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Merge branch 'master' into remove_kubectl_run_command_deprecated_en

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2020-06-12 15:58:02 +08:00
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content/en/_index.html
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abstract: "Automated container deployment, scaling, and management"
cid: home
---
{{< announcement >}}
{{< deprecationwarning >}}
{{< blocks/section id="oceanNodes" >}}
{{% blocks/feature image="flower" %}}
@@ -60,4 +57,4 @@ Kubernetes is open source giving you the freedom to take advantage of on-premise
{{< blocks/kubernetes-features >}}
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content/en/blog/_posts/2017-01-00-Running-Mongodb-On-Kubernetes-With-Statefulsets.md
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slug: running-mongodb-on-kubernetes-with-statefulsets
url: /blog/2017/01/Running-Mongodb-On-Kubernetes-With-Statefulsets
---
_Editor's note: Today’s post is by Sandeep Dinesh, Developer Advocate, Google Cloud Platform, showing how to run a database in a container._
_Editor's note: Today’s post is by Sandeep Dinesh, Developer Advocate, Google Cloud Platform, showing how to run a database in a container._
{{% warning %}}
This post is several years old. The code examples need changes to work on a current Kubernetes cluster.
{{% /warning %}}
Conventional wisdom says you can’t run a database in a container. “Containers are stateless!” they say, and “databases are pointless without state!”
Conventional wisdom says you can’t run a database in a container. “Containers are stateless!” they say, and “databases are pointless without state!”
Of course, this is not true at all. At Google, everything runs in a container, including databases. You just need the right tools. [Kubernetes 1.5](https://kubernetes.io/blog/2016/12/kubernetes-1-5-supporting-production-workloads/) includes the new [StatefulSet](/docs/concepts/abstractions/controllers/statefulsets/) API object (in previous versions, StatefulSet was known as PetSet). With StatefulSets, Kubernetes makes it much easier to run stateful workloads such as databases.
If you’ve followed my previous posts, you know how to create a [MEAN Stack app with Docker](http://blog.sandeepdinesh.com/2015/07/running-mean-web-application-in-docker.html), then [migrate it to Kubernetes](https://medium.com/google-cloud/running-a-mean-stack-on-google-cloud-platform-with-kubernetes-149ca81c2b5d) to provide easier management and reliability, and [create a MongoDB replica set](https://medium.com/google-cloud/mongodb-replica-sets-with-kubernetes-d96606bd9474) to provide redundancy and high availability.
If you’ve followed my previous posts, you know how to create a [MEAN Stack app with Docker](http://blog.sandeepdinesh.com/2015/07/running-mean-web-application-in-docker.html), then [migrate it to Kubernetes](https://medium.com/google-cloud/running-a-mean-stack-on-google-cloud-platform-with-kubernetes-149ca81c2b5d) to provide easier management and reliability, and [create a MongoDB replica set](https://medium.com/google-cloud/mongodb-replica-sets-with-kubernetes-d96606bd9474) to provide redundancy and high availability.
While the replica set in my previous blog post worked, there were some annoying steps that you needed to follow. You had to manually create a disk, a ReplicationController, and a service for each replica. Scaling the set up and down meant managing all of these resources manually, which is an opportunity for error, and would put your stateful application at risk In the previous example, we created a Makefile to ease the management of these resources, but it would have been great if Kubernetes could just take care of all of this for us.
With StatefulSets, these headaches finally go away. You can create and manage your MongoDB replica set natively in Kubernetes, without the need for scripts and Makefiles. Let’s take a look how.
_Note: StatefulSets are currently a beta resource. The [sidecar container](https://github.com/cvallance/mongo-k8s-sidecar) used for auto-configuration is also unsupported._
While the replica set in my previous blog post worked, there were some annoying steps that you needed to follow. You had to manually create a disk, a ReplicationController, and a service for each replica. Scaling the set up and down meant managing all of these resources manually, which is an opportunity for error, and would put your stateful application at risk In the previous example, we created a Makefile to ease the management of these resources, but it would have been great if Kubernetes could just take care of all of this for us.
With StatefulSets, these headaches finally go away. You can create and manage your MongoDB replica set natively in Kubernetes, without the need for scripts and Makefiles. Let’s take a look how.
_Note: StatefulSets are currently a beta resource. The [sidecar container](https://github.com/cvallance/mongo-k8s-sidecar) used for auto-configuration is also unsupported._
**Prerequisites and Setup**
Before we get started, you’ll need a Kubernetes 1.5+ and the [Kubernetes command line tool](/docs/user-guide/prereqs/). If you want to follow along with this tutorial and use Google Cloud Platform, you also need the [Google Cloud SDK](http://cloud.google.com/sdk).
Once you have a [Google Cloud project created](https://console.cloud.google.com/projectcreate) and have your Google Cloud SDK setup (hint: gcloud init), we can create our cluster.
To create a Kubernetes 1.5 cluster, run the following command:
To create a Kubernetes 1.5 cluster, run the following command:
```
gcloud container clusters create "test-cluster"
```
This will make a three node Kubernetes cluster. Feel free to [customize the command](https://cloud.google.com/sdk/gcloud/reference/container/clusters/create) as you see fit.
This will make a three node Kubernetes cluster. Feel free to [customize the command](https://cloud.google.com/sdk/gcloud/reference/container/clusters/create) as you see fit.
Then, authenticate into the cluster:
```
gcloud container clusters get-credentials test-cluster
```
**Setting up the MongoDB replica set**
To set up the MongoDB replica set, you need three things: A [StorageClass](/docs/user-guide/persistent-volumes/#storageclasses), a [Headless Service](/docs/user-guide/services/#headless-services), and a [StatefulSet](/docs/concepts/abstractions/controllers/statefulsets/).
I’ve created the configuration files for these already, and you can clone the example from GitHub:
I’ve created the configuration files for these already, and you can clone the example from GitHub:
```
git clone https://github.com/thesandlord/mongo-k8s-sidecar.git
@@ -75,10 +54,7 @@ git clone https://github.com/thesandlord/mongo-k8s-sidecar.git
cd /mongo-k8s-sidecar/example/StatefulSet/
```
To create the MongoDB replica set, run these two commands:
To create the MongoDB replica set, run these two commands:
```
kubectl apply -f googlecloud\_ssd.yaml
@@ -86,341 +62,202 @@ kubectl apply -f googlecloud\_ssd.yaml
kubectl apply -f mongo-statefulset.yaml
```
That's it! With these two commands, you have launched all the components required to run an highly available and redundant MongoDB replica set.
At an high level, it looks something like this:
![](https://lh4.googleusercontent.com/ohALxLD4Ugj5FCwWqgqZ4xP9al4lTgrPDc9HsgPWYRZRz_buuYK6LKSC7A5n98DdOO-Po3Zq77Yt43-QhTWdIaXqltHI7PX0zMXAXbpiilYgdowGZapG0lJ9lgubwBj1CwNHHtXA)
Let’s examine each piece in more detail.
**StorageClass**
The storage class tells Kubernetes what kind of storage to use for the database nodes. You can set up many different types of StorageClasses in a ton of different environments. For example, if you run Kubernetes in your own datacenter, you can use [GlusterFS](https://www.gluster.org/). On GCP, your [storage choices](https://cloud.google.com/compute/docs/disks/) are SSDs and hard disks. There are currently drivers for [AWS](/docs/user-guide/persistent-volumes/#aws), [Azure](/docs/user-guide/persistent-volumes/#azure-disk), [Google Cloud](/docs/user-guide/persistent-volumes/#gce), [GlusterFS](/docs/user-guide/persistent-volumes/#glusterfs), [OpenStack Cinder](/docs/user-guide/persistent-volumes/#openstack-cinder), [vSphere](/docs/user-guide/persistent-volumes/#vsphere), [Ceph RBD](/docs/user-guide/persistent-volumes/#ceph-rbd), and [Quobyte](/docs/user-guide/persistent-volumes/#quobyte).
The configuration for the StorageClass looks like this:
The configuration for the StorageClass looks like this:
```
kind: StorageClass
apiVersion: storage.k8s.io/v1beta1
metadata:
name: fast
provisioner: kubernetes.io/gce-pd
parameters:
```yaml
kind: StorageClass
apiVersion: storage.k8s.io/v1beta1
metadata:
name: fast
provisioner: kubernetes.io/gce-pd
parameters:
type: pd-ssd
```
This configuration creates a new StorageClass called “fast” that is backed by SSD volumes. The StatefulSet can now request a volume, and the StorageClass will automatically create it!
Deploy this StorageClass:
Deploy this StorageClass:
```
kubectl apply -f googlecloud\_ssd.yaml
```
**Headless Service**
Now you have created the Storage Class, you need to make a Headless Service. These are just like normal Kubernetes Services, except they don’t do any load balancing for you. When combined with StatefulSets, they can give you unique DNS addresses that let you directly access the pods! This is perfect for creating MongoDB replica sets, because our app needs to connect to all of the MongoDB nodes individually.
The configuration for the Headless Service looks like this:
The configuration for the Headless Service looks like this:
```
```yaml
apiVersion: v1
kind: Service
metadata:
name: mongo
labels:
name: mongo
name: mongo
labels:
name: mongo
spec:
ports:
- port: 27017
targetPort: 27017
clusterIP: None
selector:
role: mongo
ports:
- port: 27017
targetPort: 27017
clusterIP: None
selector:
role: mongo
```
You can tell this is a Headless Service because the clusterIP is set to “None.” Other than that, it looks exactly the same as any normal Kubernetes Service.
**StatefulSet**
The pièce de résistance. The StatefulSet actually runs MongoDB and orchestrates everything together. StatefulSets differ from Kubernetes [ReplicaSets](/docs/user-guide/replicasets/) (not to be confused with MongoDB replica sets!) in certain ways that makes them more suited for stateful applications. Unlike Kubernetes ReplicaSets, pods created under a StatefulSet have a few unique attributes. The name of the pod is not random, instead each pod gets an ordinal name. Combined with the Headless Service, this allows pods to have stable identification. In addition, pods are created one at a time instead of all at once, which can help when bootstrapping a stateful system. You can read more about StatefulSets in the [documentation](/docs/concepts/abstractions/controllers/statefulsets/).
Just like before, [this “sidecar” container](https://github.com/cvallance/mongo-k8s-sidecar) will configure the MongoDB replica set automatically. A “sidecar” is a helper container which helps the main container do its work.
The configuration for the StatefulSet looks like this:
The configuration for the StatefulSet looks like this:
```
```yaml
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
name: mongo
name: mongo
spec:
serviceName: "mongo"
replicas: 3
template:
metadata:
labels:
role: mongo
environment: test
spec:
terminationGracePeriodSeconds: 10
containers:
- name: mongo
image: mongo
command:
- mongod
- "--replSet"
- rs0
- "--smallfiles"
- "--noprealloc"
ports:
- containerPort: 27017
volumeMounts:
- name: mongo-persistent-storage
mountPath: /data/db
- name: mongo-sidecar
image: cvallance/mongo-k8s-sidecar
env:
- name: MONGO\_SIDECAR\_POD\_LABELS
value: "role=mongo,environment=test"
volumeClaimTemplates:
- metadata:
name: mongo-persistent-storage
annotations:
volume.beta.kubernetes.io/storage-class: "fast"
spec:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 100Gi
selector:
matchLabels:
role: mongo
environment: test
serviceName: "mongo"
replicas: 3
template:
metadata:
labels:
role: mongo
environment: test
spec:
terminationGracePeriodSeconds: 10
containers:
- name: mongo
image: mongo
command:
- mongod
- "--replSet"
- rs0
- "--smallfiles"
- "--noprealloc"
ports:
- containerPort: 27017
volumeMounts:
- name: mongo-persistent-storage
mountPath: /data/db
- name: mongo-sidecar
image: cvallance/mongo-k8s-sidecar
env:
- name: MONGO_SIDECAR_POD_LABELS
value: "role=mongo,environment=test"
volumeClaimTemplates:
- metadata:
name: mongo-persistent-storage
spec:
storageClassName: "fast"
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 100Gi
```
It’s a little long, but fairly straightforward.
The first second describes the StatefulSet object. Then, we move into the Metadata section, where you can specify labels and the number of replicas.
Next comes the pod spec. The terminationGracePeriodSeconds is used to gracefully shutdown the pod when you scale down the number of replicas, which is important for databases! Then the configurations for the two containers is shown. The first one runs MongoDB with command line flags that configure the replica set name. It also mounts the persistent storage volume to /data/db, the location where MongoDB saves its data. The second container runs the sidecar.
Next comes the pod spec. The terminationGracePeriodSeconds is used to gracefully shutdown the pod when you scale down the number of replicas, which is important for databases! Then the configurations for the two containers is shown. The first one runs MongoDB with command line flags that configure the replica set name. It also mounts the persistent storage volume to /data/db, the location where MongoDB saves its data. The second container runs the sidecar.
Finally, there is the volumeClaimTemplates. This is what talks to the StorageClass we created before to provision the volume. It will provision a 100 GB disk for each MongoDB replica.
