resources, and compare actual usage to the pod's request.
-
-The kube-scheduler identifies the resource [requests and limits](/docs/concepts/configuration/manage-resources-containers/) configured for each Pod; when either a request or limit is non-zero, the kube-scheduler reports a metrics timeseries. The time series is labelled by:
- namespace
- pod name
- the node where the pod is scheduled or an empty string if not yet scheduled
- priority
- the assigned scheduler for that pod
- the name of the resource (for example, `cpu`)
- the unit of the resource if known (for example, `cores`)
-
-Once a pod reaches completion (has a `restartPolicy` of `Never` or `OnFailure` and is in the `Succeeded` or `Failed` pod phase, or has been deleted and all containers have a terminated state) the series is no longer reported since the scheduler is now free to schedule other pods to run. The two metrics are called `kube_pod_resource_request` and `kube_pod_resource_limit`.
-
-The metrics are exposed at the HTTP endpoint `/metrics/resources` and require the same authorization as the `/metrics`
-endpoint on the scheduler. You must use the `--show-hidden-metrics-for-version=1.20` flag to expose these alpha stability metrics.
-
-
 ## {{% heading "whatsnext" %}}

 * Read about the [Prometheus text format](https://github.com/prometheus/docs/blob/master/content/docs/instrumenting/exposition_formats.md#text-based-format) for metrics
+* See the list of [stable Kubernetes metrics](https://github.com/kubernetes/kubernetes/blob/master/test/instrumentation/testdata/stable-metrics-list.yaml)
 * Read about the [Kubernetes deprecation policy](/docs/reference/using-api/deprecation-policy/#deprecating-a-feature-or-behavior)
@@ -40,10 +40,10 @@ separate database or file service.
 A ConfigMap is an API [object](/docs/concepts/overview/working-with-objects/kubernetes-objects/)
 that lets you store configuration for other objects to use. Unlike most
 Kubernetes objects that have a `spec`, a ConfigMap has `data` and `binaryData`
-fields. These fields accept key-value pairs as their values.  Both the `data`
+fields. These fields accepts key-value pairs as their values.  Both the `data`
 field and the `binaryData` are optional. The `data` field is designed to
 contain UTF-8 byte sequences while the `binaryData` field is designed to
-contain binary data as base64-encoded strings.
+contain binary data.

 The name of a ConfigMap must be a valid
 [DNS subdomain name](/docs/concepts/overview/working-with-objects/names#dns-subdomain-names).
@@ -225,7 +225,7 @@ The kubelet checks whether the mounted ConfigMap is fresh on every periodic sync
 However, the kubelet uses its local cache for getting the current value of the ConfigMap.
 The type of the cache is configurable using the `ConfigMapAndSecretChangeDetectionStrategy` field in
 the [KubeletConfiguration struct](https://github.com/kubernetes/kubernetes/blob/{{< param "docsbranch" >}}/staging/src/k8s.io/kubelet/config/v1beta1/types.go).
-A ConfigMap can be either propagated by watch (default), ttl-based, or by redirecting
+A ConfigMap can be either propagated by watch (default), ttl-based, or simply redirecting
 all requests directly to the API server.
 As a result, the total delay from the moment when the ConfigMap is updated to the moment
 when new keys are projected to the Pod can be as long as the kubelet sync period + cache
@@ -72,7 +72,8 @@ You cannot overcommit `hugepages-*` resources.
 This is different from the `memory` and `cpu` resources.
 {{< /note >}}

-CPU and memory are collectively referred to as *compute resources*, or *resources*. Compute
+CPU and memory are collectively referred to as *compute resources*, or just
+*resources*. Compute
 resources are measurable quantities that can be requested, allocated, and
 consumed. They are distinct from
 [API resources](/docs/concepts/overview/kubernetes-api/). API resources, such as Pods and
@@ -395,7 +396,7 @@ The kubelet supports different ways to measure Pod storage use:

 {{< tabs name="resource-emphemeralstorage-measurement" >}}
 {{% tab name="Periodic scanning" %}}
-The kubelet performs regular, scheduled checks that scan each
+The kubelet performs regular, schedules checks that scan each
 `emptyDir` volume, container log directory, and writeable container layer.

 The scan measures how much space is used.
@@ -553,7 +554,7 @@ extender.

 ### Consuming extended resources

-Users can consume extended resources in Pod specs like CPU and memory.
+Users can consume extended resources in Pod specs just like CPU and memory.
 The scheduler takes care of the resource accounting so that no more than the
 available amount is simultaneously allocated to Pods.

@@ -599,10 +600,6 @@ spec:
        example.com/foo: 1
 ```

-## PID limiting
-
-Process ID (PID) limits allow for the configuration of a kubelet to limit the number of PIDs that a given Pod can consume. See [Pid Limiting](/docs/concepts/policy/pid-limiting/) for information.
-
 ## Troubleshooting

 ### My Pods are pending with event message failedScheduling
@@ -59,18 +59,16 @@ DNS server watches the Kubernetes API for new `Services` and creates a set of DN

 - Avoid using `hostNetwork`, for the same reasons as `hostPort`.

- Use [headless Services](/docs/concepts/services-networking/service/#headless-services) (which have a `ClusterIP` of `None`) for service discovery when you don't need `kube-proxy` load balancing.
+- Use [headless Services](/docs/concepts/services-networking/service/#headless-services) (which have a `ClusterIP` of `None`) for easy service discovery when you don't need `kube-proxy` load balancing.

 ## Using Labels

 - Define and use [labels](/docs/concepts/overview/working-with-objects/labels/) that identify __semantic attributes__ of your application or Deployment, such as `{ app: myapp, tier: frontend, phase: test, deployment: v3 }`. You can use these labels to select the appropriate Pods for other resources; for example, a Service that selects all `tier: frontend` Pods, or all `phase: test` components of `app: myapp`. See the [guestbook](https://github.com/kubernetes/examples/tree/{{< param "githubbranch" >}}/guestbook/) app for examples of this approach.

-A Service can be made to span multiple Deployments by omitting release-specific labels from its selector. When you need to update a running service without downtime, use a [Deployment](/docs/concepts/workloads/controllers/deployment/).
+A Service can be made to span multiple Deployments by omitting release-specific labels from its selector. [Deployments](/docs/concepts/workloads/controllers/deployment/) make it easy to update a running service without downtime.

 A desired state of an object is described by a Deployment, and if changes to that spec are _applied_, the deployment controller changes the actual state to the desired state at a controlled rate.

- Use the [Kubernetes common labels](/docs/concepts/overview/working-with-objects/common-labels/) for common use cases. These standardized labels enrich the metadata in a way that allows tools, including `kubectl` and [dashboard](/docs/tasks/access-application-cluster/web-ui-dashboard), to work in an interoperable way.
-
 - You can manipulate labels for debugging. Because Kubernetes controllers (such as ReplicaSet) and Services match to Pods using selector labels, removing the relevant labels from a Pod will stop it from being considered by a controller or from being served traffic by a Service. If you remove the labels of an existing Pod, its controller will create a new Pod to take its place. This is a useful way to debug a previously "live" Pod in a "quarantine" environment. To interactively remove or add labels, use [`kubectl label`](/docs/reference/generated/kubectl/kubectl-commands#label).

 ## Container Images
@@ -81,9 +79,9 @@ The [imagePullPolicy](/docs/concepts/containers/images/#updating-images) and the

 - `imagePullPolicy: Always`: every time the kubelet launches a container, the kubelet queries the container image registry to resolve the name to an image digest. If the kubelet has a container image with that exact digest cached locally, the kubelet uses its cached image; otherwise, the kubelet downloads (pulls) the image with the resolved digest, and uses that image to launch the container.

- `imagePullPolicy` is omitted and either the image tag is `:latest` or it is omitted: `imagePullPolicy` is automatically set to `Always`. Note that this will _not_ be updated to `IfNotPresent` if the tag changes value.
+- `imagePullPolicy` is omitted and either the image tag is `:latest` or it is omitted: `Always` is applied.

- `imagePullPolicy` is omitted and the image tag is present but not `:latest`: `imagePullPolicy` is automatically set to `IfNotPresent`. Note that this will _not_ be updated to `Always` if the tag is later removed or changed to `:latest`.
+- `imagePullPolicy` is omitted and the image tag is present but not `:latest`: `IfNotPresent` is applied.

 - `imagePullPolicy: Never`: the image is assumed to exist locally. No attempt is made to pull the image.

@@ -96,7 +94,7 @@ You should avoid using the `:latest` tag when deploying containers in production
 {{< /note >}}

 {{< note >}}
-The caching semantics of the underlying image provider make even `imagePullPolicy: Always` efficient, as long as the registry is reliably accessible. With Docker, for example, if the image already exists, the pull attempt is fast because all image layers are cached and no image download is needed.
+The caching semantics of the underlying image provider make even `imagePullPolicy: Always` efficient. With Docker, for example, if the image already exists, the pull attempt is fast because all image layers are cached and no image download is needed.
 {{< /note >}}

 ## Using kubectl
@@ -24,16 +24,6 @@ a password, a token, or a key. Such information might otherwise be put in a
 Pod specification or in an image. Users can create Secrets and the system
 also creates some Secrets.

-{{< caution >}}
-Kubernetes Secrets are, by default, stored as unencrypted base64-encoded
-strings. By default they can be retrieved - as plain text - by anyone with API
-access, or anyone with access to Kubernetes' underlying data store, etcd. In
-order to safely use Secrets, it is recommended you (at a minimum):
-
-1. [Enable Encryption at Rest](/docs/tasks/administer-cluster/encrypt-data/) for Secrets.
-2. [Enable or configure RBAC rules](/docs/reference/access-authn-authz/authorization/) that restrict reading and writing the Secret. Be aware that secrets can be obtained implicitly by anyone with the permission to create a Pod.
-{{< /caution >}}
-
 <!-- body -->

 ## Overview of Secrets
@@ -109,14 +99,14 @@ empty-secret   Opaque   0      2m6s
 ```

