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clean up turnkey cloud solutions

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Karen Bradshaw
2020-10-28 11:19:25 -04:00
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content/en/docs/setup/production-environment/container-runtimes.md
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title: Container runtimes
content_type: concept
weight: 10
weight: 20
---
<!-- overview -->
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title: Turnkey Cloud Solutions
weight: 30
---
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- colemickens
- brendandburns
title: Running Kubernetes on Alibaba Cloud
---
## Alibaba Cloud Container Service
The [Alibaba Cloud Container Service](https://www.alibabacloud.com/product/container-service) lets you run and manage Docker applications on a cluster of either Alibaba Cloud ECS instances or in a Serverless fashion. It supports the popular open source container orchestrators: Docker Swarm and Kubernetes.
To simplify cluster deployment and management, use [Kubernetes Support for Alibaba Cloud Container Service](https://www.alibabacloud.com/product/kubernetes). You can get started quickly by following the [Kubernetes walk-through](https://www.alibabacloud.com/help/doc-detail/86737.htm), and there are some [tutorials for Kubernetes Support on Alibaba Cloud](https://yq.aliyun.com/teams/11/type_blog-cid_200-page_1) in Chinese.
To use custom binaries or open source Kubernetes, follow the instructions below.
## Custom Deployments
The source code for [Kubernetes with Alibaba Cloud provider implementation](https://github.com/AliyunContainerService/kubernetes) is open source and available on GitHub.
For more information, see "[Quick deployment of Kubernetes - VPC environment on Alibaba Cloud](https://www.alibabacloud.com/forum/read-830)" in English.
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reviewers:
- justinsb
- clove
title: Running Kubernetes on AWS EC2
content_type: task
---
<!-- overview -->
This page describes how to install a Kubernetes cluster on AWS.
## {{% heading "prerequisites" %}}
To create a Kubernetes cluster on AWS, you will need an Access Key ID and a Secret Access Key from AWS.
### Supported Production Grade Tools
* [conjure-up](https://docs.conjure-up.io/stable/en/cni/k8s-and-aws) is an open-source installer for Kubernetes that creates Kubernetes clusters with native AWS integrations on Ubuntu.
* [Kubernetes Operations](https://github.com/kubernetes/kops) - Production Grade K8s Installation, Upgrades, and Management. Supports running Debian, Ubuntu, CentOS, and RHEL in AWS.
* [kube-aws](https://github.com/kubernetes-retired/kube-aws), creates and manages Kubernetes clusters with [Flatcar Linux](https://www.flatcar-linux.org/) nodes, using AWS tools: EC2, CloudFormation and Autoscaling.
* [KubeOne](https://github.com/kubermatic/kubeone) is an open source cluster lifecycle management tool that creates, upgrades and manages Kubernetes Highly-Available clusters.
<!-- steps -->
## Getting started with your cluster
### Command line administration tool: kubectl
The cluster startup script will leave you with a `kubernetes` directory on your workstation.
Alternately, you can download the latest Kubernetes release from [this page](https://github.com/kubernetes/kubernetes/releases).
Next, add the appropriate binary folder to your `PATH` to access kubectl:
```shell
# macOS
export PATH=<path/to/kubernetes-directory>/platforms/darwin/amd64:$PATH
# Linux
export PATH=<path/to/kubernetes-directory>/platforms/linux/amd64:$PATH
```
An up-to-date documentation page for this tool is available here: [kubectl manual](/docs/reference/kubectl/kubectl/)
By default, `kubectl` will use the `kubeconfig` file generated during the cluster startup for authenticating against the API.
For more information, please read [kubeconfig files](/docs/tasks/access-application-cluster/configure-access-multiple-clusters/)
### Examples
See [a simple nginx example](/docs/tasks/run-application/run-stateless-application-deployment/) to try out your new cluster.
The "Guestbook" application is another popular example to get started with Kubernetes: [guestbook example](https://github.com/kubernetes/examples/tree/{{< param "githubbranch" >}}/guestbook/)
For more complete applications, please look in the [examples directory](https://github.com/kubernetes/examples/tree/{{< param "githubbranch" >}}/)
## Scaling the cluster
Adding and removing nodes through `kubectl` is not supported. You can still scale the amount of nodes manually through adjustments of the 'Desired' and 'Max' properties within the
[Auto Scaling Group](https://docs.aws.amazon.com/autoscaling/latest/userguide/as-manual-scaling.html), which was created during the installation.