Finally, there is the volumeClaimTemplates. This is what talks to the StorageClass we created before to provision the volume. It will provision a 100 GB disk for each MongoDB replica.
**Using the MongoDB replica set**
At this point, you should have three pods created in your cluster. These correspond to the three nodes in your MongoDB replica set. You can see them with this command:
At this point, you should have three pods created in your cluster. These correspond to the three nodes in your MongoDB replica set. You can see them with this command:
```
kubectl get pods
NAME READY STATUS RESTARTS AGE
mongo-0 2/2 Running 0 3m
mongo-1 2/2 Running 0 3m
mongo-2 2/2 Running 0 3m
```
Each pod in a StatefulSet backed by a Headless Service will have a stable DNS name. The template follows this format: \<pod-name\>.\<service-name\>
Each pod in a StatefulSet backed by a Headless Service will have a stable DNS name. The template follows this format: \<pod-name\>.\<service-name\>
This means the DNS names for the MongoDB replica set are:
This means the DNS names for the MongoDB replica set are:
```
mongo-0.mongo
mongo-1.mongo
mongo-2.mongo
```
You can use these names directly in the [connection string URI](http://docs.mongodb.com/manual/reference/connection-string) of your app.
You can use these names directly in the [connection string URI](http://docs.mongodb.com/manual/reference/connection-string) of your app.
In this case, the connection string URI would be:
In this case, the connection string URI would be:
```
“mongodb://mongo-0.mongo,mongo-1.mongo,mongo-2.mongo:27017/dbname\_?”
mongodb://mongo-0.mongo,mongo-1.mongo,mongo-2.mongo:27017/dbname\_?
```
That’s it!
That’s it!
**Scaling the MongoDB replica set**
A huge advantage of StatefulSets is that you can scale them just like Kubernetes ReplicaSets. If you want 5 MongoDB Nodes instead of 3, just run the scale command:
**Scaling the MongoDB replica set**
A huge advantage of StatefulSets is that you can scale them just like Kubernetes ReplicaSets. If you want 5 MongoDB Nodes instead of 3, just run the scale command:
```
kubectl scale --replicas=5 statefulset mongo
```
The sidecar container will automatically configure the new MongoDB nodes to join the replica set.
The sidecar container will automatically configure the new MongoDB nodes to join the replica set.
Include the two new nodes (mongo-3.mongo & mongo-4.mongo) in your connection string URI and you are good to go. Too easy!
Include the two new nodes (mongo-3.mongo & mongo-4.mongo) in your connection string URI and you are good to go. Too easy!
**Cleaning Up**
**Cleaning Up**
To clean up the deployed resources, delete the StatefulSet, Headless Service, and the provisioned volumes.
Delete the StatefulSet:
To clean up the deployed resources, delete the StatefulSet, Headless Service, and the provisioned volumes.
Delete the StatefulSet:
```
kubectl delete statefulset mongo
```
Delete the Service:
Delete the Service:
```
kubectl delete svc mongo
```
Delete the Volumes:
Delete the Volumes:
```
kubectl delete pvc -l role=mongo
```
Finally, you can delete the test cluster:
Finally, you can delete the test cluster:
```
gcloud container clusters delete "test-cluster"
```
Happy Hacking!
For more cool Kubernetes and Container blog posts, follow me on [Twitter](https://twitter.com/sandeepdinesh) and [Medium](https://medium.com/@SandeepDinesh).
_--Sandeep Dinesh, Developer Advocate, Google Cloud Platform._
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---
layout: blog
title: Supporting the Evolving Ingress Specification in Kubernetes 1.18
date: 2020-06-05
slug: Supporting-the-Evolving-Ingress-Specification-in-Kubernetes-1.18
---
**Authors:** Alex Gervais (Datawire.io)
Earlier this year, the Kubernetes team released [Kubernetes 1.18](https://kubernetes.io/blog/2020/03/25/kubernetes-1-18-release-announcement/), which extended Ingress. In this blog post, we’ll walk through what’s new in the new Ingress specification, what it means for your applications, and how to upgrade to an ingress controller that supports this new specification.
### What is Kubernetes Ingress
When deploying your applications in Kubernetes, one of the first challenges many people encounter is how to get traffic into their cluster. [Kubernetes ingress](https://kubernetes.io/docs/concepts/services-networking/ingress/) is a collection of routing rules that govern how external users access services running in a Kubernetes cluster. There are [three general approaches](https://blog.getambassador.io/kubernetes-ingress-nodeport-load-balancers-and-ingress-controllers-6e29f1c44f2d) for exposing your application:
* Using a `NodePort` to expose your application on a port across each of your nodes
* Using a `LoadBalancer` service to create an external load balancer that points to a Kubernetes service in your cluster
* Using a Kubernetes Ingress resource
### What’s new in Kubernetes 1.18 Ingress
There are three significant additions to the Ingress API in Kubernetes 1.18:
* A new `pathType` field
* A new `IngressClass` resource
* Support for wildcards in hostnames
The new `pathType` field allows you to specify how Ingress paths should match.
The field supports three types: `ImplementationSpecific` (default), `exact`, and `prefix`. Explicitly defining the expected behavior of path matching will allow every ingress-controller to support a user’s needs and will increase portability between ingress-controller implementation solutions.
The `IngressClass` resource specifies how Ingresses should be implemented by controllers. This was added to formalize the commonly used but never standardized `kubernetes.io/ingress.class` annotation and allow for implementation-specific extensions and configuration.
You can read more about these changes, as well as the support for wildcards in hostnames in more detail in [a previous blog post](https://kubernetes.io/blog/2020/04/02/improvements-to-the-ingress-api-in-kubernetes-1.18/).
## Supporting Kubernetes ingress
[Ambassador](https://www.getambassador.io) is an open-source Envoy-based ingress controller. We believe strongly in supporting common standards such as Kubernetes ingress, which we adopted and [announced our initial support for back in 2019](https://blog.getambassador.io/ambassador-ingress-controller-better-config-reporting-updated-envoy-proxy-99dc9139e28f).
Every Ambassador release goes through rigorous testing. Therefore, we also contributed an [open conformance test suite](https://github.com/kubernetes-sigs/ingress-controller-conformance), supporting Kubernetes ingress. We wrote the initial bits of test code and will keep iterating over the newly added features and different versions of the Ingress specification as it evolves to a stable v1 GA release. Documentation and usage samples, is one of our top priorities. We understand how complex usage can be, especially when transitioning from a previous version of an API.
Following a test-driven development approach, the first step we took in supporting Ingress improvements in Ambassador was to translate the revised specification -- both in terms of API and behavior -- into a comprehensible test suite. The test suite, although still under heavy development and going through multiple iterations, was rapidly added to the Ambassador CI infrastructure and acceptance criteria. This means every change to the Ambassador codebase going forward will be compliant with the Ingress API and be tested end-to-end in a lightweight [KIND cluster](https://kind.sigs.k8s.io/). Using KIND allowed us to make rapid improvements while limiting our cloud provider infrastructure bill and testing out unreleased Kubernetes features with pre-release builds.
### Adopting a new specification
With a global comprehension of additions to Ingress introduced in Kubernetes 1.18 and a test suite on hand, we tackled the task of adapting the Ambassador code so that it would support translating the high-level Ingress API resources into Envoy configurations and constructs. Luckily Ambassador already supported previous versions of ingress functionalities so the development effort was incremental.
We settled on a controller name of `getambassador.io/ingress-controller`. This value, consistent with Ambassador's domain and CRD versions, must be used to tie in an IngressClass `spec.controller` with an Ambassador deployment. The new IngressClass resource allows for extensibility by setting a `spec.parameters` field. At the moment Ambassador makes no use of this field and its usage is reserved for future development.
Paths can now define different matching behaviors using the `pathType` field. The field will default to a value of `ImplementationSpecific`, which uses the same matching rules as the [Ambassador Mappings](https://www.getambassador.io/docs/latest/topics/using/mappings/) prefix field and previous Ingress specification for backward compatibility reasons.
### Kubernetes Ingress Controllers
A comprehensive [list of Kubernetes ingress controllers](https://kubernetes.io/docs/concepts/services-networking/ingress-controllers/) is available in the Kubernetes documentation. Currently, Ambassador is the only ingress controller that supports these new additions to the ingress specification. Powered by the [Envoy Proxy](https://www.envoyproxy.io), Ambassador is the fastest way for you to try out the new ingress specification today.
Check out the following resources:
* Ambassador on [GitHub](https://www.github.com/datawire/ambassador)
* The Ambassador [documentation](https://www.getambassador.io/docs)
* [Improvements to the Ingress API](https://kubernetes.io/blog/2020/04/02/improvements-to-the-ingress-api-in-kubernetes-1.18/)
Or join the community on [Slack](http://d6e.co/slack)!
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---
title: Concepts
main_menu: true
content_template: templates/concept
content_type: concept
weight: 40
---
{{% capture overview %}}
<!-- overview -->
The Concepts section helps you learn about the parts of the Kubernetes system and the abstractions Kubernetes uses to represent your {{< glossary_tooltip text="cluster" term_id="cluster" length="all" >}}, and helps you obtain a deeper understanding of how Kubernetes works.
{{% /capture %}}
{{% capture body %}}
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## Overview
@@ -60,12 +60,13 @@ The Kubernetes master is responsible for maintaining the desired state for your
The nodes in a cluster are the machines (VMs, physical servers, etc) that run your applications and cloud workflows. The Kubernetes master controls each node; you'll rarely interact with nodes directly.
{{% /capture %}}
{{% capture whatsnext %}}
## {{% heading "whatsnext" %}}
If you would like to write a concept page, see
[Using Page Templates](/docs/home/contribute/page-templates/)
for information about the concept page type and the concept template.
[Page Content Types](/docs/home/contribute/style/page-content-types/#concept)
for information about the concept page types.
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---
title: Cloud Controller Manager
content_template: templates/concept
content_type: concept
weight: 40
---
{{% capture overview %}}
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{{< feature-state state="beta" for_k8s_version="v1.11" >}}
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The cloud-controller-manager is structured using a plugin
mechanism that allows different cloud providers to integrate their platforms with Kubernetes.
{{% /capture %}}
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## Design
@@ -200,8 +200,9 @@ rules:
- update
```
{{% /capture %}}
{{% capture whatsnext %}}
## {{% heading "whatsnext" %}}
[Cloud Controller Manager Administration](/docs/tasks/administer-cluster/running-cloud-controller/#cloud-controller-manager)
has instructions on running and managing the cloud controller manager.
@@ -212,4 +213,3 @@ The cloud controller manager uses Go interfaces to allow implementations from an
The implementation of the shared controllers highlighted in this document (Node, Route, and Service), and some scaffolding along with the shared cloudprovider interface, is part of the Kubernetes core. Implementations specific to cloud providers are outside the core of Kubernetes and implement the `CloudProvider` interface.
For more information about developing plugins, see [Developing Cloud Controller Manager](/docs/tasks/administer-cluster/developing-cloud-controller-manager/).
{{% /capture %}}
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- dchen1107
- liggitt
title: Control Plane-Node Communication
content_template: templates/concept
content_type: concept
weight: 20
aliases:
- master-node-communication
---
{{% capture overview %}}
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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).
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## Node to Control Plane
All communication paths from the nodes to the control plane terminate at the apiserver (none of the other master components are designed to expose remote services). In a typical deployment, the apiserver is configured to listen for remote connections on a secure HTTPS port (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. For example, on a default GKE deployment, 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.
@@ -31,9 +31,11 @@ The control plane components also communicate with the cluster apiserver over th
As a result, the default operating mode for connections from the nodes and pods running on the nodes to the control plane is secured by default and can run over untrusted and/or public networks.
## Control Plane to node
There are two primary communication paths from the control plane (apiserver) to the nodes. The first is from the apiserver to the kubelet process which runs on each node in the cluster. The second is from the apiserver to any node, pod, or service through the apiserver's proxy functionality.
### apiserver to kubelet
The connections from the apiserver to the kubelet are used for:
* Fetching logs for pods.
@@ -61,9 +63,10 @@ This tunnel ensures that the traffic is not exposed outside of the network in wh
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 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 connections.
All control plane to nodes traffic then goes through these 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.
See [Konnectivity Service Setup](/docs/tasks/setup-konnectivity/) on how to set it up in your cluster.
Follow the [Konnectivity service task](/docs/tasks/extend-kubernetes/setup-konnectivity/) to set up the Konnectivity service in your cluster.
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## Controller pattern
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* Read about the [Kubernetes control plane](/docs/concepts/#kubernetes-control-plane)
* Discover some of the basic [Kubernetes objects](/docs/concepts/#kubernetes-objects)
* Learn more about the [Kubernetes API](/docs/concepts/overview/kubernetes-api/)
* If you want to write your own controller, see [Extension Patterns](/docs/concepts/extend-kubernetes/extend-cluster/#extension-patterns) in Extending Kubernetes.
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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
@@ -23,9 +23,9 @@ The [components](/docs/concepts/overview/components/#node-components) on a node
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## Management
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See [Control Topology Management Policies on a Node](/docs/tasks/administer-cluster/topology-manager/)
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* Learn about the [components](/docs/concepts/overview/components/#node-components) that make up a node.