 The `DATA` column shows the number of data items stored in the Secret.
-In this case, `0` means we have created an empty Secret.
+In this case, `0` means we have just created an empty Secret.

 ###  Service account token Secrets

 A `kubernetes.io/service-account-token` type of Secret is used to store a
 token that identifies a service account. When using this Secret type, you need
 to ensure that the `kubernetes.io/service-account.name` annotation is set to an
-existing service account name. A Kubernetes controller fills in some other
+existing service account name. An Kubernetes controller fills in some other
 fields such as the `kubernetes.io/service-account.uid` annotation and the
 `token` key in the `data` field set to actual token content.

@@ -281,16 +271,9 @@ However, using the builtin Secret type helps unify the formats of your credentia
 and the API server does verify if the required keys are provided in a Secret
 configuration.

-{{< caution >}}
-SSH private keys do not establish trusted communication between an SSH client and
-host server on their own. A secondary means of establishing trust is needed to
-mitigate "man in the middle" attacks, such as a `known_hosts` file added to a
-ConfigMap.
-{{< /caution >}}
-
 ### TLS secrets

-Kubernetes provides a builtin Secret type `kubernetes.io/tls` for storing
+Kubernetes provides a builtin Secret type `kubernetes.io/tls` for to storing
 a certificate and its associated key that are typically used for TLS . This
 data is primarily used with TLS termination of the Ingress resource, but may
 be used with other resources or directly by a workload.
@@ -368,7 +351,7 @@ data:

 A bootstrap type Secret has the following keys specified under `data`:

- `token-id`: A random 6 character string as the token identifier. Required.
+- `token_id`: A random 6 character string as the token identifier. Required.
 - `token-secret`: A random 16 character string as the actual token secret. Required.
 - `description`: A human-readable string that describes what the token is
  used for. Optional.
@@ -669,7 +652,7 @@ The kubelet checks whether the mounted secret is fresh on every periodic sync.
 However, the kubelet uses its local cache for getting the current value of the Secret.
 The type of the cache is configurable using the `ConfigMapAndSecretChangeDetectionStrategy` field in
 the [KubeletConfiguration struct](https://github.com/kubernetes/kubernetes/blob/{{< param "docsbranch" >}}/staging/src/k8s.io/kubelet/config/v1beta1/types.go).
-A Secret can be either propagated by watch (default), ttl-based, or by redirecting
+A Secret can be either propagated by watch (default), ttl-based, or simply redirecting
 all requests directly to the API server.
 As a result, the total delay from the moment when the Secret is updated to the moment
 when new keys are projected to the Pod can be as long as the kubelet sync period + cache
@@ -718,7 +701,7 @@ spec:

 #### Consuming Secret Values from environment variables

-Inside a container that consumes a secret in the environment variables, the secret keys appear as
+Inside a container that consumes a secret in an environment variables, the secret keys appear as
 normal environment variables containing the base64 decoded values of the secret data.
 This is the result of commands executed inside the container from the example above:

@@ -742,11 +725,6 @@ The output is similar to:
 1f2d1e2e67df
 ```

-#### Environment variables are not updated after a secret update
-
-If a container already consumes a Secret in an environment variable, a Secret update will not be seen by the container unless it is restarted.
-There are third party solutions for triggering restarts when secrets change.
-
 ## Immutable Secrets {#secret-immutable}

 {{< feature-state for_k8s_version="v1.19" state="beta" >}}
@@ -786,7 +764,7 @@ these pods.
 The `imagePullSecrets` field is a list of references to secrets in the same namespace.
 You can use an `imagePullSecrets` to pass a secret that contains a Docker (or other) image registry
 password to the kubelet. The kubelet uses this information to pull a private image on behalf of your Pod.
-See the [PodSpec API](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#podspec-v1-core) for more information about the `imagePullSecrets` field.
+See the [PodSpec API](/docs/reference/generated/kubernetes-api/{{< latest-version >}}/#podspec-v1-core) for more information about the `imagePullSecrets` field.

 #### Manually specifying an imagePullSecret

@@ -801,6 +779,12 @@ field set to that of the service account.
 See [Add ImagePullSecrets to a service account](/docs/tasks/configure-pod-container/configure-service-account/#add-imagepullsecrets-to-a-service-account)
 for a detailed explanation of that process.

+### Automatic mounting of manually created Secrets
+
+Manually created secrets (for example, one containing a token for accessing a GitHub account)
+can be automatically attached to pods based on their service account.
+See [Injecting Information into Pods Using a PodPreset](/docs/tasks/inject-data-application/podpreset/) for a detailed explanation of that process.
+
 ## Details

 ### Restrictions
@@ -40,7 +40,6 @@ as are any environment variables specified statically in the Docker image.
 ### Cluster information

 A list of all services that were running when a Container was created is available to that Container as environment variables.
-This list is limited to services within the same namespace as the new Container's Pod and Kubernetes control plane services.
 Those environment variables match the syntax of Docker links.

 For a service named *foo* that maps to a Container named *bar*,
@@ -36,13 +36,10 @@ No parameters are passed to the handler.

 `PreStop`

-This hook is called immediately before a container is terminated due to an API request or management
-event such as a liveness/startup probe failure, preemption, resource contention and others. A call
-to the `PreStop` hook fails if the container is already in a terminated or completed state and the
-hook must complete before the TERM signal to stop the container can be sent. The Pod's termination
-grace period countdown begins before the `PreStop` hook is executed, so regardless of the outcome of
-the handler, the container will eventually terminate within the Pod's termination grace period. No
-parameters are passed to the handler.
+This hook is called immediately before a container is terminated due to an API request or management event such as liveness probe failure, preemption, resource contention and others. A call to the preStop hook fails if the container is already in terminated or completed state.
+It is blocking, meaning it is synchronous,
+so it must complete before the signal to stop the container can be sent.
+No parameters are passed to the handler.

 A more detailed description of the termination behavior can be found in
 [Termination of Pods](/docs/concepts/workloads/pods/pod-lifecycle/#pod-termination).
@@ -60,7 +57,7 @@ Resources consumed by the command are counted against the Container.

 When a Container lifecycle management hook is called,
 the Kubernetes management system execute the handler according to the hook action,
-`httpGet` and `tcpSocket` are executed by the kubelet process, and `exec` is executed in the container.
+`exec` and `tcpSocket` are executed in the container, and `httpGet` is executed by the kubelet process.

 Hook handler calls are synchronous within the context of the Pod containing the Container.
 This means that for a `PostStart` hook,
@@ -68,15 +65,19 @@ the Container ENTRYPOINT and hook fire asynchronously.
 However, if the hook takes too long to run or hangs,
 the Container cannot reach a `running` state.

-`PreStop` hooks are not executed asynchronously from the signal to stop the Container; the hook must
-complete its execution before the TERM signal can be sent. If a `PreStop` hook hangs during
-execution, the Pod's phase will be `Terminating` and remain there until the Pod is killed after its
-`terminationGracePeriodSeconds` expires. This grace period applies to the total time it takes for
-both the `PreStop` hook to execute and for the Container to stop normally. If, for example,
-`terminationGracePeriodSeconds` is 60, and the hook takes 55 seconds to complete, and the Container
-takes 10 seconds to stop normally after receiving the signal, then the Container will be killed
-before it can stop normally, since `terminationGracePeriodSeconds` is less than the total time
-(55+10) it takes for these two things to happen.
+`PreStop` hooks are not executed asynchronously from the signal
+to stop the Container; the hook must complete its execution before
+the signal can be sent.
+If a `PreStop` hook hangs during execution,
+the Pod's phase will be `Terminating` and remain there until the Pod is
+killed after its `terminationGracePeriodSeconds` expires.
+This grace period applies to the total time it takes for both
+the `PreStop` hook to execute and for the Container to stop normally.
+If, for example, `terminationGracePeriodSeconds` is 60, and the hook
+takes 55 seconds to complete, and the Container takes 10 seconds to stop
+normally after receiving the signal, then the Container will be killed
+before it can stop normally, since `terminationGracePeriodSeconds` is
+less than the total time (55+10) it takes for these two things to happen.

 If either a `PostStart` or `PreStop` hook fails,
 it kills the Container.
@@ -49,32 +49,16 @@ Instead, specify a meaningful tag such as `v1.42.0`.

 ## Updating images

-When you first create a {{< glossary_tooltip text="Deployment" term_id="deployment" >}},
-{{< glossary_tooltip text="StatefulSet" term_id="statefulset" >}}, Pod, or other
-object that includes a Pod template, then by default the pull policy of all
-containers in that pod will be set to `IfNotPresent` if it is not explicitly
-specified. This policy causes the
-{{< glossary_tooltip text="kubelet" term_id="kubelet" >}} to skip pulling an
-image if it already exists.
-
-If you would like to always force a pull, you can do one of the following:
+The default pull policy is `IfNotPresent` which causes the
+{{< glossary_tooltip text="kubelet" term_id="kubelet" >}} to skip
+pulling an image if it already exists. If you would like to always force a pull,
+you can do one of the following:

 - set the `imagePullPolicy` of the container to `Always`.
- omit the `imagePullPolicy` and use `:latest` as the tag for the image to use;
-  Kubernetes will set the policy to `Always`.
+- omit the `imagePullPolicy` and use `:latest` as the tag for the image to use.
 - omit the `imagePullPolicy` and the tag for the image to use.
 - enable the [AlwaysPullImages](/docs/reference/access-authn-authz/admission-controllers/#alwayspullimages) admission controller.

-{{< note >}}
-The value of `imagePullPolicy` of the container is always set when the object is
-first _created_, and is not updated if the image's tag later changes.
-
-For example, if you create a Deployment with an image whose tag is _not_
-`:latest`, and later update that Deployment's image to a `:latest` tag, the
-`imagePullPolicy` field will _not_ change to `Always`. You must manually change
-the pull policy of any object after its initial creation.
-{{< /note >}}
-
 When `imagePullPolicy` is defined without a specific value, it is also set to `Always`.

 ## Multi-architecture images with image indexes
@@ -135,7 +119,7 @@ Here are the recommended steps to configuring your nodes to use a private regist
 example, run these on your desktop/laptop:

   1. Run `docker login [server]` for each set of credentials you want to use.  This updates `$HOME/.docker/config.json` on your PC.
-   1. View `$HOME/.docker/config.json` in an editor to ensure it contains only the credentials you want to use.
+   1. View `$HOME/.docker/config.json` in an editor to ensure it contains just the credentials you want to use.
   1. Get a list of your nodes; for example:
      - if you want the names: `nodes=$( kubectl get nodes -o jsonpath='{range.items[*].metadata}{.name} {end}' )`
      - if you want to get the IP addresses: `nodes=$( kubectl get nodes -o jsonpath='{range .items[*].status.addresses[?(@.type=="ExternalIP")]}{.address} {end}' )`
@@ -9,7 +9,7 @@ weight: 20

 <!-- overview -->

-{{< feature-state for_k8s_version="v1.20" state="stable" >}}
+{{< feature-state for_k8s_version="v1.14" state="beta" >}}

 This page describes the RuntimeClass resource and runtime selection mechanism.

@@ -35,6 +35,10 @@ but with different settings.

 ## Setup

+Ensure the RuntimeClass feature gate is enabled (it is by default). See [Feature
+Gates](/docs/reference/command-line-tools-reference/feature-gates/) for an explanation of enabling
+feature gates. The `RuntimeClass` feature gate must be enabled on apiservers _and_ kubelets.
+
 1. Configure the CRI implementation on nodes (runtime dependent)
 2. Create the corresponding RuntimeClass resources

@@ -47,7 +51,7 @@ CRI implementation for how to configure.
 {{< note >}}
 RuntimeClass assumes a homogeneous node configuration across the cluster by default (which means
 that all nodes are configured the same way with respect to container runtimes). To support
-heterogeneous node configurations, see [Scheduling](#scheduling) below.
+heterogenous node configurations, see [Scheduling](#scheduling) below.
 {{< /note >}}

 The configurations have a corresponding `handler` name, referenced by the RuntimeClass. The
@@ -62,7 +66,7 @@ The RuntimeClass resource currently only has 2 significant fields: the RuntimeCl
 (`metadata.name`) and the handler (`handler`). The object definition looks like this:

 ```yaml
-apiVersion: node.k8s.io/v1  # RuntimeClass is defined in the node.k8s.io API group
+apiVersion: node.k8s.io/v1beta1  # RuntimeClass is defined in the node.k8s.io API group
 kind: RuntimeClass
 metadata:
  name: myclass  # The name the RuntimeClass will be referenced by
@@ -94,7 +98,7 @@ spec:
  # ...
 ```

-This will instruct the kubelet to use the named RuntimeClass to run this pod. If the named
+This will instruct the Kubelet to use the named RuntimeClass to run this pod. If the named
 RuntimeClass does not exist, or the CRI cannot run the corresponding handler, the pod will enter the
 `Failed` terminal [phase](/docs/concepts/workloads/pods/pod-lifecycle/#pod-phase). Look for a
 corresponding [event](/docs/tasks/debug-application-cluster/debug-application-introspection/) for an
@@ -140,9 +144,11 @@ See CRI-O's [config documentation](https://raw.githubusercontent.com/cri-o/cri-o

 {{< feature-state for_k8s_version="v1.16" state="beta" >}}

-By specifying the `scheduling` field for a RuntimeClass, you can set constraints to
-ensure that Pods running with this RuntimeClass are scheduled to nodes that support it.
-If `scheduling` is not set, this RuntimeClass is assumed to be supported by all nodes.
+As of Kubernetes v1.16, RuntimeClass includes support for heterogenous clusters through its
+`scheduling` fields. Through the use of these fields, you can ensure that pods running with this
+RuntimeClass are scheduled to nodes that support it. To use the scheduling support, you must have
+the [RuntimeClass admission controller](/docs/reference/access-authn-authz/admission-controllers/#runtimeclass)
+enabled (the default, as of 1.16).

 To ensure pods land on nodes supporting a specific RuntimeClass, that set of nodes should have a
 common label which is then selected by the `runtimeclass.scheduling.nodeSelector` field. The
@@ -179,3 +185,5 @@ are accounted for in Kubernetes.
 - [RuntimeClass Scheduling Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/585-runtime-class/README.md#runtimeclass-scheduling)
 - Read about the [Pod Overhead](/docs/concepts/scheduling-eviction/pod-overhead/) concept
 - [PodOverhead Feature Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/20190226-pod-overhead.md)
+
+
@@ -145,7 +145,7 @@ Kubernetes provides several built-in authentication methods, and an [Authenticat

 ### Authorization

-[Authorization](/docs/reference/access-authn-authz/webhook/) determines whether specific users can read, write, and do other operations on API resources. It works at the level of whole resources -- it doesn't discriminate based on arbitrary object fields. If the built-in authorization options don't meet your needs, and [Authorization webhook](/docs/reference/access-authn-authz/webhook/) allows calling out to user-provided code to make an authorization decision.
+[Authorization](/docs/reference/access-authn-authz/webhook/) determines whether specific users can read, write, and do other operations on API resources. It just works at the level of whole resources -- it doesn't discriminate based on arbitrary object fields. If the built-in authorization options don't meet your needs, and [Authorization webhook](/docs/reference/access-authn-authz/webhook/) allows calling out to user-provided code to make an authorization decision.


 ### Dynamic Admission Control
@@ -28,7 +28,9 @@ The most common way to implement the APIService is to run an *extension API serv
 Extension API servers should have low latency networking to and from the kube-apiserver.
 Discovery requests are required to round-trip from the kube-apiserver in five seconds or less.

-If your extension API server cannot achieve that latency requirement, consider making changes that let you meet it.
+If your extension API server cannot achieve that latency requirement, consider making changes that let you meet it. You can also set the
+`EnableAggregatedDiscoveryTimeout=false` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) on the kube-apiserver
+to disable the timeout restriction. This deprecated feature gate will be removed in a future release.

 ## {{% heading "whatsnext" %}}

@@ -31,7 +31,7 @@ Once a custom resource is installed, users can create and access its objects usi

 ## Custom controllers

-On their own, custom resources let you store and retrieve structured data.
+On their own, custom resources simply let you store and retrieve structured data.
 When you combine a custom resource with a *custom controller*, custom resources
 provide a true _declarative API_.

@@ -120,7 +120,7 @@ Kubernetes provides two ways to add custom resources to your cluster:

 Kubernetes provides these two options to meet the needs of different users, so that neither ease of use nor flexibility is compromised.

-Aggregated APIs are subordinate API servers that sit behind the primary API server, which acts as a proxy. This arrangement is called [API Aggregation](/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/) (AA). To users, the Kubernetes API appears extended.
+Aggregated APIs are subordinate API servers that sit behind the primary API server, which acts as a proxy. This arrangement is called [API Aggregation](/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/) (AA). To users, it simply appears that the Kubernetes API is extended.

 CRDs allow users to create new types of resources without adding another API server. You do not need to understand API Aggregation to use CRDs.

@@ -201,11 +201,10 @@ Monitoring agents for device plugin resources can be deployed as a daemon, or as
 The canonical directory `/var/lib/kubelet/pod-resources` requires privileged access, so monitoring
 agents must run in a privileged security context.  If a device monitoring agent is running as a
 DaemonSet, `/var/lib/kubelet/pod-resources` must be mounted as a
-{{< glossary_tooltip term_id="volume" >}} in the device monitoring agent's
+{{< glossary_tooltip term_id="volume" >}} in the plugin's
 [PodSpec](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#podspec-v1-core).

-Support for the "PodResources service" requires `KubeletPodResources` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) to be enabled.
-It is enabled by default starting with Kubernetes 1.15 and is v1 since Kubernetes 1.20.
+Support for the "PodResources service" requires `KubeletPodResources` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) to be enabled. It is enabled by default starting with Kubernetes 1.15.

 ## Device Plugin integration with the Topology Manager

@@ -24,7 +24,7 @@ Network plugins in Kubernetes come in a few flavors:
 The kubelet has a single default network plugin, and a default network common to the entire cluster. It probes for plugins when it starts up, remembers what it finds, and executes the selected plugin at appropriate times in the pod lifecycle (this is only true for Docker, as CRI manages its own CNI plugins). There are two Kubelet command line parameters to keep in mind when using plugins:

 * `cni-bin-dir`: Kubelet probes this directory for plugins on startup
-* `network-plugin`: The network plugin to use from `cni-bin-dir`.  It must match the name reported by a plugin probed from the plugin directory.  For CNI plugins, this is `cni`.
+* `network-plugin`: The network plugin to use from `cni-bin-dir`.  It must match the name reported by a plugin probed from the plugin directory.  For CNI plugins, this is simply "cni".

 ## Network Plugin Requirements

@@ -159,7 +159,7 @@ This option is provided to the network-plugin; currently **only kubenet supports
 ## Usage Summary

 * `--network-plugin=cni` specifies that we use the `cni` network plugin with actual CNI plugin binaries located in `--cni-bin-dir` (default `/opt/cni/bin`) and CNI plugin configuration located in `--cni-conf-dir` (default `/etc/cni/net.d`).
-* `--network-plugin=kubenet` specifies that we use the `kubenet` network plugin with CNI `bridge`, `lo` and `host-local` plugins placed in `/opt/cni/bin` or `cni-bin-dir`.
+* `--network-plugin=kubenet` specifies that we use the `kubenet` network plugin with CNI `bridge` and `host-local` plugins placed in `/opt/cni/bin` or `cni-bin-dir`.
 * `--network-plugin-mtu=9001` specifies the MTU to use, currently only used by the `kubenet` network plugin.

 ## {{% heading "whatsnext" %}}
@@ -74,7 +74,7 @@ failure.
 In the webhook model, Kubernetes makes a network request to a remote service.
 In the *Binary Plugin* model, Kubernetes executes a binary (program).
 Binary plugins are used by the kubelet (e.g.
-[Flex Volume Plugins](/docs/concepts/storage/volumes/#flexvolume)
+[Flex Volume Plugins](/docs/concepts/storage/volumes/#flexVolume)
 and [Network Plugins](/docs/concepts/extend-kubernetes/compute-storage-net/network-plugins/))
 and by kubectl.

@@ -146,7 +146,7 @@ Kubernetes provides several built-in authentication methods, and an [Authenticat

 ### Authorization

-[Authorization](/docs/reference/access-authn-authz/webhook/) determines whether specific users can read, write, and do other operations on API resources. It works at the level of whole resources -- it doesn't discriminate based on arbitrary object fields. If the built-in authorization options don't meet your needs, and [Authorization webhook](/docs/reference/access-authn-authz/webhook/) allows calling out to user-provided code to make an authorization decision.
+[Authorization](/docs/reference/access-authn-authz/webhook/) determines whether specific users can read, write, and do other operations on API resources. It just works at the level of whole resources -- it doesn't discriminate based on arbitrary object fields. If the built-in authorization options don't meet your needs, and [Authorization webhook](/docs/reference/access-authn-authz/webhook/) allows calling out to user-provided code to make an authorization decision.


 ### Dynamic Admission Control
@@ -161,7 +161,7 @@ After a request is authorized, if it is a write operation, it also goes through

 ### Storage Plugins

-[Flex Volumes](/docs/concepts/storage/volumes/#flexvolume)
+[Flex Volumes](/docs/concepts/storage/volumes/#flexVolume)
 allow users to mount volume types without built-in support by having the
 Kubelet call a Binary Plugin to mount the volume.

@@ -103,28 +103,27 @@ as well as keeping the existing service in good shape.
 ## Writing your own Operator {#writing-operator}

 If there isn't an Operator in the ecosystem that implements the behavior you
-want, you can code your own. 
+want, you can code your own. In [What's next](#whats-next) you'll find a few
+links to libraries and tools you can use to write your own cloud native
+Operator.

 You also implement an Operator (that is, a Controller) using any language / runtime
 that can act as a [client for the Kubernetes API](/docs/reference/using-api/client-libraries/).

-Following are a few libraries and tools you can use to write your own cloud native
-Operator.

-{{% thirdparty-content %}}
-
-* [kubebuilder](https://book.kubebuilder.io/)
-* [KUDO](https://kudo.dev/) (Kubernetes Universal Declarative Operator)
-* [Metacontroller](https://metacontroller.app/) along with WebHooks that
-  you implement yourself
-* [Operator Framework](https://operatorframework.io)

 ## {{% heading "whatsnext" %}}


 * Learn more about [Custom Resources](/docs/concepts/extend-kubernetes/api-extension/custom-resources/)
 * Find ready-made operators on [OperatorHub.io](https://operatorhub.io/) to suit your use case
+* Use existing tools to write your own operator, eg:
+  * using [KUDO](https://kudo.dev/) (Kubernetes Universal Declarative Operator)
+  * using [kubebuilder](https://book.kubebuilder.io/)
+  * using [Metacontroller](https://metacontroller.app/) along with WebHooks that
+    you implement yourself
+  * using the [Operator Framework](https://operatorframework.io)
 * [Publish](https://operatorhub.io/) your operator for other people to use
-* Read [CoreOS' original article](https://web.archive.org/web/20170129131616/https://coreos.com/blog/introducing-operators.html) that introduced the Operator pattern (this is an archived version of the original article).
+* Read [CoreOS' original article](https://coreos.com/blog/introducing-operators.html) that introduced the Operator pattern
 * Read an [article](https://cloud.google.com/blog/products/containers-kubernetes/best-practices-for-building-kubernetes-operators-and-stateful-apps) from Google Cloud about best practices for building Operators

@@ -26,7 +26,7 @@ Fortunately, there is a cloud provider that offers message queuing as a managed

 A cluster operator can setup Service Catalog and use it to communicate with the cloud provider's service broker to provision an instance of the message queuing service and make it available to the application within the Kubernetes cluster.
 The application developer therefore does not need to be concerned with the implementation details or management of the message queue.
-The application can access the message queue as a service.
+The application can simply use it as a service.

 ## Architecture

@@ -51,11 +51,11 @@ the same machine, and do not run user containers on this machine. See

 {{< glossary_definition term_id="kube-controller-manager" length="all" >}}

-Some types of these controllers are:
+These controllers include:

  * Node controller: Responsible for noticing and responding when nodes go down.
-  * Job controller: Watches for Job objects that represent one-off tasks, then creates
-    Pods to run those tasks to completion.
+  * Replication controller: Responsible for maintaining the correct number of pods for every replication
+  controller object in the system.
  * Endpoints controller: Populates the Endpoints object (that is, joins Services & Pods).
  * Service Account & Token controllers: Create default accounts and API access tokens for new namespaces.

@@ -19,7 +19,7 @@ is the {{< glossary_tooltip text="API server" term_id="kube-apiserver" >}}. The
 exposes an HTTP API that lets end users, different parts of your cluster, and
 external components communicate with one another.

-The Kubernetes API lets you query and manipulate the state of API objects in Kubernetes
+The Kubernetes API lets you query and manipulate the state of objects in the Kubernetes API
 (for example: Pods, Namespaces, ConfigMaps, and Events).

 Most operations can be performed through the
@@ -43,7 +43,7 @@ Each VM is a full machine running all the components, including its own operatin
 Containers have become popular because they provide extra benefits, such as:

 * Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use.
-* Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and efficient rollbacks (due to image immutability).
+* Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and easy rollbacks (due to image immutability).
 * Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
 * Observability not only surfaces OS-level information and metrics, but also application health and other signals.
 * Environmental consistency across development, testing, and production: Runs the same on a laptop as it does in the cloud.
@@ -59,8 +59,8 @@ metadata:
 ## Applications And Instances Of Applications

 An application can be installed one or more times into a Kubernetes cluster and,
-in some cases, the same namespace. For example, WordPress can be installed more
-than once where different websites are different installations of WordPress.
+in some cases, the same namespace. For example, wordpress can be installed more
+than once where different websites are different installations of wordpress.

 The name of an application and the instance name are recorded separately. For
 example, WordPress has a `app.kubernetes.io/name` of `wordpress` while it has
@@ -168,6 +168,6 @@ metadata:
 ...
 ```