## Tearing down the cluster
Make sure the environment variables you used to provision your cluster are still exported, then call the following script inside the
`kubernetes` directory:
```shell
cluster/kube-down.sh
```
## Support Level
IaaS Provider | Config. Mgmt | OS | Networking | Docs | Conforms | Support Level
-------------------- | ------------ | ------------- | ---------- | --------------------------------------------- | ---------| ----------------------------
AWS | kops | Debian | k8s (VPC) | [docs](https://github.com/kubernetes/kops) | | Community ([@justinsb](https://github.com/justinsb))
AWS | CoreOS | CoreOS | flannel | - | | Community
AWS | Juju | Ubuntu | flannel, calico, canal | - | 100% | Commercial, Community
AWS | KubeOne | Ubuntu, CoreOS, CentOS | canal, weavenet | [docs](https://github.com/kubermatic/kubeone) | 100% | Commercial, Community
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title: Running Kubernetes on Azure
---
## Azure Kubernetes Service (AKS)
The [Azure Kubernetes Service](https://azure.microsoft.com/en-us/services/kubernetes-service/) offers simple
deployments for Kubernetes clusters.
For an example of deploying a Kubernetes cluster onto Azure via the Azure Kubernetes Service:
**[Microsoft Azure Kubernetes Service](https://docs.microsoft.com/en-us/azure/aks/intro-kubernetes)**
## Custom Deployments: AKS-Engine
The core of the Azure Kubernetes Service is **open source** and available on GitHub for the community
to use and contribute to: **[AKS-Engine](https://github.com/Azure/aks-engine)**. The legacy [ACS-Engine](https://github.com/Azure/acs-engine) codebase has been deprecated in favor of AKS-engine.
AKS-Engine is a good choice if you need to make customizations to the deployment beyond what the Azure Kubernetes
Service officially supports. These customizations include deploying into existing virtual networks, utilizing multiple
agent pools, and more. Some community contributions to AKS-Engine may even become features of the Azure Kubernetes Service.
The input to AKS-Engine is an apimodel JSON file describing the Kubernetes cluster. It is similar to the Azure Resource Manager (ARM) template syntax used to deploy a cluster directly with the Azure Kubernetes Service. The resulting output is an ARM template that can be checked into source control and used to deploy Kubernetes clusters to Azure.
You can get started by following the **[AKS-Engine Kubernetes Tutorial](https://github.com/Azure/aks-engine/blob/master/docs/tutorials/README.md)**.
## CoreOS Tectonic for Azure
The CoreOS Tectonic Installer for Azure is **open source** and available on GitHub for the community to use and contribute to: **[Tectonic Installer](https://github.com/coreos/tectonic-installer)**.
Tectonic Installer is a good choice when you need to make cluster customizations as it is built on [Hashicorp's Terraform](https://www.terraform.io/docs/providers/azurerm/) Azure Resource Manager (ARM) provider. This enables users to customize or integrate using familiar Terraform tooling.
You can get started using the [Tectonic Installer for Azure Guide](https://coreos.com/tectonic/docs/latest/install/azure/azure-terraform.html).
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- jbeda
- mikedanese
- thockin
title: Running Kubernetes on Google Compute Engine
content_type: task
---
<!-- overview -->
The example below creates a Kubernetes cluster with 3 worker node Virtual Machines and a master Virtual Machine (i.e. 4 VMs in your cluster). This cluster is set up and controlled from your workstation (or wherever you find convenient).
## {{% heading "prerequisites" %}}
If you want a simplified getting started experience and GUI for managing clusters, please consider trying [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine/) for hosted cluster installation and management.
For an easy way to experiment with the Kubernetes development environment, click the button below
to open a Google Cloud Shell with an auto-cloned copy of the Kubernetes source repo.
[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.png)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/kubernetes/kubernetes&page=editor&open_in_editor=README.md)
If you want to use custom binaries or pure open source Kubernetes, please continue with the instructions below.
### Prerequisites
1. You need a Google Cloud Platform account with billing enabled. Visit the [Google Developers Console](https://console.cloud.google.com) for more details.
1. Install `gcloud` as necessary. `gcloud` can be installed as a part of the [Google Cloud SDK](https://cloud.google.com/sdk/).
1. Enable the [Compute Engine Instance Group Manager API](https://console.developers.google.com/apis/api/replicapool.googleapis.com/overview) in the [Google Cloud developers console](https://console.developers.google.com/apis/library).
1. Make sure that gcloud is set to use the Google Cloud Platform project you want. You can check the current project using `gcloud config list project` and change it via `gcloud config set project <project-id>`.
1. Make sure you have credentials for GCloud by running `gcloud auth login`.
1. (Optional) In order to make API calls against GCE, you must also run `gcloud auth application-default login`.