* Read the [API definition for Node](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#node-v1-core).
* Read the [Node](https://git.k8s.io/community/contributors/design-proposals/architecture/architecture.md#the-kubernetes-node)
section of the architecture design document.
* Read about [taints and tolerations](/docs/concepts/configuration/taint-and-toleration/).
* Read about [cluster autoscaling](/docs/tasks/administer-cluster/cluster-management/#cluster-autoscaling).
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Add-ons extend the functionality of Kubernetes.
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## Networking and Network Policy
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### easyrsa
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x509 certificates to use for authentication as documented
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### kubeadm
[kubeadm](/docs/reference/setup-tools/kubeadm/kubeadm/) is a popular option for creating kubernetes clusters.
kubeadm has configuration options to specify configuration information for cloud providers. For example a typical
@@ -363,7 +363,7 @@ Kubernetes network plugin and should appear in the `[Route]` section of the
[kubenet]: /docs/concepts/cluster-administration/network-plugins/#kubenet
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- davidopp
- lavalamp
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The cluster administration overview is for anyone creating or administering a Kubernetes cluster.
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## Planning a cluster
See the guides in [Setup](/docs/setup/) for examples of how to plan, set up, and configure Kubernetes clusters. The solutions listed in this article are called *distros*.
@@ -68,6 +68,6 @@ Note: Not all distros are actively maintained. Choose distros which have been te
* [Logging and Monitoring Cluster Activity](/docs/concepts/cluster-administration/logging/) explains how logging in Kubernetes works and how to implement it.
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## Enabling API Priority and Fairness
@@ -136,7 +136,7 @@ classes:
controllers.
* The `workload-low` priority level is for requests from any other service
account, which will typically include all requests from controllers runing in
account, which will typically include all requests from controllers running in
Pods.
* The `global-default` priority level handles all other traffic, e.g.
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request and the PriorityLevel to which it was assigned.
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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).
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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.
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## Image Collection
@@ -77,10 +77,11 @@ Including:
| `--low-diskspace-threshold-mb` | `--eviction-hard` or `eviction-soft` | eviction generalizes disk thresholds to other resources |
| `--outofdisk-transition-frequency` | `--eviction-pressure-transition-period` | eviction generalizes disk pressure transition to other resources |
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- piosz
- x13n
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Application and systems logs can help you understand what is happening inside your cluster. 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, 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.
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Cluster-level logging architectures are described in assumption that
a logging backend is present inside or outside of your cluster. If you're
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every application; however, the implementation for such a logging mechanism
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title: Managing Resources
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You've deployed your application and exposed it via a service. Now what? Kubernetes provides a number of tools to help you manage your application deployment, including scaling and updating. Among the features that we will discuss in more depth are [configuration files](/docs/concepts/configuration/overview/) and [labels](/docs/concepts/overview/working-with-objects/labels/).
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## Organizing resource configurations
@@ -402,7 +402,7 @@ For more information, please see [kubectl edit](/docs/reference/generated/kubect
You can use `kubectl patch` to update API objects in place. This command supports JSON patch,
JSON merge patch, and strategic merge patch. See
[Update API Objects in Place Using kubectl patch](/docs/tasks/run-application/update-api-object-kubectl-patch/)
[Update API Objects in Place Using kubectl patch](/docs/tasks/manage-kubernetes-objects/update-api-object-kubectl-patch/)
and
[kubectl patch](/docs/reference/generated/kubectl/kubectl-commands/#patch).
@@ -449,11 +449,12 @@ kubectl edit deployment/my-nginx
That's it! The Deployment will declaratively update the deployed nginx application progressively behind the scene. It ensures that only a certain number of old replicas may be down while they are being updated, and only a certain number of new replicas may be created above the desired number of pods. To learn more details about it, visit [Deployment page](/docs/concepts/workloads/controllers/deployment/).
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- Learn about [how to use `kubectl` for application introspection and debugging](/docs/tasks/debug-application-cluster/debug-application-introspection/).
- See [Configuration Best Practices and Tips](/docs/concepts/configuration/overview/).
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- RainbowMango
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System component metrics can give a better look into what is happening inside them. Metrics are particularly useful for building dashboards and alerts.
Metrics in Kubernetes control plane are emitted in [prometheus format](https://prometheus.io/docs/instrumenting/exposition_formats/) and are human readable.
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## Metrics in Kubernetes
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cloudprovider_gce_api_request_duration_seconds { request = "list_disk"}
```
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* 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](https://kubernetes.io/docs/reference/using-api/deprecation-policy/#deprecating-a-feature-or-behavior )
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Networking is a central part of Kubernetes, but it can be challenging to
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problems to address:
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3. Pod-to-Service communications: this is covered by [services](/docs/concepts/services-networking/service/).
4. External-to-Service communications: this is covered by [services](/docs/concepts/services-networking/service/).
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Kubernetes is all about sharing machines between applications. Typically,
sharing machines requires ensuring that two applications do not try to use the
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The early design of the networking model and its rationale, and some future
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## Proxies
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## Motivation
Use a ConfigMap for setting configuration data separately from application code.
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{{< /note >}}
## Using ConfigMaps
ConfigMaps can be mounted as data volumes. ConfigMaps can also be used by other
parts of the system, without being directly exposed to the Pod. For example,
ConfigMaps can hold data that other parts of the system should use for configuration.
### Using ConfigMaps as files from a Pod
To consume a ConfigMap in a volume in a Pod:
1. Create a config map or use an existing one. Multiple Pods can reference the same config map.
1. Modify your Pod definition to add a volume under `.spec.volumes[]`. Name the volume anything, and have a `.spec.volumes[].configmap.localObjectReference` field set to reference your ConfigMap object.
1. Add a `.spec.containers[].volumeMounts[]` to each container that needs the config map. Specify `.spec.containers[].volumeMounts[].readOnly = true` and `.spec.containers[].volumeMounts[].mountPath` to an unused directory name where you would like the config map to appear.
1. Modify your image or command line so that the program looks for files in that directory. Each key in the config map `data` map becomes the filename under `mountPath`.
This is an example of a Pod that mounts a ConfigMap in a volume:
```yaml
apiVersion: v1
kind: Pod
metadata:
name: mypod
spec:
containers:
- name: mypod
image: redis
volumeMounts:
- name: foo
mountPath: "/etc/foo"
readOnly: true
volumes:
- name: foo
configMap:
name: myconfigmap
```
Each ConfigMap you want to use needs to be referred to in `.spec.volumes`.
If there are multiple containers in the Pod, then each container needs its
own `volumeMounts` block, but only one `.spec.volumes` is needed per ConfigMap.
#### Mounted ConfigMaps are updated automatically
When a config map currently consumed in a volume is updated, projected keys are eventually updated as well.
The kubelet checks whether the mounted config map 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 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
propagation delay, where the cache propagation delay depends on the chosen cache type
(it equals to watch propagation delay, ttl of cache, or zero correspondingly).
{{< feature-state for_k8s_version="v1.18" state="alpha" >}}
The Kubernetes alpha feature _Immutable Secrets and ConfigMaps_ provides an option to set
individual Secrets and ConfigMaps as immutable. For clusters that extensively use ConfigMaps
(at least tens of thousands of unique ConfigMap to Pod mounts), preventing changes to their
data has the following advantages:
- protects you from accidental (or unwanted) updates that could cause applications outages
- improves performance of your cluster by significantly reducing load on kube-apiserver, by
closing watches for config maps marked as immutable.
To use this feature, enable the `ImmutableEmphemeralVolumes`
[feature gate](/docs/reference/command-line-tools-reference/feature-gates/) and set
your Secret or ConfigMap `immutable` field to `true`. For example:
```yaml
apiVersion: v1
kind: ConfigMap
metadata:
...
data:
...
immutable: true
```
{{< note >}}
Once a ConfigMap or Secret is marked as immutable, it is _not_ possible to revert this change
nor to mutate the contents of the `data` field. You can only delete and recreate the ConfigMap.
Existing Pods maintain a mount point to the deleted ConfigMap - it is recommended to recreate
these pods.
{{< /note >}}
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* Read about [Secrets](/docs/concepts/configuration/secret/).
* Read [Configure a Pod to Use a ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/).
* Read [The Twelve-Factor App](https://12factor.net/) to understand the motivation for
separating code from configuration.
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For step-by-step instructions on creating and specifying kubeconfig files, see
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## Supporting multiple clusters, users, and authentication mechanisms
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This document highlights and consolidates configuration best practices that are introduced throughout the user guide, Getting Started documentation, and examples.
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## General Configuration Tips
- When defining configurations, specify the latest stable API version.
@@ -105,5 +105,5 @@ The caching semantics of the underlying image provider make even `imagePullPolic
- Use `kubectl run` and `kubectl expose` to quickly create single-container Deployments and Services. See [Use a Service to Access an Application in a Cluster](/docs/tasks/access-application-cluster/service-access-application-cluster/) for an example.
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In Kubernetes, the Pod's overhead is set at
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@@ -188,11 +188,12 @@ running with a defined Overhead. This functionality is not available in the 1.9
kube-state-metrics, but is expected in a following release. Users will need to build kube-state-metrics
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* [RuntimeClass](/docs/concepts/containers/runtime-class/)
* [PodOverhead Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/20190226-pod-overhead.md)
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scheduler tries to preempt (evict) lower priority Pods to make scheduling of the
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exceeding its requests, it won't be evicted. Another Pod with higher priority
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* Read about using ResourceQuotas in connection with PriorityClasses: [limit Priority Class consumption by default](/docs/concepts/policy/resource-quotas/#limit-priority-class-consumption-by-default)
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## Enabling Bin Packing using RequestedToCapacityRatioResourceAllocation
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Kubernetes Secrets let you store and manage sensitive information, such
as passwords, OAuth tokens, and ssh keys. Storing confidential information in a Secret
is safer and more flexible than putting it verbatim in a
{{< glossary_tooltip term_id="pod" >}} definition or in a {{< glossary_tooltip text="container image" term_id="image" >}}. See [Secrets design document](https://git.k8s.io/community/contributors/design-proposals/auth/secrets.md) for more information.
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## Overview of Secrets
@@ -29,12 +29,13 @@ Pod specification or in an image. Users can create secrets and the system
also creates some secrets.
To use a secret, a Pod needs to reference the secret.
A secret can be used with a Pod in two ways:
A secret can be used with a Pod in three ways:
- As files in a
- As [files](#using-secrets-as-files-from-a-pod) in a
{{< glossary_tooltip text="volume" term_id="volume" >}} mounted on one or more of
its containers.
- By the kubelet when pulling images for the Pod.
- As [container environment variable](#using-secrets-as-environment-variables).
- By the [kubelet when pulling images](#using-imagepullsecrets) for the Pod.
### Built-in Secrets
@@ -725,7 +726,7 @@ data has the following advantages:
- improves performance of your cluster by significantly reducing load on kube-apiserver, by
closing watches for secrets marked as immutable.
To use this feature, enable the `ImmutableEmphemeralVolumes`
To use this feature, enable the `ImmutableEphemeralVolumes`
[feature gate](/docs/reference/command-line-tools-reference/feature-gates/) and set
your Secret or ConfigMap `immutable` field to `true`. For example:
```yaml
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* Learn more about [Container lifecycle hooks](/docs/concepts/containers/container-lifecycle-hooks/).
* Get hands-on experience
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* Learn more about the [Container environment](/docs/concepts/containers/container-environment/).
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## Updating Images
@@ -66,6 +66,7 @@ Credentials can be provided in several ways:
- Using Oracle Cloud Infrastructure Registry (OCIR)
- use IAM roles and policies to control access to OCIR repositories
- Using Azure Container Registry (ACR)
- use IAM roles and policies to control access to ACR repositories
- Using IBM Cloud Container Registry
- use IAM roles and policies to grant access to IBM Cloud Container Registry
- Configuring Nodes to Authenticate to a Private Registry
@@ -130,9 +131,13 @@ Troubleshooting:
- `aws_credentials.go:116] Got ECR credentials from ECR API for <AWS account ID for ECR>.dkr.ecr.<AWS region>.amazonaws.com`
### Using Azure Container Registry (ACR)
When using [Azure Container Registry](https://azure.microsoft.com/en-us/services/container-registry/)
you can authenticate using either an admin user or a service principal.
In either case, authentication is done via standard Docker authentication. These instructions assume the
Kubernetes has native support for the [Azure Container
Registry (ACR)](https://azure.microsoft.com/en-us/services/container-registry/), when running on Azure Kubernetes Service (AKS).
The AKS cluster service principal must have `AcrPull` permission in the ACR instance. See [Authenticate with Azure Container Registry from Azure Kubernetes Service](https://docs.microsoft.com/en-us/azure/aks/cluster-container-registry-integration) for configuration instructions. Then, simply use the full ACR image name (e.g. `my_registry.azurecr.io/image:tag`).
You may also authenticate using either an ACR admin user or a service principal.
In this case, authentication is done via standard Docker authentication. The following instructions assume the
[azure-cli](https://github.com/azure/azure-cli) command line tool.