-With the MySQL `StatefulSet` and `Service` you'll notice information about both MySQL and WordPress, the broader application, are included.
+With the MySQL `StatefulSet` and `Service` you'll notice information about both MySQL and Wordpress, the broader application, are included.


@@ -42,7 +42,7 @@ Example labels:
   * `"partition" : "customerA"`, `"partition" : "customerB"`
   * `"track" : "daily"`, `"track" : "weekly"`

-These are examples of commonly used labels; you are free to develop your own conventions. Keep in mind that label Key must be unique for a given object.
+These are just examples of commonly used labels; you are free to develop your own conventions. Keep in mind that label Key must be unique for a given object.

 ## Syntax and character set

@@ -52,10 +52,7 @@ If the prefix is omitted, the label Key is presumed to be private to the user. A

 The `kubernetes.io/` and `k8s.io/` prefixes are reserved for Kubernetes core components.

-Valid label value:
-* must be 63 characters or less (cannot be empty),
-* must begin and end with an alphanumeric character (`[a-z0-9A-Z]`),
-* could contain dashes (`-`), underscores (`_`), dots (`.`), and alphanumerics between.
+Valid label values must be 63 characters or less and must be empty or begin and end with an alphanumeric character (`[a-z0-9A-Z]`) with dashes (`-`), underscores (`_`), dots (`.`), and alphanumerics between.