1. Make sure you can start up a GCE VM from the command line. At least make sure you can do the [Create an instance](https://cloud.google.com/compute/docs/instances/#startinstancegcloud) part of the GCE Quickstart.
1. Make sure you can SSH into the VM without interactive prompts. See the [Log in to the instance](https://cloud.google.com/compute/docs/instances/#sshing) part of the GCE Quickstart.
<!-- steps -->
## Starting a cluster
You can install a client and start a cluster with either one of these commands (we list both in case only one is installed on your machine):
```shell
curl -sS https://get.k8s.io | bash
```
or
```shell
wget -q -O - https://get.k8s.io | bash
```
Once this command completes, you will have a master VM and four worker VMs, running as a Kubernetes cluster.
By default, some containers will already be running on your cluster. Containers like `fluentd` provide [logging](/docs/concepts/cluster-administration/logging/), while `heapster` provides [monitoring](https://releases.k8s.io/master/cluster/addons/cluster-monitoring/README.md) services.
The script run by the commands above creates a cluster with the name/prefix "kubernetes". It defines one specific cluster config, so you can't run it more than once.
Alternately, you can download and install the latest Kubernetes release from [this page](https://github.com/kubernetes/kubernetes/releases), then run the `<kubernetes>/cluster/kube-up.sh` script to start the cluster:
```shell
cd kubernetes
cluster/kube-up.sh
```
If you want more than one cluster running in your project, want to use a different name, or want a different number of worker nodes, see the `<kubernetes>/cluster/gce/config-default.sh` file for more fine-grained configuration before you start up your cluster.
If you run into trouble, please see the section on [troubleshooting](/docs/setup/production-environment/turnkey/gce/#troubleshooting), post to the
[Kubernetes Forum](https://discuss.kubernetes.io), or come ask questions on `#gke` Slack channel.
The next few steps will show you:
1. How to set up the command line client on your workstation to manage the cluster
1. Examples of how to use the cluster
1. How to delete the cluster
1. How to start clusters with non-default options (like larger clusters)
## Installing the Kubernetes command line tools on your workstation
The cluster startup script will leave you with a running cluster and a `kubernetes` directory on your workstation.
The [kubectl](/docs/reference/kubectl/kubectl/) tool controls the Kubernetes cluster
manager. It lets you inspect your cluster resources, create, delete, and update
components, and much more. You will use it to look at your new cluster and bring
up example apps.
You can use `gcloud` to install the `kubectl` command-line tool on your workstation:
```shell
gcloud components install kubectl
```
{{< note >}}
The kubectl version bundled with `gcloud` may be older than the one
downloaded by the get.k8s.io install script. See [Installing kubectl](/docs/tasks/tools/install-kubectl/)
document to see how you can set up the latest `kubectl` on your workstation.
{{< /note >}}
## Getting started with your cluster
### Inspect your cluster
Once `kubectl` is in your path, you can use it to look at your cluster. E.g., running:
```shell
kubectl get --all-namespaces services
```
should show a set of [services](/docs/concepts/services-networking/service/) that look something like this:
```shell
NAMESPACE NAME TYPE CLUSTER_IP EXTERNAL_IP PORT(S) AGE
default kubernetes ClusterIP 10.0.0.1 <none> 443/TCP 1d
kube-system kube-dns ClusterIP 10.0.0.2 <none> 53/TCP,53/UDP 1d
kube-system kube-ui ClusterIP 10.0.0.3 <none> 80/TCP 1d
...
```
Similarly, you can take a look at the set of [pods](/docs/concepts/workloads/pods/) that were created during cluster startup.
You can do this via the
```shell
kubectl get --all-namespaces pods
```
command.
You'll see a list of pods that looks something like this (the name specifics will be different):
```shell
NAMESPACE NAME READY STATUS RESTARTS AGE
kube-system coredns-5f4fbb68df-mc8z8 1/1 Running 0 15m
kube-system fluentd-cloud-logging-kubernetes-minion-63uo 1/1 Running 0 14m
kube-system fluentd-cloud-logging-kubernetes-minion-c1n9 1/1 Running 0 14m
kube-system fluentd-cloud-logging-kubernetes-minion-c4og 1/1 Running 0 14m
kube-system fluentd-cloud-logging-kubernetes-minion-ngua 1/1 Running 0 14m
kube-system kube-ui-v1-curt1 1/1 Running 0 15m
kube-system monitoring-heapster-v5-ex4u3 1/1 Running 1 15m
kube-system monitoring-influx-grafana-v1-piled 2/2 Running 0 15m
```
Some of the pods may take a few seconds to start up (during this time they'll show `Pending`), but check that they all show as `Running` after a short period.