You first need to create a registry and generate credentials, complete documentation for this can be found in
@@ -370,4 +375,4 @@ common use cases and suggested solutions.
If you need access to multiple registries, you can create one secret for each registry.
Kubelet will merge any `imagePullSecrets` into a single virtual `.docker/config.json`
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@@ -18,10 +18,10 @@ run it.
Containers decouple applications from underlying host infrastructure.
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## Container images
A [container image](/docs/concepts/containers/images/) is a ready-to-run
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## Motivation
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you can specify the overhead of running pods utilizing this RuntimeClass and ensure these overheads
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- [RuntimeClass Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/runtime-class.md)
- [RuntimeClass Scheduling Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/runtime-class-scheduling.md)
- Read about the [Pod Overhead](/docs/concepts/configuration/pod-overhead/) concept
- [PodOverhead Feature Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/20190226-pod-overhead.md)
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Be sure to also [create an entry in the table of contents](/docs/home/contribute/write-new-topic/#creating-an-entry-in-the-table-of-contents) for your new document.
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The aggregation layer allows Kubernetes to be extended with additional APIs, beyond what is offered by the core Kubernetes APIs.
The additional APIs can either be ready-made solutions such as [service-catalog](/docs/concepts/extend-kubernetes/service-catalog/), or APIs that you develop yourself.
The aggregation layer is different from [Custom Resources](/docs/concepts/extend-kubernetes/api-extension/custom-resources/), which are a way to make the {{< glossary_tooltip term_id="kube-apiserver" text="kube-apiserver" >}} recognise new kinds of object.
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`EnableAggregatedDiscoveryTimeout=false` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) on the kube-apiserver
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* To get the aggregator working in your environment, [configure the aggregation layer](/docs/tasks/access-kubernetes-api/configure-aggregation-layer/).
* Then, [setup an extension api-server](/docs/tasks/access-kubernetes-api/setup-extension-api-server/) to work with the aggregation layer.
* Also, learn how to [extend the Kubernetes API using Custom Resource Definitions](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/).
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* To get the aggregator working in your environment, [configure the aggregation layer](/docs/tasks/extend-kubernetes/configure-aggregation-layer/).
* Then, [setup an extension api-server](/docs/tasks/extend-kubernetes/setup-extension-api-server/) to work with the aggregation layer.
* Also, learn how to [extend the Kubernetes API using Custom Resource Definitions](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/).
* Read the specification for [APIService](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#apiservice-v1-apiregistration-k8s-io)
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## Custom resources
A *resource* is an endpoint in the [Kubernetes API](/docs/reference/using-api/api-overview/) that stores a collection of
@@ -128,7 +128,7 @@ Regardless of how they are installed, the new resources are referred to as Custo
## CustomResourceDefinitions
The [CustomResourceDefinition](/docs/tasks/access-kubernetes-api/custom-resources/custom-resource-definitions/)
The [CustomResourceDefinition](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/)
API resource allows you to define custom resources.
Defining a CRD object creates a new custom resource with a name and schema that you specify.
The Kubernetes API serves and handles the storage of your custom resource.
@@ -178,17 +178,17 @@ Aggregated APIs offer more advanced API features and customization of other feat
| Feature | Description | CRDs | Aggregated API |
| ------- | ----------- | ---- | -------------- |
| Validation | Help users prevent errors and allow you to evolve your API independently of your clients. These features are most useful when there are many clients who can't all update at the same time. | Yes. Most validation can be specified in the CRD using [OpenAPI v3.0 validation](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/#validation). Any other validations supported by addition of a [Validating Webhook](/docs/reference/access-authn-authz/admission-controllers/#validatingadmissionwebhook-alpha-in-1-8-beta-in-1-9). | Yes, arbitrary validation checks |
| Defaulting | See above | Yes, either via [OpenAPI v3.0 validation](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/#defaulting) `default` keyword (GA in 1.17), or via a [Mutating Webhook](/docs/reference/access-authn-authz/admission-controllers/#mutatingadmissionwebhook) (though this will not be run when reading from etcd for old objects). | Yes |
| Multi-versioning | Allows serving the same object through two API versions. Can help ease API changes like renaming fields. Less important if you control your client versions. | [Yes](/docs/tasks/access-kubernetes-api/custom-resources/custom-resource-definition-versioning) | Yes |
| Validation | Help users prevent errors and allow you to evolve your API independently of your clients. These features are most useful when there are many clients who can't all update at the same time. | Yes. Most validation can be specified in the CRD using [OpenAPI v3.0 validation](/docs/tasks/extend-kubernetes/extend-api-custom-resource-definitions/#validation). Any other validations supported by addition of a [Validating Webhook](/docs/reference/access-authn-authz/admission-controllers/#validatingadmissionwebhook-alpha-in-1-8-beta-in-1-9). | Yes, arbitrary validation checks |
| Defaulting | See above | Yes, either via [OpenAPI v3.0 validation](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/#defaulting) `default` keyword (GA in 1.17), or via a [Mutating Webhook](/docs/reference/access-authn-authz/admission-controllers/#mutatingadmissionwebhook) (though this will not be run when reading from etcd for old objects). | Yes |
| Multi-versioning | Allows serving the same object through two API versions. Can help ease API changes like renaming fields. Less important if you control your client versions. | [Yes](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definition-versioning) | Yes |
| Custom Storage | If you need storage with a different performance mode (for example, a time-series database instead of key-value store) or isolation for security (for example, encryption of sensitive information, etc.) | No | Yes |
| Custom Business Logic | Perform arbitrary checks or actions when creating, reading, updating or deleting an object | Yes, using [Webhooks](/docs/reference/access-authn-authz/extensible-admission-controllers/#admission-webhooks). | Yes |
| Scale Subresource | Allows systems like HorizontalPodAutoscaler and PodDisruptionBudget interact with your new resource | [Yes](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/#scale-subresource) | Yes |
| Status Subresource | Allows fine-grained access control where user writes the spec section and the controller writes the status section. Allows incrementing object Generation on custom resource data mutation (requires separate spec and status sections in the resource) | [Yes](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/#status-subresource) | Yes |
| Scale Subresource | Allows systems like HorizontalPodAutoscaler and PodDisruptionBudget interact with your new resource | [Yes](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/#scale-subresource) | Yes |
| Status Subresource | Allows fine-grained access control where user writes the spec section and the controller writes the status section. Allows incrementing object Generation on custom resource data mutation (requires separate spec and status sections in the resource) | [Yes](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/#status-subresource) | Yes |
| Other Subresources | Add operations other than CRUD, such as "logs" or "exec". | No | Yes |
| strategic-merge-patch | The new endpoints support PATCH with `Content-Type: application/strategic-merge-patch+json`. Useful for updating objects that may be modified both locally, and by the server. For more information, see ["Update API Objects in Place Using kubectl patch"](/docs/tasks/run-application/update-api-object-kubectl-patch/) | No | Yes |
| strategic-merge-patch | The new endpoints support PATCH with `Content-Type: application/strategic-merge-patch+json`. Useful for updating objects that may be modified both locally, and by the server. For more information, see ["Update API Objects in Place Using kubectl patch"](/docs/tasks/manage-kubernetes-objects/update-api-object-kubectl-patch/) | No | Yes |
| Protocol Buffers | The new resource supports clients that want to use Protocol Buffers | No | Yes |
| OpenAPI Schema | Is there an OpenAPI (swagger) schema for the types that can be dynamically fetched from the server? Is the user protected from misspelling field names by ensuring only allowed fields are set? Are types enforced (in other words, don't put an `int` in a `string` field?) | Yes, based on the [OpenAPI v3.0 validation](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/#validation) schema (GA in 1.16). | Yes |
| OpenAPI Schema | Is there an OpenAPI (swagger) schema for the types that can be dynamically fetched from the server? Is the user protected from misspelling field names by ensuring only allowed fields are set? Are types enforced (in other words, don't put an `int` in a `string` field?) | Yes, based on the [OpenAPI v3.0 validation](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/#validation) schema (GA in 1.16). | Yes |
### Common Features
@@ -246,12 +246,13 @@ When you add a custom resource, you can access it using:
- A REST client that you write.
- A client generated using [Kubernetes client generation tools](https://github.com/kubernetes/code-generator) (generating one is an advanced undertaking, but some projects may provide a client along with the CRD or AA).
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* Learn how to [Extend the Kubernetes API with the aggregation layer](/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/).
* Learn how to [Extend the Kubernetes API with CustomResourceDefinition](/docs/tasks/access-kubernetes-api/custom-resources/custom-resource-definitions/).
* Learn how to [Extend the Kubernetes API with CustomResourceDefinition](/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/).
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## Device plugin registration
@@ -225,12 +225,13 @@ Here are some examples of device plugin implementations:
* The [SR-IOV Network device plugin](https://github.com/intel/sriov-network-device-plugin)
* The [Xilinx FPGA device plugins](https://github.com/Xilinx/FPGA_as_a_Service/tree/master/k8s-fpga-device-plugin/trunk) for Xilinx FPGA devices
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* Learn about [scheduling GPU resources](/docs/tasks/manage-gpus/scheduling-gpus/) using device plugins
* Learn about [advertising extended resources](/docs/tasks/administer-cluster/extended-resource-node/) on a node
* Read about using [hardware acceleration for TLS ingress](https://kubernetes.io/blog/2019/04/24/hardware-accelerated-ssl/tls-termination-in-ingress-controllers-using-kubernetes-device-plugins-and-runtimeclass/) with Kubernetes
* Learn about the [Topology Manager] (/docs/tasks/adminster-cluster/topology-manager/)
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* CNI plugins: adhere to the appc/CNI specification, designed for interoperability.
* Kubenet plugin: implements basic `cbr0` using the `bridge` and `host-local` CNI plugins
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## Installation
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* `--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.
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## Overview
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* Learn more about [Custom Resources](/docs/concepts/api-extension/custom-resources/)
* Learn about [Dynamic admission control](/docs/reference/access-authn-authz/extensible-admission-controllers/)
@@ -207,4 +208,4 @@ the nodes chosen for a pod.
* Learn about [kubectl plugins](/docs/tasks/extend-kubectl/kubectl-plugins/)
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Operators are software extensions to Kubernetes that make use of [custom
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to manage applications and their components. Operators follow
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## Motivation
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You also implement an Operator (that is, a Controller) using any language / runtime
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* 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
@@ -129,4 +130,3 @@ that can act as a [client for the Kubernetes API](/docs/reference/using-api/clie
* 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
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## Introduction
@@ -102,10 +102,11 @@ Pod-by-pod schedulers, such as the Kubernetes default scheduler, process Pods in
These downsides of pod-by-pod schedulers are addressed by batching or bulk scheduling in Poseidon-Firmament scheduler. Processing several pods in a batch allows the scheduler to jointly consider their placement, and thus to find the best trade-off for the whole batch instead of one pod. At the same time it amortizes work across pods resulting in much higher throughput.
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* See [Poseidon-Firmament](https://github.com/kubernetes-sigs/poseidon#readme) on GitHub for more information.
* See the [design document](https://github.com/kubernetes-sigs/poseidon/blob/master/docs/design/README.md) for Poseidon.
* Read [Firmament: Fast, Centralized Cluster Scheduling at Scale](https://www.usenix.org/system/files/conference/osdi16/osdi16-gog.pdf), the academic paper on the Firmament scheduling design.
* If you'd like to contribute to Poseidon-Firmament, refer to the [developer setup instructions](https://github.com/kubernetes-sigs/poseidon/blob/master/docs/devel/README.md).
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{{< glossary_definition term_id="service-catalog" length="all" prepend="Service Catalog is" >}}
A service broker, as defined by the [Open service broker API spec](https://github.com/openservicebrokerapi/servicebroker/blob/v2.13/spec.md), is an endpoint for a set of managed services offered and maintained by a third-party, which could be a cloud provider such as AWS, GCP, or Azure.
@@ -14,10 +14,10 @@ Some examples of managed services are Microsoft Azure Cloud Queue, Amazon Simple
Using Service Catalog, a {{< glossary_tooltip text="cluster operator" term_id="cluster-operator" >}} can browse the list of managed services offered by a service broker, provision an instance of a managed service, and bind with it to make it available to an application in the Kubernetes cluster.
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## Example use case
An {{< glossary_tooltip text="application developer" term_id="application-developer" >}} wants to use message queuing as part of their application running in a Kubernetes cluster.
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key: topic
```
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* If you are familiar with {{< glossary_tooltip text="Helm Charts" term_id="helm-chart" >}}, [install Service Catalog using Helm](/docs/tasks/service-catalog/install-service-catalog-using-helm/) into your Kubernetes cluster. Alternatively, you can [install Service Catalog using the SC tool](/docs/tasks/service-catalog/install-service-catalog-using-sc/).
* View [sample service brokers](https://github.com/openservicebrokerapi/servicebroker/blob/master/gettingStarted.md#sample-service-brokers).
* Explore the [kubernetes-incubator/service-catalog](https://github.com/kubernetes-incubator/service-catalog) project.
* View [svc-cat.io](https://svc-cat.io/docs/).
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When you deploy Kubernetes, you get a cluster.