 For example, here's the configuration file for a Pod that has two labels `environment: production` and `app: nginx` :

@@ -101,7 +98,7 @@ For both equality-based and set-based conditions there is no logical _OR_ (`||`)
 ### _Equality-based_ requirement

 _Equality-_ or _inequality-based_ requirements allow filtering by label keys and values. Matching objects must satisfy all of the specified label constraints, though they may have additional labels as well.
-Three kinds of operators are admitted `=`,`==`,`!=`. The first two represent _equality_ (and are synonyms), while the latter represents _inequality_. For example:
+Three kinds of operators are admitted `=`,`==`,`!=`. The first two represent _equality_ (and are simply synonyms), while the latter represents _inequality_. For example:

 ```
 environment = production
@@ -28,7 +28,7 @@ resource can only be in one namespace.

 Namespaces are a way to divide cluster resources between multiple users (via [resource quota](/docs/concepts/policy/resource-quotas/)).

-It is not necessary to use multiple namespaces to separate slightly different
+It is not necessary to use multiple namespaces just to separate slightly different
 resources, such as different versions of the same software: use
 [labels](/docs/concepts/overview/working-with-objects/labels) to distinguish
 resources within the same namespace.
@@ -91,7 +91,7 @@ kubectl config view --minify | grep namespace:
 When you create a [Service](/docs/concepts/services-networking/service/),
 it creates a corresponding [DNS entry](/docs/concepts/services-networking/dns-pod-service/).
 This entry is of the form `<service-name>.<namespace-name>.svc.cluster.local`, which means
-that if a container only uses `<service-name>`, it will resolve to the service which
+that if a container just uses `<service-name>`, it will resolve to the service which
 is local to a namespace.  This is useful for using the same configuration across
 multiple namespaces such as Development, Staging and Production.  If you want to reach
 across namespaces, you need to use the fully qualified domain name (FQDN).
@@ -31,7 +31,7 @@ When using imperative commands, a user operates directly on live objects
 in a cluster. The user provides operations to
 the `kubectl` command as arguments or flags.

-This is the recommended way to get started or to run a one-off task in
+This is the simplest way to get started or to run a one-off task in
 a cluster. Because this technique operates directly on live
 objects, it provides no history of previous configurations.

@@ -47,7 +47,7 @@ kubectl create deployment nginx --image nginx

 Advantages compared to object configuration:

- Commands are expressed as a single action word.
+- Commands are simple, easy to learn and easy to remember.
 - Commands require only a single step to make changes to the cluster.

 Disadvantages compared to object configuration:
@@ -1,117 +0,0 @@
---
-reviewers:
- derekwaynecarr
-title: Process ID Limits And Reservations
-content_type: concept
-weight: 40
---
-
-<!-- overview -->
-
-{{< feature-state for_k8s_version="v1.20" state="stable" >}}
-
-Kubernetes allow you to limit the number of process IDs (PIDs) that a {{< glossary_tooltip term_id="Pod" text="Pod" >}} can use.
-You can also reserve a number of allocatable PIDs for each {{< glossary_tooltip term_id="node" text="node" >}}
-for use by the operating system and daemons (rather than by Pods).
-
-<!-- body -->
-
-Process IDs (PIDs) are a fundamental resource on nodes. It is trivial to hit the
-task limit without hitting any other resource limits, which can then cause
-instability to a host machine.
-
-Cluster administrators require mechanisms to ensure that Pods running in the
-cluster cannot induce PID exhaustion that prevents host daemons (such as the
-{{< glossary_tooltip text="kubelet" term_id="kubelet" >}} or
-{{< glossary_tooltip text="kube-proxy" term_id="kube-proxy" >}},
-and potentially also the container runtime) from running.
-In addition, it is important to ensure that PIDs are limited among Pods in order
-to ensure they have limited impact on other workloads on the same node.
-
-{{< note >}}
-On certain Linux installations, the operating system sets the PIDs limit to a low default,
-such as `32768`. Consider raising the value of `/proc/sys/kernel/pid_max`.
-{{< /note >}}
-
-You can configure a kubelet to limit the number of PIDs a given Pod can consume.
-For example, if your node's host OS is set to use a maximum of `262144` PIDs and
-expect to host less than `250` Pods, one can give each Pod a budget of `1000`
-PIDs to prevent using up that node's overall number of available PIDs. If the
-admin wants to overcommit PIDs similar to CPU or memory, they may do so as well
-with some additional risks. Either way, a single Pod will not be able to bring
-the whole machine down. This kind of resource limiting helps to prevent simple
-fork bombs from affecting operation of an entire cluster.
-
-Per-Pod PID limiting allows administrators to protect one Pod from another, but
-does not ensure that all Pods scheduled onto that host are unable to impact the node overall.
-Per-Pod limiting also does not protect the node agents themselves from PID exhaustion.
-
-You can also reserve an amount of PIDs for node overhead, separate from the
-allocation to Pods. This is similar to how you can reserve CPU, memory, or other
-resources for use by the operating system and other facilities outside of Pods
-and their containers.
-
-PID limiting is a an important sibling to [compute
-resource](/docs/concepts/configuration/manage-resources-containers/) requests
-and limits. However, you specify it in a different way: rather than defining a
-Pod's resource limit in the `.spec` for a Pod, you configure the limit as a
-setting on the kubelet. Pod-defined PID limits are not currently supported.
-
-{{< caution >}}
-This means that the limit that applies to a Pod may be different depending on
-where the Pod is scheduled. To make things simple, it's easiest if all Nodes use
-the same PID resource limits and reservations.
-{{< /caution >}}
-
-## Node PID limits
-
-Kubernetes allows you to reserve a number of process IDs for the system use. To
-configure the reservation, use the parameter `pid=<number>` in the
-`--system-reserved` and `--kube-reserved` command line options to the kubelet.
-The value you specified declares that the specified number of process IDs will
-be reserved for the system as a whole and for Kubernetes system daemons
-respectively.
-
-{{< note >}}
-Before Kubernetes version 1.20, PID resource limiting with Node-level
-reservations required enabling the [feature
-gate](/docs/reference/command-line-tools-reference/feature-gates/)
-`SupportNodePidsLimit` to work.
-{{< /note >}}
-
-## Pod PID limits
-
-Kubernetes allows you to limit the number of processes running in a Pod. You
-specify this limit at the node level, rather than configuring it as a resource
-limit for a particular Pod. Each Node can have a different PID limit.  
-To configure the limit, you can specify the command line parameter `--pod-max-pids` to the kubelet, or set `PodPidsLimit` in the kubelet [configuration file](/docs/tasks/administer-cluster/kubelet-config-file/).
-
-{{< note >}}
-Before Kubernetes version 1.20, PID resource limiting for Pods required enabling
-the [feature gate](/docs/reference/command-line-tools-reference/feature-gates/)
-`SupportPodPidsLimit` to work.
-{{< /note >}}
-
-## PID based eviction
-
-You can configure kubelet to start terminating a Pod when it is misbehaving and consuming abnormal amount of resources.
-This feature is called eviction. You can [Configure Out of Resource Handling](/docs/tasks/administer-cluster/out-of-resource) for various eviction signals.
-Use `pid.available` eviction signal to configure the threshold for number of PIDs used by Pod.
-You can set soft and hard eviction policies. However, even with the hard eviction policy, if the number of PIDs growing very fast,
-node can still get into unstable state by hitting the node PIDs limit.
-Eviction signal value is calculated periodically and does NOT enforce the limit.
-
-PID limiting - per Pod and per Node sets the hard limit.
-Once the limit is hit, workload will start experiencing failures when trying to get a new PID.
-It may or may not lead to rescheduling of a Pod,
-depending on how workload reacts on these failures and how liveleness and readiness
-probes are configured for the Pod. However, if limits were set correctly,
-you can guarantee that other Pods workload and system processes will not run out of PIDs
-when one Pod is misbehaving.
-
-## {{% heading "whatsnext" %}}
-
- Refer to the [PID Limiting enhancement document](https://github.com/kubernetes/enhancements/blob/097b4d8276bc9564e56adf72505d43ce9bc5e9e8/keps/sig-node/20190129-pid-limiting.md) for more information.
- For historical context, read [Process ID Limiting for Stability Improvements in Kubernetes 1.14](/blog/2019/04/15/process-id-limiting-for-stability-improvements-in-kubernetes-1.14/).
- Read [Managing Resources for Containers](/docs/concepts/configuration/manage-resources-containers/).
- Learn how to [Configure Out of Resource Handling](/docs/tasks/administer-cluster/out-of-resource).
@@ -4,7 +4,7 @@ reviewers:
 - tallclair
 title: Pod Security Policies
 content_type: concept
-weight: 30
+weight: 20
 ---

 <!-- overview -->
@@ -197,7 +197,7 @@ alias kubectl-user='kubectl --as=system:serviceaccount:psp-example:fake-user -n
 ### Create a policy and a pod

 Define the example PodSecurityPolicy object in a file. This is a policy that
-prevents the creation of privileged pods.
+simply prevents the creation of privileged pods.
 The name of a PodSecurityPolicy object must be a valid
 [DNS subdomain name](/docs/concepts/overview/working-with-objects/names#dns-subdomain-names).

@@ -216,17 +216,12 @@ kubectl-user create -f- <<EOF
 apiVersion: v1
 kind: Pod
 metadata:
-  name: pause
+  name:      pause
 spec:
  containers:
-    - name: pause
+    - name:  pause
      image: k8s.gcr.io/pause
 EOF
-```
-
-The output is similar to this:
-
-```
 Error from server (Forbidden): error when creating "STDIN": pods "pause" is forbidden: unable to validate against any pod security policy: []
 ```