### Run some examples
Then, see [a simple nginx example](/docs/tasks/run-application/run-stateless-application-deployment/) to try out your new cluster.
For more complete applications, please look in the [examples directory](https://github.com/kubernetes/examples/tree/{{< param "githubbranch" >}}/). The [guestbook example](https://github.com/kubernetes/examples/tree/{{< param "githubbranch" >}}/guestbook/) is a good "getting started" walkthrough.
## Tearing down the cluster
To remove/delete/teardown the cluster, use the `kube-down.sh` script.
```shell
cd kubernetes
cluster/kube-down.sh
```
Likewise, the `kube-up.sh` in the same directory will bring it back up. You do not need to rerun the `curl` or `wget` command: everything needed to setup the Kubernetes cluster is now on your workstation.
## Customizing
The script above relies on Google Storage to stage the Kubernetes release. It
then will start (by default) a single master VM along with 3 worker VMs. You
can tweak some of these parameters by editing `kubernetes/cluster/gce/config-default.sh`
You can view a transcript of a successful cluster creation
[here](https://gist.github.com/satnam6502/fc689d1b46db9772adea).
## Troubleshooting
### Project settings
You need to have the Google Cloud Storage API, and the Google Cloud Storage
JSON API enabled. It is activated by default for new projects. Otherwise, it
can be done in the Google Cloud Console. See the [Google Cloud Storage JSON
API Overview](https://cloud.google.com/storage/docs/json_api/) for more
details.
Also ensure that-- as listed in the [Prerequisites section](#prerequisites)-- you've enabled the `Compute Engine Instance Group Manager API`, and can start up a GCE VM from the command line as in the [GCE Quickstart](https://cloud.google.com/compute/docs/quickstart) instructions.
### Cluster initialization hang
If the Kubernetes startup script hangs waiting for the API to be reachable, you can troubleshoot by SSHing into the master and node VMs and looking at logs such as `/var/log/startupscript.log`.
**Once you fix the issue, you should run `kube-down.sh` to cleanup** after the partial cluster creation, before running `kube-up.sh` to try again.
### SSH
If you're having trouble SSHing into your instances, ensure the GCE firewall
isn't blocking port 22 to your VMs. By default, this should work but if you
have edited firewall rules or created a new non-default network, you'll need to
expose it: `gcloud compute firewall-rules create default-ssh --network=<network-name>
--description "SSH allowed from anywhere" --allow tcp:22`
Additionally, your GCE SSH key must either have no passcode or you need to be
using `ssh-agent`.
### Networking
The instances must be able to connect to each other using their private IP. The
script uses the "default" network which should have a firewall rule called
"default-allow-internal" which allows traffic on any port on the private IPs.
If this rule is missing from the default network or if you change the network
being used in `cluster/config-default.sh` create a new rule with the following
field values:
* Source Ranges: `10.0.0.0/8`
* Allowed Protocols and Port: `tcp:1-65535;udp:1-65535;icmp`
## Support Level
IaaS Provider | Config. Mgmt | OS | Networking | Docs | Conforms | Support Level
-------------------- | ------------ | ------ | ---------- | --------------------------------------------- | ---------| ----------------------------
GCE | Saltstack | Debian | GCE | [docs](/docs/setup/production-environment/turnkey/gce/) | | Project
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title: Running Kubernetes on Multiple Clouds with IBM Cloud Private
---
IBM® Cloud Private is a turnkey cloud solution and an on-premises turnkey cloud solution. IBM Cloud Private delivers pure upstream Kubernetes with the typical management components that are required to run real enterprise workloads. These workloads include health management, log management, audit trails, and metering for tracking usage of workloads on the platform.
IBM Cloud Private is available in a community edition and a fully supported enterprise edition. The community edition is available at no charge from [Docker Hub](https://hub.docker.com/r/ibmcom/icp-inception/). The enterprise edition supports high availability topologies and includes commercial support from IBM for Kubernetes and the IBM Cloud Private management platform. If you want to try IBM Cloud Private, you can use either the hosted trial, the tutorial, or the self-guided demo. You can also try the free community edition. For details, see [Get started with IBM Cloud Private](https://www.ibm.com/cloud/private/get-started).