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## Control Plane Components
The control plane's components make global decisions about the cluster (for example, scheduling), as well as detecting and responding to cluster events (for example, starting up a new {{< glossary_tooltip text="pod" term_id="pod">}} when a deployment's `replicas` field is unsatisfied).
@@ -122,10 +122,11 @@ about containers in a central database, and provides a UI for browsing that data
A [cluster-level logging](/docs/concepts/cluster-administration/logging/) mechanism is responsible for
saving container logs to a central log store with search/browsing interface.
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* Learn about [Nodes](/docs/concepts/architecture/nodes/)
* Learn about [Controllers](/docs/concepts/architecture/controller/)
* Learn about [kube-scheduler](/docs/concepts/scheduling-eviction/kube-scheduler/)
* Read etcd's official [documentation](https://etcd.io/docs/)
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title: The Kubernetes API
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The core of Kubernetes' {{< glossary_tooltip text="control plane" term_id="control-plane" >}}
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## API changes
@@ -135,10 +136,10 @@ There are several API groups in a cluster:
There are two paths to extending the API with [custom resources](/docs/concepts/api-extension/custom-resources/):
1. [CustomResourceDefinition](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/)
1. [CustomResourceDefinition](/docs/tasks/extend-kubernetes/custom-resource-definitions/)
lets you declaratively define how the API server should provide your chosen resource API.
1. You can also [implement your own extension API server](/docs/tasks/access-kubernetes-api/setup-extension-api-server/)
and use the [aggregator](/docs/tasks/access-kubernetes-api/configure-aggregation-layer/)
1. You can also [implement your own extension API server](/docs/tasks/extend-kubernetes/setup-extension-api-server/)
and use the [aggregator](/docs/tasks/extend-kubernetes/configure-aggregation-layer/)
to make it seamless for clients.
## Enabling or disabling API groups
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Kubernetes stores its serialized state in terms of the API resources by writing them into
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[Controlling API Access](/docs/reference/access-authn-authz/controlling-access/) describes
how the cluster manages authentication and authorization for API access.
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document.
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title: What is Kubernetes?
description: >
Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
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Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
The name Kubernetes originates from Greek, meaning helmsman or pilot. Google open-sourced the Kubernetes project in 2014. Kubernetes combines [over 15 years of Google's experience](/blog/2015/04/borg-predecessor-to-kubernetes/) running production workloads at scale with best-of-breed ideas and practices from the community.
@@ -86,9 +86,10 @@ Kubernetes:
* Does not provide nor adopt any comprehensive machine configuration, maintenance, management, or self-healing systems.
* Additionally, Kubernetes is not a mere orchestration system. In fact, it eliminates the need for orchestration. The technical definition of orchestration is execution of a defined workflow: first do A, then B, then C. In contrast, Kubernetes comprises a set of independent, composable control processes that continuously drive the current state towards the provided desired state. It shouldn’t matter how you get from A to C. Centralized control is also not required. This results in a system that is easier to use and more powerful, robust, resilient, and extensible.
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* Take a look at the [Kubernetes Components](/docs/concepts/overview/components/)
* Ready to [Get Started](/docs/setup/)?
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## Attaching metadata to objects
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You can visualize and manage Kubernetes objects with more tools than kubectl and
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The metadata is organized around the concept of an _application_. Kubernetes is not
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```
{{< note >}}
Field selectors are essentially resource *filters*. By default, no selectors/filters are applied, meaning that all resources of the specified type are selected. This makes the following `kubectl` queries equivalent:
```shell
kubectl get pods
kubectl get pods --field-selector ""
```
Field selectors are essentially resource *filters*. By default, no selectors/filters are applied, meaning that all resources of the specified type are selected. This makes the `kubectl` queries `kubectl get pods` and `kubectl get pods --field-selector ""` equivalent.
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## Supported fields
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## Understanding Kubernetes objects {#kubernetes-objects}
*Kubernetes objects* are persistent entities in the Kubernetes system. Kubernetes uses these entities to represent the state of your cluster. Specifically, they can describe:
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and the `spec` format for a Deployment can be found in
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* [Kubernetes API overview](/docs/reference/using-api/api-overview/) explains some more API concepts
* Learn about the most important basic Kubernetes objects, such as [Pod](/docs/concepts/workloads/pods/pod-overview/).
* Learn about [controllers](/docs/concepts/architecture/controller/) in Kubernetes
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_Labels_ are key/value pairs that are attached to objects, such as pods.
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## Motivation
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- thockin
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Each object in your cluster has a [_Name_](#names) that is unique for that type of resource.
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## Names
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* Read about [labels](/docs/concepts/overview/working-with-objects/labels/) in Kubernetes.
* See the [Identifiers and Names in Kubernetes](https://git.k8s.io/community/contributors/design-proposals/architecture/identifiers.md) design document.
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kubectl api-resources --namespaced=false
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* Learn more about [creating a new namespace](/docs/tasks/administer-cluster/namespaces/#creating-a-new-namespace).
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- Declarative object configuration is harder to debug and understand results when they are unexpected.
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- [Managing Kubernetes Objects Using Imperative Commands](/docs/tasks/manage-kubernetes-objects/imperative-command/)
- [Managing Kubernetes Objects Using Object Configuration (Imperative)](/docs/tasks/manage-kubernetes-objects/imperative-config/)
@@ -185,4 +186,4 @@ Disadvantages compared to imperative object configuration:
- [Kubectl Book](https://kubectl.docs.kubernetes.io)
- [Kubernetes API Reference](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/)
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By default, containers run with unbounded [compute resources](/docs/user-guide/compute-resources) on a Kubernetes cluster.
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Within a namespace, a Pod or Container can consume as much CPU and memory as defined by the namespace's resource quota. There is a concern that one Pod or Container could monopolize all available resources. A LimitRange is a policy to constrain resource allocations (to Pods or Containers) in a namespace.
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## Enabling LimitRange
LimitRange support is enabled by default for many Kubernetes distributions. It is
enabled when the apiserver `--enable-admission-plugins=` flag has `LimitRanger` admission controller as
one of its arguments.
LimitRange support has been enabled by default since Kubernetes 1.10.
A LimitRange is enforced in a particular namespace when there is a
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- tallclair
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## What is a Pod Security Policy?
@@ -34,7 +34,7 @@ administrator to control the following:
| Usage of host networking and ports | [`hostNetwork`, `hostPorts`](#host-namespaces) |
| Usage of volume types | [`volumes`](#volumes-and-file-systems) |
| Usage of the host filesystem | [`allowedHostPaths`](#volumes-and-file-systems) |
| White list of FlexVolume drivers | [`allowedFlexVolumes`](#flexvolume-drivers) |
| Allow specific FlexVolume drivers | [`allowedFlexVolumes`](#flexvolume-drivers) |
| Allocating an FSGroup that owns the pod's volumes | [`fsGroup`](#volumes-and-file-systems) |
| Requiring the use of a read only root file system | [`readOnlyRootFilesystem`](#volumes-and-file-systems) |
| The user and group IDs of the container | [`runAsUser`, `runAsGroup`, `supplementalGroups`](#users-and-groups) |
@@ -401,13 +401,13 @@ namespace. Doing so gives the pod access to the loopback device, services
listening on localhost, and could be used to snoop on network activity of other
pods on the same node.
**HostPorts** - Provides a whitelist of ranges of allowable ports in the host
**HostPorts** - Provides a list of ranges of allowable ports in the host
network namespace. Defined as a list of `HostPortRange`, with `min`(inclusive)
and `max`(inclusive). Defaults to no allowed host ports.
### Volumes and file systems
**Volumes** - Provides a whitelist of allowed volume types. The allowable values
**Volumes** - Provides a list of allowed volume types. The allowable values
correspond to the volume sources that are defined when creating a volume. For
the complete list of volume types, see [Types of
Volumes](/docs/concepts/storage/volumes/#types-of-volumes). Additionally, `*`
@@ -438,7 +438,7 @@ minimum value of the first range as the default. Validates against all ranges.
all ranges if `FSGroups` is set.
- *RunAsAny* - No default provided. Allows any `fsGroup` ID to be specified.
**AllowedHostPaths** - This specifies a whitelist of host paths that are allowed
**AllowedHostPaths** - This specifies a list of host paths that are allowed
to be used by hostPath volumes. An empty list means there is no restriction on
host paths used. This is defined as a list of objects with a single `pathPrefix`
field, which allows hostPath volumes to mount a path that begins with an
@@ -469,7 +469,7 @@ root filesystem (i.e. no writable layer).
### FlexVolume drivers
This specifies a whitelist of FlexVolume drivers that are allowed to be used
This specifies a list of FlexVolume drivers that are allowed to be used
by flexvolume. An empty list or nil means there is no restriction on the drivers.
Please make sure [`volumes`](#volumes-and-file-systems) field contains the
`flexVolume` volume type; no FlexVolume driver is allowed otherwise.
@@ -555,7 +555,7 @@ the PodSecurityPolicy. For more details on Linux capabilities, see
The following fields take a list of capabilities, specified as the capability
name in ALL_CAPS without the `CAP_` prefix.
**AllowedCapabilities** - Provides a whitelist of capabilities that may be added
**AllowedCapabilities** - Provides a list of capabilities that are allowed to be added
to a container. The default set of capabilities are implicitly allowed. The
empty set means that no additional capabilities may be added beyond the default
set. `*` can be used to allow all capabilities.
@@ -579,7 +579,7 @@ specified.
### AllowedProcMountTypes
`allowedProcMountTypes` is a whitelist of allowed ProcMountTypes.
`allowedProcMountTypes` is a list of allowed ProcMountTypes.
Empty or nil indicates that only the `DefaultProcMountType` may be used.
`DefaultProcMount` uses the container runtime defaults for readonly and masked
@@ -631,12 +631,13 @@ By default, all safe sysctls are allowed.
Refer to the [Sysctl documentation](
/docs/concepts/cluster-administration/sysctl-cluster/#podsecuritypolicy).
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## {{% heading "whatsnext" %}}
See [Pod Security Standards](/docs/concepts/security/pod-security-standards/) for policy recommendations.
Refer to [Pod Security Policy Reference](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#podsecuritypolicy-v1beta1-policy) for the api details.
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reviewers:
- derekwaynecarr
title: Resource Quotas
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When several users or teams share a cluster with a fixed number of nodes,
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Resource quotas are a tool for administrators to address this concern.
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A resource quota, defined by a `ResourceQuota` object, provides constraints that limit
aggregate resource consumption per namespace. It can limit the quantity of objects that can
@@ -596,10 +596,11 @@ See [LimitedResources](https://github.com/kubernetes/kubernetes/pull/36765) and
See a [detailed example for how to use resource quota](/docs/tasks/administer-cluster/quota-api-object/).
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See [ResourceQuota design doc](https://git.k8s.io/community/contributors/design-proposals/resource-management/admission_control_resource_quota.md) for more information.
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@@ -4,12 +4,12 @@ reviewers:
- kevin-wangzefeng
- bsalamat
title: Assigning Pods to Nodes
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You can constrain a {{< glossary_tooltip text="Pod" term_id="pod" >}} to only be able to run on particular
{{< glossary_tooltip text="Node(s)" term_id="node" >}}, or to prefer to run on particular nodes.
@@ -21,9 +21,9 @@ but there are some circumstances where you may want more control on a node where
that a pod ends up on a machine with an SSD attached to it, or to co-locate pods from two different
services that communicate a lot into the same availability zone.
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## nodeSelector
@@ -213,10 +213,8 @@ 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 `failure-domain.beta.kubernetes.io/zone` and some value V
such that there is at least one node in the cluster with key `failure-domain.beta.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 prefers not to be scheduled onto a node if that node is already running a pod with label
having key "security" and value "S2". (If the `topologyKey` were `failure-domain.beta.kubernetes.io/zone` then
it would mean 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
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`
flavor and the `preferredDuringSchedulingIgnoredDuringExecution` flavor.
@@ -388,9 +386,10 @@ spec:
The above pod will run on the node kube-01.
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[Taints](/docs/concepts/scheduling-eviction/taint-and-toleration/) allow a Node to *repel* a set of Pods.
@@ -402,4 +401,4 @@ Once a Pod is assigned to a Node, the kubelet runs the Pod and allocates node-lo
The [topology manager](/docs/tasks/administer-cluster/topology-manager/) can take part in node-level
resource allocation decisions.
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## Scheduling overview {#scheduling}
@@ -86,12 +86,13 @@ of the scheduler:
`QueueSort`, `Filter`, `Score`, `Bind`, `Reserve`, `Permit`, and others. You
can also configure the kube-scheduler to run different profiles.
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* Read about [scheduler performance tuning](/docs/concepts/scheduling-eviction/scheduler-perf-tuning/)
* Read about [Pod topology spread constraints](/docs/concepts/workloads/pods/pod-topology-spread-constraints/)
* Read the [reference documentation](/docs/reference/command-line-tools-reference/kube-scheduler/) for kube-scheduler
* Learn about [configuring multiple schedulers](/docs/tasks/administer-cluster/configure-multiple-schedulers/)
* Learn about [topology management policies](/docs/tasks/administer-cluster/topology-manager/)
* Learn about [Pod Overhead](/docs/concepts/configuration/pod-overhead/)
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- bsalamat
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{{< feature-state for_k8s_version="v1.14" state="beta" >}}
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This page explains performance tuning optimizations that are relevant for
large Kubernetes clusters.