@@ -269,17 +264,12 @@ kubectl-user create -f- <<EOF
 apiVersion: v1
 kind: Pod
 metadata:
-  name: pause
+  name:      pause
 spec:
  containers:
-    - name: pause
+    - name:  pause
      image: k8s.gcr.io/pause
 EOF
-```
-
-The output is similar to this
-
-```
 pod "pause" created
 ```

@@ -291,19 +281,14 @@ kubectl-user create -f- <<EOF
 apiVersion: v1
 kind: Pod
 metadata:
-  name: privileged
+  name:      privileged
 spec:
  containers:
-    - name: pause
+    - name:  pause
      image: k8s.gcr.io/pause
      securityContext:
        privileged: true
 EOF
-```
-
-The output is similar to this:
-
-```
 Error from server (Forbidden): error when creating "STDIN": pods "privileged" is forbidden: unable to validate against any pod security policy: [spec.containers[0].securityContext.privileged: Invalid value: true: Privileged containers are not allowed]
 ```

@@ -3,7 +3,7 @@ reviewers:
 - derekwaynecarr
 title: Resource Quotas
 content_type: concept
-weight: 20
+weight: 10
 ---

 <!-- overview -->
@@ -58,7 +58,7 @@ Neither contention nor changes to quota will affect already created resources.
 ## Enabling Resource Quota

 Resource Quota support is enabled by default for many Kubernetes distributions.  It is
-enabled when the {{< glossary_tooltip text="API server" term_id="kube-apiserver" >}} `--enable-admission-plugins=` flag has `ResourceQuota` as
+enabled when the API server `--enable-admission-plugins=` flag has `ResourceQuota` as
 one of its arguments.

 A resource quota is enforced in a particular namespace when there is a
@@ -610,28 +610,17 @@ plugins:
        values: ["cluster-services"]
 ```

-Then, create a resource quota object in the `kube-system` namespace:
+Now, "cluster-services" pods will be allowed in only those namespaces where a quota object with a matching `scopeSelector` is present.
+For example:

-{{< codenew file="policy/priority-class-resourcequota.yaml" >}}
-
-```shell
-$ kubectl apply -f https://k8s.io/examples/policy/priority-class-resourcequota.yaml -n kube-system
+```yaml
+    scopeSelector:
+      matchExpressions:
+      - scopeName: PriorityClass
+        operator: In
+        values: ["cluster-services"]
 ```

-```
-resourcequota/pods-cluster-services created
-```
-
-In this case, a pod creation will be allowed if:
-
-1.  the Pod's `priorityClassName` is not specified.
-1.  the Pod's `priorityClassName` is specified to a value other than `cluster-services`.
-1.  the Pod's `priorityClassName` is set to `cluster-services`, it is to be created
-   in the `kube-system` namespace, and it has passed the resource quota check.
-
-A Pod creation request is rejected if its `priorityClassName` is set to `cluster-services`
-and it is to be created in a namespace other than `kube-system`.
-
 ## {{% heading "whatsnext" %}}

 - See [ResourceQuota design doc](https://git.k8s.io/community/contributors/design-proposals/resource-management/admission_control_resource_quota.md) for more information.
@@ -5,7 +5,7 @@ reviewers:
 - bsalamat
 title: Assigning Pods to Nodes
 content_type: concept
-weight: 20
+weight: 50
 ---


@@ -120,12 +120,12 @@ pod is eligible to be scheduled on, based on labels on the node.

 There are currently two types of node affinity, called `requiredDuringSchedulingIgnoredDuringExecution` and
 `preferredDuringSchedulingIgnoredDuringExecution`. You can think of them as "hard" and "soft" respectively,
-in the sense that the former specifies rules that *must* be met for a pod to be scheduled onto a node (similar to
+in the sense that the former specifies rules that *must* be met for a pod to be scheduled onto a node (just like
 `nodeSelector` but using a more expressive syntax), while the latter specifies *preferences* that the scheduler
 will try to enforce but will not guarantee. The "IgnoredDuringExecution" part of the names means that, similar
 to how `nodeSelector` works, if labels on a node change at runtime such that the affinity rules on a pod are no longer
-met, the pod continues to run on the node. In the future we plan to offer
-`requiredDuringSchedulingRequiredDuringExecution` which will be identical to `requiredDuringSchedulingIgnoredDuringExecution`
+met, the pod will still continue to run on the node. In the future we plan to offer
+`requiredDuringSchedulingRequiredDuringExecution` which will be just like `requiredDuringSchedulingIgnoredDuringExecution`
 except that it will evict pods from nodes that cease to satisfy the pods' node affinity requirements.

 Thus an example of `requiredDuringSchedulingIgnoredDuringExecution` would be "only run the pod on nodes with Intel CPUs"
@@ -158,49 +158,6 @@ If you remove or change the label of the node where the pod is scheduled, the po

 The `weight` field in `preferredDuringSchedulingIgnoredDuringExecution` is in the range 1-100. For each node that meets all of the scheduling requirements (resource request, RequiredDuringScheduling affinity expressions, etc.), the scheduler will compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node matches the corresponding MatchExpressions. This score is then combined with the scores of other priority functions for the node. The node(s) with the highest total score are the most preferred.

-#### Node affinity per scheduling profile
-
-{{< feature-state for_k8s_version="v1.20" state="beta" >}}
-
-When configuring multiple [scheduling profiles](/docs/reference/scheduling/config/#multiple-profiles), you can associate
-a profile with a Node affinity, which is useful if a profile only applies to a specific set of Nodes.
-To do so, add an `addedAffinity` to the args of the [`NodeAffinity` plugin](/docs/reference/scheduling/config/#scheduling-plugins)
-in the [scheduler configuration](/docs/reference/scheduling/config/). For example:
-
-```yaml
-apiVersion: kubescheduler.config.k8s.io/v1beta1
-kind: KubeSchedulerConfiguration
-
-profiles:
-  - schedulerName: default-scheduler
-  - schedulerName: foo-scheduler
-    pluginConfig:
-      - name: NodeAffinity
-        args:
-          addedAffinity:
-            requiredDuringSchedulingIgnoredDuringExecution:
-              nodeSelectorTerms:
-              - matchExpressions:
-                - key: scheduler-profile
-                  operator: In
-                  values:
-                  - foo
-```
-
-The `addedAffinity` is applied to all Pods that set `.spec.schedulerName` to `foo-scheduler`, in addition to the
-NodeAffinity specified in the PodSpec.
-That is, in order to match the Pod, Nodes need to satisfy `addedAffinity` and the Pod's `.spec.NodeAffinity`.
-
-Since the `addedAffinity` is not visible to end users, its behavior might be unexpected to them. We
-recommend to use node labels that have clear correlation with the profile's scheduler name.
-
-{{< note >}}
-The DaemonSet controller, which [creates Pods for DaemonSets](/docs/concepts/workloads/controllers/daemonset/#scheduled-by-default-scheduler)
-is not aware of scheduling profiles. For this reason, it is recommended that you keep a scheduler profile, such as the
-`default-scheduler`, without any `addedAffinity`. Then, the Daemonset's Pod template should use this scheduler name.
-Otherwise, some Pods created by the Daemonset controller might remain unschedulable.
-{{< /note >}}
-
 ### Inter-pod affinity and anti-affinity