For more information, explore the following resources:
* [IBM Cloud Private](https://www.ibm.com/cloud/private)
* [Reference architecture for IBM Cloud Private](https://github.com/ibm-cloud-architecture/refarch-privatecloud)
* [IBM Cloud Private documentation](https://www.ibm.com/support/knowledgecenter/SSBS6K/product_welcome_cloud_private.html)
## IBM Cloud Private and Terraform
The following modules are available where you can deploy IBM Cloud Private by using Terraform:
* AWS: [Deploy IBM Cloud Private to AWS](https://github.com/ibm-cloud-architecture/terraform-icp-aws)
* Azure: [Deploy IBM Cloud Private to Azure](https://github.com/ibm-cloud-architecture/terraform-icp-azure)
* IBM Cloud: [Deploy IBM Cloud Private cluster to IBM Cloud](https://github.com/ibm-cloud-architecture/terraform-icp-ibmcloud)
* OpenStack: [Deploy IBM Cloud Private to OpenStack](https://github.com/ibm-cloud-architecture/terraform-icp-openstack)
* Terraform module: [Deploy IBM Cloud Private on any supported infrastructure vendor](https://github.com/ibm-cloud-architecture/terraform-module-icp-deploy)
* VMware: [Deploy IBM Cloud Private to VMware](https://github.com/ibm-cloud-architecture/terraform-icp-vmware)
## IBM Cloud Private on AWS
You can deploy an IBM Cloud Private cluster on Amazon Web Services (AWS) using Terraform.
IBM Cloud Private can also run on the AWS cloud platform by using Terraform. To deploy IBM Cloud Private in an AWS EC2 environment, see [Installing IBM Cloud Private on AWS](https://github.com/ibm-cloud-architecture/terraform-icp-aws).
## IBM Cloud Private on Azure
You can enable Microsoft Azure as a cloud provider for IBM Cloud Private deployment and take advantage of all the IBM Cloud Private features on the Azure public cloud. For more information, see [IBM Cloud Private on Azure](https://www.ibm.com/support/knowledgecenter/SSBS6K_3.2.0/supported_environments/azure_overview.html).
## IBM Cloud Private with Red Hat OpenShift
You can deploy IBM certified software containers that are running on IBM Cloud Private onto Red Hat OpenShift.
Integration capabilities:
* Supports Linux® 64-bit platform in offline-only installation mode
* Single-master configuration
* Integrated IBM Cloud Private cluster management console and catalog
* Integrated core platform services, such as monitoring, metering, and logging
* IBM Cloud Private uses the OpenShift image registry
For more information see, [IBM Cloud Private on OpenShift](https://www.ibm.com/support/knowledgecenter/SSBS6K_3.2.0/supported_environments/openshift/overview.html).
## IBM Cloud Private on VirtualBox
To install IBM Cloud Private to a VirtualBox environment, see [Installing IBM Cloud Private on VirtualBox](https://github.com/ibm-cloud-architecture/refarch-privatecloud-virtualbox).
## IBM Cloud Private on VMware
You can install IBM Cloud Private on VMware with either Ubuntu or RHEL images. For details, see the following projects:
* [Installing IBM Cloud Private with Ubuntu](https://github.com/ibm-cloud-architecture/refarch-privatecloud/blob/master/Installing_ICp_on_prem_ubuntu.md)
* [Installing IBM Cloud Private with Red Hat Enterprise](https://github.com/ibm-cloud-architecture/refarch-privatecloud/tree/master/icp-on-rhel)
The IBM Cloud Private Hosted service automatically deploys IBM Cloud Private Hosted on your VMware vCenter Server instances. This service brings the power of microservices and containers to your VMware environment on IBM Cloud. With this service, you can extend the same familiar VMware and IBM Cloud Private operational model and tools from on-premises into the IBM Cloud.
For more information, see [IBM Cloud Private Hosted service](https://cloud.ibm.com/docs/vmwaresolutions?topic=vmwaresolutions-icp_overview).
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title: Running Kubernetes on Tencent Kubernetes Engine
---
## Tencent Kubernetes Engine
[Tencent Cloud Tencent Kubernetes Engine (TKE)](https://intl.cloud.tencent.com/product/tke) provides native Kubernetes container management services. You can deploy and manage a Kubernetes cluster with TKE in just a few steps. For detailed directions, see [Deploy Tencent Kubernetes Engine](https://intl.cloud.tencent.com/document/product/457/11741).
TKE is a [Certified Kubernetes product](https://www.cncf.io/certification/software-conformance/).It is fully compatible with the native Kubernetes API.
## Custom Deployment
The core of Tencent Kubernetes Engine is open source and available [on GitHub](https://github.com/TencentCloud/tencentcloud-cloud-controller-manager/).
When using TKE to create a Kubernetes cluster, you can choose managed mode or independent deployment mode. In addition, you can customize the deployment as needed; for example, you can choose an existing Cloud Virtual Machine instance for cluster creation or enable Kube-proxy in IPVS mode.
## What's Next
To learn more, see the [TKE documentation](https://intl.cloud.tencent.com/document/product/457).