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In large clusters, you can tune the scheduler's behaviour balancing
scheduling outcomes between latency (new Pods are placed quickly) and
@@ -164,4 +164,4 @@ Node 1, Node 5, Node 2, Node 6, Node 3, Node 4
After going over all the Nodes, it goes back to Node 1.
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- ahg-g
title: Scheduling Framework
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{{< feature-state for_k8s_version="v1.15" state="alpha" >}}
@@ -20,9 +20,9 @@ framework.
[kep]: https://github.com/kubernetes/enhancements/blob/master/keps/sig-scheduling/20180409-scheduling-framework.md
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# Framework workflow
@@ -239,4 +239,3 @@ If you are using Kubernetes v1.18 or later, you can configure a set of plugins a
a scheduler profile and then define multiple profiles to fit various kinds of workload.
Learn more at [multiple profiles](/docs/reference/scheduling/profiles/#multiple-profiles).
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- kevin-wangzefeng
- bsalamat
title: Taints and Tolerations
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[_Node affinity_](/docs/concepts/scheduling-eviction/assign-pod-node/#affinity-and-anti-affinity),
is a property of {{< glossary_tooltip text="Pods" term_id="pod" >}} that *attracts* them to
a set of {{< glossary_tooltip text="nodes" term_id="node" >}} (either as a preference or a
@@ -22,9 +22,9 @@ Taints and tolerations work together to ensure that pods are not scheduled
onto inappropriate nodes. One or more taints are applied to a node; this
marks that the node should not accept any pods that do not tolerate the taints.
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## Concepts
@@ -282,9 +282,10 @@ tolerations to all daemons, to prevent DaemonSets from breaking.
Adding these tolerations ensures backward compatibility. You can also add
arbitrary tolerations to DaemonSets.
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* Read about [out of resource handling](/docs/tasks/administer-cluster/out-of-resource/) and how you can configure it
* Read about [pod priority](/docs/concepts/configuration/pod-priority-preemption/)
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@@ -2,13 +2,13 @@
reviewers:
- zparnold
title: Overview of Cloud Native Security
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Kubernetes Security (and security in general) is an immense topic that has many
highly interrelated parts. In today's era where open source software is
integrated into many of the systems that help web applications run,
@@ -17,9 +17,9 @@ think about security holistically. This guide will define a mental model
for some general concepts surrounding Cloud Native Security. The mental model is completely arbitrary
and you should only use it if it helps you think about where to secure your software
stack.
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## The 4C's of Cloud Native Security
Let's start with a diagram that may help you understand how you can think about security in layers.
@@ -153,12 +153,13 @@ Most of the above mentioned suggestions can actually be automated in your code
delivery pipeline as part of a series of checks in security. To learn about a
more "Continuous Hacking" approach to software delivery, [this article](https://thenewstack.io/beyond-ci-cd-how-continuous-hacking-of-docker-containers-and-pipeline-driven-security-keeps-ygrene-secure/) provides more detail.
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* Read about [network policies for Pods](/docs/concepts/services-networking/network-policies/)
* Read about [securing your cluster](/docs/tasks/administer-cluster/securing-a-cluster/)
* Read about [API access control](/docs/reference/access-authn-authz/controlling-access/)
* Read about [data encryption in transit](/docs/tasks/tls/managing-tls-in-a-cluster/) for the control plane
* Read about [data encryption at rest](/docs/tasks/administer-cluster/encrypt-data/)
* Read about [Secrets in Kubernetes](/docs/concepts/configuration/secret/)
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reviewers:
- tallclair
title: Pod Security Standards
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Security settings for Pods are typically applied by using [security
contexts](/docs/tasks/configure-pod-container/security-context/). Security Contexts allow for the
@@ -21,9 +21,9 @@ However, numerous means of policy enforcement have arisen that augment or replac
PodSecurityPolicy. The intent of this page is to detail recommended Pod security profiles, decoupled
from any specific instantiation.
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## Policy Types
@@ -43,9 +43,9 @@ should range from highly restricted to highly flexible:
The Privileged policy is purposely-open, and entirely unrestricted. This type of policy is typically
aimed at system- and infrastructure-level workloads managed by privileged, trusted users.
The privileged policy is defined by an absence of restrictions. For blacklist-oriented enforcement
The privileged policy is defined by an absence of restrictions. For allow-by-default enforcement
mechanisms (such as gatekeeper), the privileged profile may be an absence of applied constraints
rather than an instantiated policy. In contrast, for a whitelist oriented mechanism (such as Pod
rather than an instantiated policy. In contrast, for a deny-by-default mechanism (such as Pod
Security Policy) the privileged policy should enable all controls (disable all restrictions).
### Baseline/Default
@@ -56,8 +56,8 @@ developers of non-critical applications. The following listed controls should be
enforced/disallowed:
<table>
<caption style="display:none">Baseline policy specification</caption>
<tbody>
<caption style="display:none">Baseline policy specification</caption>
<tbody>
<tr>
<td><strong>Control</strong></td>
<td><strong>Policy</strong></td>
@@ -90,7 +90,7 @@ enforced/disallowed:
<br><b>Restricted Fields:</b><br>
spec.containers[*].securityContext.capabilities.add<br>
spec.initContainers[*].securityContext.capabilities.add<br>
<br><b>Allowed Values:</b> empty (optionally whitelisted defaults)<br>
<br><b>Allowed Values:</b> empty (or restricted to a known list)<br>
</td>
</tr>
<tr>
@@ -105,20 +105,20 @@ enforced/disallowed:
<tr>
<td>Host Ports</td>
<td>
HostPorts should be disallowed, or at minimum restricted to a whitelist.<br>
HostPorts should be disallowed, or at minimum restricted to a known list.<br>
<br><b>Restricted Fields:</b><br>
spec.containers[*].ports[*].hostPort<br>
spec.initContainers[*].ports[*].hostPort<br>
<br><b>Allowed Values:</b> 0, undefined, (whitelisted)<br>
<br><b>Allowed Values:</b> 0, undefined (or restricted to a known list)<br>
</td>
</tr>
<tr>
<td>AppArmor <em>(optional)</em></td>
<td>
On supported hosts, the `runtime/default` AppArmor profile is applied by default. The default policy should prevent overriding or disabling the policy, or restrict overrides to a whitelisted set of profiles.<br>
On supported hosts, the 'runtime/default' AppArmor profile is applied by default. The default policy should prevent overriding or disabling the policy, or restrict overrides to an allowed set of profiles.<br>
<br><b>Restricted Fields:</b><br>
metadata.annotations['container.apparmor.security.beta.kubernetes.io/*']<br>
<br><b>Allowed Values:</b> runtime/default, undefined<br>
<br><b>Allowed Values:</b> 'runtime/default', undefined<br>
</td>
</tr>
<tr>
@@ -132,6 +132,31 @@ enforced/disallowed:
<br><b>Allowed Values:</b> undefined/nil<br>
</td>
</tr>
<tr>
<td>/proc Mount Type</td>
<td>
The default /proc masks are set up to reduce attack surface, and should be required.<br>
<br><b>Restricted Fields:</b><br>
spec.containers[*].securityContext.procMount<br>
spec.initContainers[*].securityContext.procMount<br>
<br><b>Allowed Values:</b> undefined/nil, 'Default'<br>
</td>
</tr>
<tr>
<td>Sysctls</td>
<td>
Sysctls can disable security mechanisms or affect all containers on a host, and should be disallowed except for an allowed "safe" subset.
A sysctl is considered safe if it is namespaced in the container or the Pod, and it is isolated from other Pods or processes on the same Node.<br>
<br><b>Restricted Fields:</b><br>
spec.securityContext.sysctls<br>
<br><b>Allowed Values:</b><br>
kernel.shm_rmid_forced<br>
net.ipv4.ip_local_port_range<br>
net.ipv4.tcp_syncookies<br>
net.ipv4.ping_group_range<br>
undefined/empty<br>
</td>
</tr>
</tbody>
</table>
@@ -143,7 +168,7 @@ well as lower-trust users.The following listed controls should be enforced/disal
<table>
<caption style="display:none">Restricted policy specification</caption>
<caption style="display:none">Restricted policy specification</caption>
<tbody>
<tr>
<td><strong>Control</strong></td>
@@ -184,7 +209,7 @@ well as lower-trust users.The following listed controls should be enforced/disal
<tr>
<td>Privilege Escalation</td>
<td>
Privilege escalation to root should not be allowed.<br>
Privilege escalation to root should not be allowed.<br>
<br><b>Restricted Fields:</b><br>
spec.containers[*].securityContext.privileged<br>
spec.initContainers[*].securityContext.privileged<br>
@@ -194,7 +219,7 @@ well as lower-trust users.The following listed controls should be enforced/disal
<tr>
<td>Running as Non-root</td>
<td>
Containers must be required to run as non-root users.<br>
Containers must be required to run as non-root users.<br>
<br><b>Restricted Fields:</b><br>
spec.securityContext.runAsNonRoot<br>
spec.containers[*].securityContext.runAsNonRoot<br>
@@ -205,7 +230,7 @@ well as lower-trust users.The following listed controls should be enforced/disal
<tr>
<td>Non-root groups <em>(optional)</em></td>
<td>
Containers should be forbidden from running with a root primary or supplementary GID.<br>
Containers should be forbidden from running with a root primary or supplementary GID.<br>
<br><b>Restricted Fields:</b><br>
spec.securityContext.runAsGroup<br>
spec.securityContext.supplementalGroups[*]<br>
@@ -224,12 +249,12 @@ well as lower-trust users.The following listed controls should be enforced/disal
<tr>
<td>Seccomp</td>
<td>
The runtime/default seccomp profile must be required, or allow additional whitelisted values.<br>
The 'runtime/default' seccomp profile must be required, or allow specific additional profiles.<br>
<br><b>Restricted Fields:</b><br>
metadata.annotations['seccomp.security.alpha.kubernetes.io/pod']<br>
metadata.annotations['container.seccomp.security.alpha.kubernetes.io/*']<br>
<br><b>Allowed Values:</b><br>
runtime/default<br>
'runtime/default'<br>
undefined (container annotation)<br>
</td>
</tr>
@@ -297,4 +322,4 @@ kernel. This allows for workloads requiring heightened permissions to still be i
Additionally, the protection of sandboxed workloads is highly dependent on the method of
sandboxing. As such, no single ‘recommended’ policy is recommended for all sandboxed workloads.
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- rickypai
- thockin
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## Default Hosts File Content
@@ -125,5 +125,5 @@ overwritten whenever the `hosts` file is remounted by Kubelet in the event of
a container restart or a Pod reschedule. Thus, it is not suggested to modify
the contents of the file.
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- lavalamp
- thockin
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## The Kubernetes model for connecting containers
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## Exposing pods to the cluster
@@ -394,8 +394,8 @@ kubectl edit svc my-nginx
kubectl get svc my-nginx
```
```
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
my-nginx ClusterIP 10.0.162.149 162.222.184.144 80/TCP,81/TCP,82/TCP 21s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
my-nginx LoadBalancer 10.0.162.149 xx.xxx.xxx.xxx 8080:30163/TCP 21s
```
```
curl https://<EXTERNAL-IP> -k
@@ -418,12 +418,13 @@ LoadBalancer Ingress: a320587ffd19711e5a37606cf4a74574-1142138393.us-east-1.el
...
```
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* Learn more about [Using a Service to Access an Application in a Cluster](/docs/tasks/access-application-cluster/service-access-application-cluster/)
* Learn more about [Connecting a Front End to a Back End Using a Service](/docs/tasks/access-application-cluster/connecting-frontend-backend/)
* Learn more about [Creating an External Load Balancer](/docs/tasks/access-application-cluster/create-external-load-balancer/)
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- thockin
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## Introduction
@@ -66,6 +66,13 @@ of the form `auto-generated-name.my-svc.my-namespace.svc.cluster-domain.example`
## Pods
### A/AAAA records
Any pods created by a Deployment or DaemonSet have the following
DNS resolution available:
`pod-ip-address.deployment-name.my-namespace.svc.cluster-domain.example.`
### Pod's hostname and subdomain fields
Currently when a pod is created, its hostname is the Pod's `metadata.name` value.
@@ -262,11 +269,11 @@ The availability of Pod DNS Config and DNS Policy "`None`" is shown as below.
| 1.10 | Beta (on by default)|
| 1.9 | Alpha |
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Allocation of IPv4 and IPv6 addresses to Pods and Services
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## Supported Features
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* [Validate IPv4/IPv6 dual-stack](/docs/tasks/network/validate-dual-stack) networking
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## Motivation
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repacking of EndpointSlices with all pods and their corresponding endpoints
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* [Enabling EndpointSlices](/docs/tasks/administer-cluster/enabling-endpointslices)
* Read [Connecting Applications with Services](/docs/concepts/services-networking/connect-applications-service/)
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@@ -16,9 +16,9 @@ that best fits your cluster.