 Inter-pod affinity and anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled *based on
@@ -246,7 +203,7 @@ as at least one already-running pod that has a label with key "security" and val
 on node N if node N has a label with key `topology.kubernetes.io/zone` and some value V
 such that there is at least one node in the cluster with key `topology.kubernetes.io/zone` and
 value V that is running a pod that has a label with key "security" and value "S1".) The pod anti-affinity
-rule says that the pod should not be scheduled onto a node if that node is in the same zone as a pod with
+rule says that the pod cannot be scheduled onto a node if that node is in the same zone as a pod with
 label having key "security" and value "S2". See the
 [design doc](https://git.k8s.io/community/contributors/design-proposals/scheduling/podaffinity.md)
 for many more examples of pod affinity and anti-affinity, both the `requiredDuringSchedulingIgnoredDuringExecution`
@@ -261,7 +218,7 @@ for performance and security reasons, there are some constraints on topologyKey:
 and `preferredDuringSchedulingIgnoredDuringExecution`.
 2. For pod anti-affinity, empty `topologyKey` is also not allowed in both `requiredDuringSchedulingIgnoredDuringExecution`
 and `preferredDuringSchedulingIgnoredDuringExecution`.
-3. For `requiredDuringSchedulingIgnoredDuringExecution` pod anti-affinity, the admission controller `LimitPodHardAntiAffinityTopology` was introduced to limit `topologyKey` to `kubernetes.io/hostname`. If you want to make it available for custom topologies, you may modify the admission controller, or disable it.
+3. For `requiredDuringSchedulingIgnoredDuringExecution` pod anti-affinity, the admission controller `LimitPodHardAntiAffinityTopology` was introduced to limit `topologyKey` to `kubernetes.io/hostname`. If you want to make it available for custom topologies, you may modify the admission controller, or simply disable it.
 4. Except for the above cases, the `topologyKey` can be any legal label-key.

 In addition to `labelSelector` and `topologyKey`, you can optionally specify a list `namespaces`
@@ -30,7 +30,7 @@ time according to the overhead associated with the Pod's
 [RuntimeClass](/docs/concepts/containers/runtime-class/).

 When Pod Overhead is enabled, the overhead is considered in addition to the sum of container
-resource requests when scheduling a Pod. Similarly, the kubelet will include the Pod overhead when sizing
+resource requests when scheduling a Pod. Similarly, Kubelet will include the Pod overhead when sizing
 the Pod cgroup, and when carrying out Pod eviction ranking.

 ## Enabling Pod Overhead {#set-up}
@@ -48,7 +48,7 @@ that uses around 120MiB per Pod for the virtual machine and the guest OS:
 ```yaml
 ---
 kind: RuntimeClass
-apiVersion: node.k8s.io/v1
+apiVersion: node.k8s.io/v1beta1
 metadata:
    name: kata-fc
 handler: kata-fc
@@ -194,4 +194,4 @@ from source in the meantime.


 * [RuntimeClass](/docs/concepts/containers/runtime-class/)
-* [PodOverhead Design](https://github.com/kubernetes/enhancements/tree/master/keps/sig-node/688-pod-overhead)
+* [PodOverhead Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/20190226-pod-overhead.md)
@@ -5,7 +5,7 @@ reviewers:
 - ahg-g
 title: Resource Bin Packing for Extended Resources
 content_type: concept
-weight: 30
+weight: 50
 ---

 <!-- overview -->
@@ -82,7 +82,7 @@ requested the score value must be reversed as follows.
 ```yaml
 shape:
  - utilization: 0
-    score: 10
+    score: 100
  - utilization: 100
    score: 0
 ```
@@ -107,7 +107,7 @@ value being calculated based on the cluster size. There is also a hardcoded
 minimum value of 50 nodes.

 {{< note >}}In clusters with less than 50 feasible nodes, the scheduler still
-checks all the nodes because there are not enough feasible nodes to stop
+checks all the nodes, simply because there are not enough feasible nodes to stop
 the scheduler's search early.

 In a small cluster, if you set a low value for `percentageOfNodesToScore`, your
@@ -10,9 +10,11 @@ weight: 70

 {{< feature-state for_k8s_version="v1.15" state="alpha" >}}

-The scheduling framework is a pluggable architecture for the Kubernetes scheduler.
-It adds a new set of "plugin" APIs to the existing scheduler. Plugins are compiled into the scheduler. The APIs allow most scheduling features to be implemented as plugins, while keeping the
-scheduling "core" lightweight and maintainable. Refer to the [design proposal of the
+The scheduling framework is a pluggable architecture for Kubernetes Scheduler
+that makes scheduler customizations easy. It adds a new set of "plugin" APIs to
+the existing scheduler. Plugins are compiled into the scheduler. The APIs
+allow most scheduling features to be implemented as plugins, while keeping the
+scheduling "core" simple and maintainable. Refer to the [design proposal of the
 scheduling framework][kep] for more technical information on the design of the
 framework.

@@ -183,7 +185,7 @@ the three things:

 {{< note >}}
 While any plugin can access the list of "waiting" Pods and approve them
-(see [`FrameworkHandle`](https://git.k8s.io/enhancements/keps/sig-scheduling/624-scheduling-framework#frameworkhandle)), we expect only the permit
+(see [`FrameworkHandle`](https://github.com/kubernetes/enhancements/blob/master/keps/sig-scheduling/20180409-scheduling-framework.md#frameworkhandle)), we expect only the permit
 plugins to approve binding of reserved Pods that are in "waiting" state. Once a Pod
 is approved, it is sent to the [PreBind](#pre-bind) phase.
 {{< /note >}}
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Kubernetes Prow Robot	ec96e13d39	Merge pull request #25598 from pjhwa/outdated2-25522 Update outdated kubernetes-api.md file in the dev-1.19-ko.7	2020-12-14 21:47:48 -08:00
Jerry Park	fd448ac4fe	Update outdated kubernetes-api.md file in the dev-1.19-ko.7	2020-12-14 07:23:12 +00:00
Kubernetes Prow Robot	5cd83e36b4	Merge pull request #25529 from pjhwa/outdated-25522 Update outdated files in the dev-1.19-ko.7 branch	2020-12-13 16:45:27 -08:00
Jerry Park	09708662cc	Update outdated files in the dev-1.19-ko.7 branch	2020-12-14 06:46:21 +09:00
Kubernetes Prow Robot	958c5bd7b8	Merge pull request #25467 from annajung/release-1.19-config-change Update 1.19 config.toml for release 1.20	2020-12-08 14:19:33 -08:00
Anna	5309821c8e	Merge pull request #25465 from annajung/release-1.19 Merge master into release-1.19 to keep in sync	2020-12-07 14:01:15 -06:00
Anna Jung (VMware)	bb6b39db54	Update config.toml for release 1.20 Signed-off-by: Anna Jung (VMware) <antheaj@vmware.com>	2020-12-07 10:57:14 -06:00