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Running Kubernetes on AWS EC2

• Prerequisites
• Cluster turnup
  • Supported procedure: get-kube
  • Alternatives
• Getting started with your cluster
  • Command line administration tool: kubectl
  • Examples
• Tearing down the cluster
• Support Level
• Further reading

Prerequisites

1. You need an AWS account. Visit http://aws.amazon.com to get started
2. Install and configure AWS Command Line Interface
3. You need an AWS instance profile and role with EC2 full access.

NOTE: This script use the ‘default’ AWS profile by default. You may explicitly set AWS profile to use using the AWS_DEFAULT_PROFILE environment variable:

export AWS_DEFAULT_PROFILE=myawsprofile

Cluster turnup

Supported procedure: get-kube

#Using wget
export KUBERNETES_PROVIDER=aws; wget -q -O - https://get.k8s.io | bash
#Using cURL
export KUBERNETES_PROVIDER=aws; curl -sS https://get.k8s.io | bash

NOTE: This script calls cluster/kube-up.sh which in turn calls cluster/aws/util.sh using cluster/aws/config-default.sh.

This process takes about 5 to 10 minutes. Once the cluster is up, the IP addresses of your master and node(s) will be printed, as well as information about the default services running in the cluster (monitoring, logging, dns). User credentials and security tokens are written in ~/.kube/config, they will be necessary to use the CLI or the HTTP Basic Auth.

By default, the script will provision a new VPC and a 4 node k8s cluster in us-west-2a (Oregon) with EC2 instances running on Ubuntu. You can override the variables defined in config-default.sh to change this behavior as follows:

export KUBE_AWS_ZONE=eu-west-1c
export NUM_NODES=2
export MASTER_SIZE=m3.medium
export NODE_SIZE=m3.medium
export AWS_S3_REGION=eu-west-1
export AWS_S3_BUCKET=mycompany-kubernetes-artifacts
export INSTANCE_PREFIX=k8s
...

If you don’t specify master and minion sizes, the scripts will attempt to guess the correct size of the master and worker nodes based on ${NUM_NODES}. In version 1.2 these default are:

• For the master, for clusters of less than 150 nodes it will use an m3.medium, for clusters of greater than 150 nodes it will use an m3.large.

• For worker nodes, for clusters less than 50 nodes it will use a t2.micro, for clusters between 50 and 150 nodes it will use a t2.small and for clusters with greater than 150 nodes it will use a t2.medium.

WARNING: beware that t2 instances receive a limited number of CPU credits per hour and might not be suitable for clusters where the CPU is used consistently. As a rough estimation, consider 15 pods/node the absolute limit a t2.large instance can handle before it starts exhausting its CPU credits steadily, although this number depends heavily on the usage.

In prior versions of Kubernetes, we defaulted the master node to a t2-class instance, but found that this sometimes gave hard-to-diagnose problems when the master ran out of memory or CPU credits. If you are running a test cluster and want to save money, you can specify export MASTER_SIZE=t2.micro but if your master pauses do check the CPU credits in the AWS console.

For production usage, we recommend at least export MASTER_SIZE=m3.medium and export NODE_SIZE=m3.medium. And once you get above a handful of nodes, be aware that one m3.large instance has more storage than two m3.medium instances, for the same price.

We generally recommend the m3 instances over the m4 instances, because the m3 instances include local instance storage. Historically local instance storage has been more reliable than AWS EBS, and performance should be more consistent. The ephemeral nature of this storage is a match for ephemeral container workloads also!

If you use an m4 instance, or another instance type which does not have local instance storage, you may want to increase the NODE_ROOT_DISK_SIZE value, although the default value of 32 is probably sufficient for the smaller instance types in the m4 family.

The script will also try to create or reuse a keypair called “kubernetes”, and IAM profiles called “kubernetes-master” and “kubernetes-minion”. If these already exist, make sure you want them to be used here.

NOTE: If using an existing keypair named “kubernetes” then you must set the AWS_SSH_KEY key to point to your private key.

Alternatives

CoreOS maintains a CLI tool, kube-aws that will create and manage a Kubernetes cluster based on CoreOS, using AWS tools: EC2, CloudFormation and Autoscaling.

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.

Next, add the appropriate binary folder to your PATH to access kubectl:

# OS X
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

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

Examples

See a simple nginx example to try out your new cluster.

The “Guestbook” application is another popular example to get started with Kubernetes: guestbook example

For more complete applications, please look in the examples directory

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:

cluster/kube-down.sh

Support Level

For support level information on all solutions, see the Table of solutions chart.

Further reading

Please see the Kubernetes docs for more details on administering and using a Kubernetes cluster.