Kubernetes as a project currently supports and maintains [GCE](https://git.k8s.io/ingress-gce/README.md) and
[nginx](https://git.k8s.io/ingress-nginx/README.md) controllers.
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## Additional controllers
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Make sure you review your ingress controller's documentation to understand the caveats of choosing it.
{{< /note >}}
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* Learn more about [Ingress](/docs/concepts/services-networking/ingress/).
* [Set up Ingress on Minikube with the NGINX Controller](/docs/tasks/access-application-cluster/ingress-minikube).
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title: Ingress
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## Terminology
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* Use [Service.Type=LoadBalancer](/docs/concepts/services-networking/service/#loadbalancer)
* Use [Service.Type=NodePort](/docs/concepts/services-networking/service/#nodeport)
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* Learn about the [Ingress API](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#ingress-v1beta1-networking-k8s-io)
* Learn about [Ingress Controllers](/docs/concepts/services-networking/ingress-controllers/)
* [Set up Ingress on Minikube with the NGINX Controller](/docs/tasks/access-application-cluster/ingress-minikube)
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title: Network Policies
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A network policy is a specification of how groups of {{< glossary_tooltip text="pods" term_id="pod">}} are allowed to communicate with each other and other network endpoints.
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## Prerequisites
Network policies are implemented by the [network plugin](/docs/concepts/extend-kubernetes/compute-storage-net/network-plugins/). To use network policies, you must be using a networking solution which supports NetworkPolicy. Creating a NetworkPolicy resource without a controller that implements it will have no effect.
@@ -89,9 +89,9 @@ __podSelector__: Each NetworkPolicy includes a `podSelector` which selects the g
__policyTypes__: Each NetworkPolicy includes a `policyTypes` list which may include either `Ingress`, `Egress`, or both. The `policyTypes` field indicates whether or not the given policy applies to ingress traffic to selected pod, egress traffic from selected pods, or both. If no `policyTypes` are specified on a NetworkPolicy then by default `Ingress` will always be set and `Egress` will be set if the NetworkPolicy has any egress rules.
__ingress__: Each NetworkPolicy may include a list of whitelist `ingress` rules. Each rule allows traffic which matches both the `from` and `ports` sections. The example policy contains a single rule, which matches traffic on a single port, from one of three sources, the first specified via an `ipBlock`, the second via a `namespaceSelector` and the third via a `podSelector`.
__ingress__: Each NetworkPolicy may include a list of allowed `ingress` rules. Each rule allows traffic which matches both the `from` and `ports` sections. The example policy contains a single rule, which matches traffic on a single port, from one of three sources, the first specified via an `ipBlock`, the second via a `namespaceSelector` and the third via a `podSelector`.
__egress__: Each NetworkPolicy may include a list of whitelist `egress` rules. Each rule allows traffic which matches both the `to` and `ports` sections. The example policy contains a single rule, which matches traffic on a single port to any destination in `10.0.0.0/24`.
__egress__: Each NetworkPolicy may include a list of allowed `egress` rules. Each rule allows traffic which matches both the `to` and `ports` sections. The example policy contains a single rule, which matches traffic on a single port to any destination in `10.0.0.0/24`.
So, the example NetworkPolicy:
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- See the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/)
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- See more [recipes](https://github.com/ahmetb/kubernetes-network-policy-recipes) for common scenarios enabled by the NetworkPolicy resource.
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Routing of service traffic based upon cluster topology.
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## Introduction
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* Read [Connecting Applications with Services](/docs/concepts/services-networking/connect-applications-service/)
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No need to modify your application to use an unfamiliar service discovery mechanism. Kubernetes gives Pods their own IP addresses and a single DNS name for a set of Pods, and can load-balance across them.
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Kubernetes gives Pods their own IP addresses and a single DNS name for a set of Pods,
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## Motivation
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* Read [Connecting Applications with Services](/docs/concepts/services-networking/connect-applications-service/)
* Read about [Ingress](/docs/concepts/services-networking/ingress/)
* Read about [EndpointSlices](/docs/concepts/services-networking/endpoint-slices/)
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Dynamic volume provisioning allows storage volumes to be created on-demand.
Without dynamic provisioning, cluster administrators have to manually make
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the need for cluster administrators to pre-provision storage. Instead, it
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## Background
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Pods are scheduled. This can be accomplished by setting the [Volume Binding
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Automatically mount the storage system of your choice, whether from local storage, a public cloud provider such as <a href="https://cloud.google.com/storage/">GCP</a> or <a href="https://aws.amazon.com/products/storage/">AWS</a>, or a network storage system such as NFS, iSCSI, Gluster, Ceph, Cinder, or Flocker.
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## Introduction
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dynamic storage support (in which case the user should create a matching PV)
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* Learn more about [Creating a PersistentVolume](/docs/tasks/configure-pod-container/configure-persistent-volume-storage/#create-a-persistentvolume).
* Learn more about [Creating a PersistentVolumeClaim](/docs/tasks/configure-pod-container/configure-persistent-volume-storage/#create-a-persistentvolumeclaim).
@@ -759,4 +760,3 @@ and need persistent storage, it is recommended that you use the following patter
* [PersistentVolumeSpec](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#persistentvolumespec-v1-core)
* [PersistentVolumeClaim](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#persistentvolumeclaim-v1-core)
* [PersistentVolumeClaimSpec](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#persistentvolumeclaimspec-v1-core)
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## Introduction
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## Kubernetes default limits
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## Introduction
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Upon availability of the new PVC, the cloned PVC is consumed the same as other PVC. It's also expected at this point that the newly created PVC is an independent object. It can be consumed, cloned, snapshotted, or deleted independently and without consideration for it's original dataSource PVC. This also implies that the source is not linked in any way to the newly created clone, it may also be modified or deleted without affecting the newly created clone.
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This document describes the concept of `VolumeSnapshotClass` in Kubernetes. Familiarity
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## Introduction
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the volume snapshot class. Different parameters may be accepted depending on the
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## Introduction
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On-disk files in a Container are ephemeral, which presents some problems for
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## CronJob
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[Cron expression format](https://pkg.go.dev/github.com/robfig/cron?tab=doc#hdr-CRON_Expression_Format)
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A _DaemonSet_ ensures that all (or some) Nodes run a copy of a Pod. As nodes are added to the
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@@ -18,18 +18,18 @@ collected. Deleting a DaemonSet will clean up the Pods it created.
Some typical uses of a DaemonSet are:
- running a cluster storage daemon, such as `glusterd`, `ceph`, on each node.
- running a logs collection daemon on every node, such as `fluentd` or `filebeat`.
- running a node monitoring daemon on every node, such as [Prometheus Node Exporter](https://github.com/prometheus/node_exporter), [Flowmill](https://github.com/Flowmill/flowmill-k8s/), [Sysdig Agent](https://docs.sysdig.com), `collectd`, [Dynatrace OneAgent](https://www.dynatrace.com/technologies/kubernetes-monitoring/), [AppDynamics Agent](https://docs.appdynamics.com/display/CLOUD/Container+Visibility+with+Kubernetes), [Datadog agent](https://docs.datadoghq.com/agent/kubernetes/daemonset_setup/), [New Relic agent](https://docs.newrelic.com/docs/integrations/kubernetes-integration/installation/kubernetes-installation-configuration), Ganglia `gmond`, [Instana Agent](https://www.instana.com/supported-integrations/kubernetes-monitoring/) or [Elastic Metricbeat](https://www.elastic.co/guide/en/beats/metricbeat/current/running-on-kubernetes.html).
- running a cluster storage daemon on every node
- running a logs collection daemon on every node
- running a node monitoring daemon on every node
In a simple case, one DaemonSet, covering all nodes, would be used for each type of daemon.
A more complex setup might use multiple DaemonSets for a single type of daemon, but with
different flags and/or different memory and cpu requests for different hardware types.
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## Writing a DaemonSet Spec
@@ -95,7 +95,7 @@ another DaemonSet, or via another workload resource such as ReplicaSet. Otherwi
Kubernetes will not stop you from doing this. One case where you might want to do this is manually
create a Pod with a different value on a node for testing.
### Running Pods on Only Some Nodes
### Running Pods on select Nodes
If you specify a `.spec.template.spec.nodeSelector`, then the DaemonSet controller will
create Pods on nodes which match that [node
@@ -103,7 +103,7 @@ selector](/docs/concepts/scheduling-eviction/assign-pod-node/). Likewise if you
then DaemonSet controller will create Pods on nodes which match that [node affinity](/docs/concepts/scheduling-eviction/assign-pod-node/).
If you do not specify either, then the DaemonSet controller will create Pods on all nodes.
## How Daemon Pods are Scheduled
## How Daemon Pods are scheduled
### Scheduled by default scheduler
@@ -144,7 +144,6 @@ In addition, `node.kubernetes.io/unschedulable:NoSchedule` toleration is added
automatically to DaemonSet Pods. The default scheduler ignores
`unschedulable` Nodes when scheduling DaemonSet Pods.
### Taints and Tolerations
Although Daemon Pods respect
@@ -152,17 +151,14 @@ Although Daemon Pods respect
the following tolerations are added to DaemonSet Pods automatically according to
the related features.
| Toleration Key | Effect | Version | Description |
| ---------------------------------------- | ---------- | ------- | ------------------------------------------------------------ |
| `node.kubernetes.io/not-ready` | NoExecute | 1.13+ | DaemonSet pods will not be evicted when there are node problems such as a network partition. |
| `node.kubernetes.io/unreachable` | NoExecute | 1.13+ | DaemonSet pods will not be evicted when there are node problems such as a network partition. |
| `node.kubernetes.io/disk-pressure` | NoSchedule | 1.8+ | |
| `node.kubernetes.io/memory-pressure` | NoSchedule | 1.8+ | |
| `node.kubernetes.io/unschedulable` | NoSchedule | 1.12+ | DaemonSet pods tolerate unschedulable attributes by default scheduler. |
| `node.kubernetes.io/network-unavailable` | NoSchedule | 1.12+ | DaemonSet pods, who uses host network, tolerate network-unavailable attributes by default scheduler. |
| Toleration Key | Effect | Version | Description |
| ---------------------------------------- | ---------- | ------- | ----------- |
| `node.kubernetes.io/not-ready` | NoExecute | 1.13+ | DaemonSet pods will not be evicted when there are node problems such as a network partition. |
| `node.kubernetes.io/unreachable` | NoExecute | 1.13+ | DaemonSet pods will not be evicted when there are node problems such as a network partition. |
| `node.kubernetes.io/disk-pressure` | NoSchedule | 1.8+ | |
| `node.kubernetes.io/memory-pressure` | NoSchedule | 1.8+ | |
| `node.kubernetes.io/unschedulable` | NoSchedule | 1.12+ | DaemonSet pods tolerate unschedulable attributes by default scheduler. |
| `node.kubernetes.io/network-unavailable` | NoSchedule | 1.12+ | DaemonSet pods, who uses host network, tolerate network-unavailable attributes by default scheduler. |
## Communicating with Daemon Pods
@@ -195,7 +191,7 @@ You can [perform a rolling update](/docs/tasks/manage-daemon/update-daemon-set/)
## Alternatives to DaemonSet
### Init Scripts
### Init scripts
It is certainly possible to run daemon processes by directly starting them on a node (e.g. using
`init`, `upstartd`, or `systemd`). This is perfectly fine. However, there are several advantages to
@@ -233,4 +229,4 @@ number of replicas and rolling out updates are more important than controlling e
the Pod runs on. Use a DaemonSet when it is important that a copy of a Pod always run on
all or certain hosts, and when it needs to start before other Pods.
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Kubernetes progressively rolls out changes to your application or its configuration, while monitoring application health to ensure it doesn't kill all your instances at the same time. If something goes wrong, Kubernetes will rollback the change for you. Take advantage of a growing ecosystem of deployment solutions.
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A _Deployment_ provides declarative updates for [Pods](/docs/concepts/workloads/pods/pod/) and
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@@ -22,10 +22,10 @@ You describe a _desired state_ in a Deployment, and the Deployment {{< glossary_
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## Use Case
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## Owners and dependents
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## Running an example Job
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There are three main types of task suitable to run as a Job:
1. Non-parallel Jobs
- normally, only one Pod is started, unless the Pod fails.
- the Job is complete as soon as its Pod terminates successfully.
- normally, only one Pod is started, unless the Pod fails.
- the Job is complete as soon as its Pod terminates successfully.
1. Parallel Jobs with a *fixed completion count*:
- specify a non-zero positive value for `.spec.completions`.
- the Job represents the overall task, and is complete when there is one successful Pod for each value in the range 1 to `.spec.completions`.
- **not implemented yet:** Each Pod is passed a different index in the range 1 to `.spec.completions`.
- specify a non-zero positive value for `.spec.completions`.
- the Job represents the overall task, and is complete when there is one successful Pod for each value in the range 1 to `.spec.completions`.
- **not implemented yet:** Each Pod is passed a different index in the range 1 to `.spec.completions`.
1. Parallel Jobs with a *work queue*:
- do not specify `.spec.completions`, default to `.spec.parallelism`.
- the Pods must coordinate amongst themselves or an external service to determine what each should work on. For example, a Pod might fetch a batch of up to N items from the work queue.
- each Pod is independently capable of determining whether or not all its peers are done, and thus that the entire Job is done.
- when _any_ Pod from the Job terminates with success, no new Pods are created.
- once at least one Pod has terminated with success and all Pods are terminated, then the Job is completed with success.
- once any Pod has exited with success, no other Pod should still be doing any work for this task or writing any output. They should all be in the process of exiting.
- do not specify `.spec.completions`, default to `.spec.parallelism`.
- the Pods must coordinate amongst themselves or an external service to determine what each should work on. For example, a Pod might fetch a batch of up to N items from the work queue.
- each Pod is independently capable of determining whether or not all its peers are done, and thus that the entire Job is done.
- when _any_ Pod from the Job terminates with success, no new Pods are created.
- once at least one Pod has terminated with success and all Pods are terminated, then the Job is completed with success.
- once any Pod has exited with success, no other Pod should still be doing any work for this task or writing any output. They should all be in the process of exiting.
For a _non-parallel_ Job, you can leave both `.spec.completions` and `.spec.parallelism` unset. When both are
unset, both are defaulted to 1.
@@ -478,4 +478,4 @@ object, but maintains complete control over what Pods are created and how work i
You can use a [`CronJob`](/docs/concepts/workloads/controllers/cron-jobs/) to create a Job that will run at specified times/dates, similar to the Unix tool `cron`.
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- bprashanth
- madhusudancs
title: ReplicaSet
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used to guarantee the availability of a specified number of identical Pods.
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## How a ReplicaSet works
@@ -366,4 +366,4 @@ The two serve the same purpose, and behave similarly, except that a ReplicationC
selector requirements as described in the [labels user guide](/docs/concepts/overview/working-with-objects/labels/#label-selectors).
As such, ReplicaSets are preferred over ReplicationControllers
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description: >
Restarts containers that fail, replaces and reschedules containers when nodes die, kills containers that don't respond to your user-defined health check, and doesn't advertise them to clients until they are ready to serve.
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{{< note >}}
A [`Deployment`](/docs/concepts/workloads/controllers/deployment/) that configures a [`ReplicaSet`](/docs/concepts/workloads/controllers/replicaset/) is now the recommended way to set up replication.
@@ -23,10 +23,10 @@ A _ReplicationController_ ensures that a specified number of pod replicas are ru
time. In other words, a ReplicationController makes sure that a pod or a homogeneous set of pods is
always up and available.
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## How a ReplicationController Works
@@ -285,4 +285,4 @@ safe to terminate when the machine is otherwise ready to be rebooted/shutdown.
Read [Run Stateless AP Replication Controller](/docs/tutorials/stateless-application/run-stateless-ap-replication-controller/).
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- kow3ns
- smarterclayton
title: StatefulSets
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StatefulSet is the workload API object used to manage stateful applications.
{{< glossary_definition term_id="statefulset" length="all" >}}
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## Using StatefulSets
@@ -270,12 +270,13 @@ After reverting the template, you must also delete any Pods that StatefulSet had
already attempted to run with the bad configuration.
StatefulSet will then begin to recreate the Pods using the reverted template.
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* Follow an example of [deploying a stateful application](/docs/tutorials/stateful-application/basic-stateful-set/).
* Follow an example of [deploying Cassandra with Stateful Sets](/docs/tutorials/stateful-application/cassandra/).
* Follow an example of [running a replicated stateful application](/docs/tasks/run-application/run-replicated-stateful-application/).
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reviewers:
- janetkuo
title: TTL Controller for Finished Resources
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{{< feature-state for_k8s_version="v1.12" state="alpha" >}}
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`TTLAfterFinished`.
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## TTL Controller
@@ -78,12 +78,13 @@ In Kubernetes, it's required to run NTP on all nodes
to avoid time skew. Clocks aren't always correct, but the difference should be
very small. Please be aware of this risk when setting a non-zero TTL.
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[Clean up Jobs automatically](/docs/concepts/workloads/controllers/jobs-run-to-completion/#clean-up-finished-jobs-automatically)
[Design doc](https://github.com/kubernetes/enhancements/blob/master/keps/sig-apps/0026-ttl-after-finish.md)
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- foxish
- davidopp
title: Disruptions
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This guide is for application owners who want to build
highly available applications, and thus need to understand
what types of Disruptions can happen to Pods.
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It is also for Cluster Administrators who want to perform automated
cluster actions, like upgrading and autoscaling clusters.
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## Voluntary and Involuntary Disruptions
@@ -262,13 +262,14 @@ the nodes in your cluster, such as a node or system software upgrade, here are s
disruptions largely overlaps with work to support autoscaling and tolerating
involuntary disruptions.
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* Follow steps to protect your application by [configuring a Pod Disruption Budget](/docs/tasks/run-application/configure-pdb/).
* Learn more about [draining nodes](/docs/tasks/administer-cluster/safely-drain-node/)
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- verb
- yujuhong
title: Ephemeral Containers
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{{< feature-state state="alpha" for_k8s_version="v1.16" >}}
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significantly in the future or be removed entirely.
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## Understanding ephemeral containers
@@ -192,4 +192,4 @@ example:
kubectl attach -it example-pod -c debugger
```
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- erictune
title: Init Containers
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This page provides an overview of init containers: specialized containers that run
before app containers in a {{< glossary_tooltip text="Pod" term_id="pod" >}}.
Init containers can contain utilities or setup scripts not present in an app image.
You can specify init containers in the Pod specification alongside the `containers`
array (which describes app containers).
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## Understanding init containers
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forcing a restart, and the init container completion record has been lost due
to garbage collection.
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* Read about [creating a Pod that has an init container](/docs/tasks/configure-pod-container/configure-pod-initialization/#create-a-pod-that-has-an-init-container)
* Learn how to [debug init containers](/docs/tasks/debug-application-cluster/debug-init-containers/)
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title: Pod Lifecycle
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{{< comment >}}Updated: 4/14/2015{{< /comment >}}
{{< comment >}}Edited and moved to Concepts section: 2/2/17{{< /comment >}}
This page describes the lifecycle of a Pod.
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## Pod phase
@@ -216,7 +216,7 @@ a list of additional conditions that the kubelet evaluates for Pod readiness.
Readiness gates are determined by the current state of `status.condition`
fields for the Pod. If Kubernetes cannot find such a
condition in the `status.conditions` field of a Pod, the status of the condition
is defaulted to "`False`". Below is an example:
is defaulted to "`False`".
Here is an example:
@@ -390,10 +390,11 @@ spec:
* Node controller sets Pod `phase` to Failed.
* If running under a controller, Pod is recreated elsewhere.
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* Get hands-on experience
[attaching handlers to Container lifecycle events](/docs/tasks/configure-pod-container/attach-handler-lifecycle-event/).
@@ -403,7 +404,7 @@ spec:
* Learn more about [Container lifecycle hooks](/docs/concepts/containers/container-lifecycle-hooks/).
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- erictune
title: Pod Overview
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This page provides an overview of `Pod`, the smallest deployable object in the Kubernetes object model.
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## Understanding Pods
A *Pod* is the basic execution unit of a Kubernetes application--the smallest and simplest unit in the Kubernetes object model that you create or deploy. A Pod represents processes running on your {{< glossary_tooltip term_id="cluster" text="cluster" >}}.
@@ -111,12 +111,13 @@ For example, a Deployment controller ensures that the running Pods match the cur
On Nodes, the {{< glossary_tooltip term_id="kubelet" text="kubelet" >}} does not directly observe or manage any of the details around pod templates and updates; those details are abstracted away. That abstraction and separation of concerns simplifies system semantics, and makes it feasible to extend the cluster's behavior without changing existing code.
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* Learn more about [Pods](/docs/concepts/workloads/pods/pod/)
* [The Distributed System Toolkit: Patterns for Composite Containers](https://kubernetes.io/blog/2015/06/the-distributed-system-toolkit-patterns) explains common layouts for Pods with more than one container
* Learn more about Pod behavior:
* [Pod Termination](/docs/concepts/workloads/pods/pod/#termination-of-pods)
* [Pod Lifecycle](/docs/concepts/workloads/pods/pod-lifecycle/)
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title: Pod Topology Spread Constraints
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You can use _topology spread constraints_ to control how {{< glossary_tooltip text="Pods" term_id="Pod" >}} are spread across your cluster among failure-domains such as regions, zones, nodes, and other user-defined topology domains. This can help to achieve high availability as well as efficient resource utilization.
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## Prerequisites
@@ -236,8 +236,7 @@ scheduled - more packed or more scattered.
The "EvenPodsSpread" feature provides flexible options to distribute Pods evenly across different
topology domains - to achieve high availability or cost-saving. This can also help on rolling update
workloads and scaling out replicas smoothly.
See [Motivation](https://github.com/kubernetes/enhancements/blob/master/keps/sig-scheduling/20190221-pod-topology-spread.md#motivation) for more details.
workloads and scaling out replicas smoothly. See [Motivation](https://github.com/kubernetes/enhancements/tree/master/keps/sig-scheduling/895-pod-topology-spread#motivation) for more details.
## Known Limitations
@@ -246,4 +245,4 @@ As of 1.18, at which this feature is Beta, there are some known limitations:
- Scaling down a Deployment may result in imbalanced Pods distribution.
- Pods matched on tainted nodes are respected. See [Issue 80921](https://github.com/kubernetes/kubernetes/issues/80921)
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title: Pods
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_Pods_ are the smallest deployable units of computing that can be created and
managed in Kubernetes.
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## What is a Pod?
@@ -206,4 +206,4 @@ describes the object in detail.
When creating the manifest for a Pod object, make sure the name specified is a valid
[DNS subdomain name](/docs/concepts/overview/working-with-objects/names#dns-subdomain-names).
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- jessfraz
title: Pod Preset
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{{< feature-state for_k8s_version="v1.6" state="alpha" >}}
This page provides an overview of PodPresets, which are objects for injecting
certain information into pods at creation time. The information can include
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## Understanding Pod presets
A PodPreset is an API resource for injecting additional runtime requirements
@@ -82,12 +82,13 @@ There may be instances where you wish for a Pod to not be altered by any Pod
Preset mutations. In these cases, you can add an annotation in the Pod Spec
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See [Injecting data into a Pod using PodPreset](/docs/tasks/inject-data-application/podpreset/)
For more information about the background, see the [design proposal for PodPreset](https://git.k8s.io/community/contributors/design-proposals/service-catalog/pod-preset.md).
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linktitle: Contribute
main_menu: true
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title: Start contributing
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This website is maintained by [Kubernetes SIG Docs](/docs/contribute/#get-involved-with-sig-docs).
@@ -23,9 +23,9 @@ Kubernetes documentation contributors:
Kubernetes documentation welcomes improvements from all contributors, new and experienced!
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## Getting started
@@ -48,7 +48,7 @@ roles and permissions.
- [Open a pull request using GitHub](/docs/contribute/new-content/new-content/#changes-using-github) to existing documentation and learn more about filing issues in GitHub.
- [Review pull requests](/docs/contribute/review/reviewing-prs/) from other Kubernetes community members for accuracy and language.
- Read the Kubernetes [content](/docs/contribute/style/content-guide/) and [style guides](/docs/contribute/style/style-guide/) so you can leave informed comments.
- Learn how to [use page templates](/docs/contribute/style/page-templates/) and [Hugo shortcodes](/docs/contribute/style/hugo-shortcodes/) to make bigger changes.
- Learn about [page content types](/docs/contribute/style/page-content-types/) and [Hugo shortcodes](/docs/contribute/style/hugo-shortcodes/).
## Next steps
@@ -75,4 +75,4 @@ SIG Docs communicates with different methods:
- Read the [contributor cheatsheet](https://github.com/kubernetes/community/tree/master/contributors/guide/contributor-cheatsheet) to get involved with Kubernetes feature development.
- Submit a [blog post or case study](/docs/contribute/new-content/blogs-case-studies/).
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This page assumes that you understand how to
[contribute to new content](/docs/contribute/new-content/overview) and
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to learn about more ways to contribute. You need to use the Git command line
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## Be the PR Wrangler for a week
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The video uploads automatically to YouTube.
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This page shows how to contribute to the upstream `kubernetes/kubernetes` project.
You can fix bugs found in the Kubernetes API documentation or the content of
@@ -16,9 +16,10 @@ API or the `kube-*` components from the upstream code, see the following instruc
- [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
- [Generating Reference Documentation for the Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/)
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- You need to have these tools installed:
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For more information, see [Creating a Pull Request](https://help.github.com/articles/creating-a-pull-request/)
and [GitHub Standard Fork & Pull Request Workflow](https://gist.github.com/Chaser324/ce0505fbed06b947d962).
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## The big picture
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You are now ready to follow the [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/) guide to generate the
[published Kubernetes API reference documentation](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/).
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* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
* [Generating Reference Docs for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/)
* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
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