Linux containers are a relatively new abstraction framework with exciting implications for Continuous Integration and Continuous Delivery patterns. They allow appropriately designed applications to be tested, validated, and deployed in an immutable fashion at much greater speed than with traditional virtual machines. When it comes to production use however, an orchestration framework is desirable to maintain a minimum number of container workers, load balance between them, schedule jobs and the like. An extremely popular method of doing this is to use AWS EC2 Container Service (ECS) with the Amazon Linux distribution, however if you find yourself making the “how do we run containers” decision then it pays to explore other technology stacks as well.
In this demo, we’ll launch a Kubernetes cluster of CoreOS on AWS. Kubernetes is a container orchestration platform that utilizes Docker to provision, run, and monitor containers on Linux. It is developed primarily by Google, and is similar to container orchestration projects they run internally. CoreOS is a lightweight Linux distribution optimized for container hosting. Related projects are Docker Inc’s “Docker Datacenter,” RedHat’s Atomic, and RancherOS.
1) Download the kubernetes package. Releases are at . This demo assumes version 1.1.8.
2) Download the coreos-kubernetes package. Releases are at . This demo assumes version 0.4.1.
3) Extract both. core-kubernetes provides a kube-aws binary used for provisioning a kube cluster in AWS (using CloudFormation), while the kubernetes package is used for its kubectl binary
[code language=”bash”] tar xzf kubernetes.tar.gz
tar xzf kube-aws-PLATFORM-ARCH.tar.gz (kube-aws-darwin-amd64.tar.gz for Macs, for instance)
[/code] 4) Setup your AWS credentials and profiles
5) Generate a KMS key to use for the cluster (change region from us-west-1 if desired, but you will need to change it everywhere). Make a note of the ARN of the generated key, it will be used in the cluster.yaml later
[code language=”bash”]aws kms –region=us-west-1 create-key –description="kube-aws assets"[/code] 5) Get a sample cluster.yaml . This is a configuration file later used for generating the AWS CloudFormation scripts and associated resources used to launch the cluster.
[code language=”bash”]mkdir my-cluster; cd my-cluster
~/darwin-amd64/kube-aws init –cluster-name=YOURCLUSTERNAME \
–external-dns-name=FQDNFORCLUSTER –region=us-west-1 \
–availability-zone=us-west-1c –key-name=VALIDEC2KEYNAME \
–kms-key-arn="arn:aws:kms:us-west-1:ARN:OF:PREVIOUSLY:GENERATED:KMS:KEY"[/code] 6) Modify the cluster.yaml with appropriate settings. “externalDNSName” wants a FQDN that will either be configured automatically if you provide a Route53 zone id for “hostedZoneId” or that you will configure AFTER provisioning has completed. This becomes the kube controller endpoint used by the Kubernetes control tooling.
Note that a new VPC is created for the Kubernetes cluster unless you configure it to use an existing VPC. You specify a region in the cluster.yaml, and if you don’t specify an Availability Zone then the “A” AZ will be used by default.
7) Render the CFN templates, validate, then launch the cluster
[code language=”bash”] ~/darwin-amd64/kube-aws render
~/darwin-amd64/kube-aws validate
~/darwin-amd64/kube-aws up
This will setup a short-term Certificate Authority (365 days) and SSL certs (90 days) for communication and then launch a cluster into CloudFormation. It will also store data about the cluster for use with kubectl
8) After the cluster has come up, an EIP will be output. Assign this EIP to the FQDN you used for externalDNSName in cluster.yaml if you did not allow kube-aws to configure this automatically via Route53. This is important, as it’s how the tools will try to control the cluster.
9) You can then start playing with the cluster. My sample session:
[code language=”bash”]# Display active Kubernetes nodes
~/kubernetes/platforms/darwin/amd64/kubectl –kubeconfig=kubeconfig get nodes
NAME STATUS AGE Ready,SchedulingDisabled 19m Ready 19m Ready 19m
# Display name and EIP of the cluster
~/darwin-amd64/kube-aws status
Controller IP: a.b.c.d
# Launch the "nginx" Docker image as container instance "my-nginx"
# 2 replicas, wire port 80
~/kubernetes/platforms/darwin/amd64/kubectl –kubeconfig=kubeconfig run my-nginx –image=nginx –replicas=2 –port=80
deployment "my-nginx" created
# Show process list
~/kubernetes/platforms/darwin/amd64/kubectl –kubeconfig=kubeconfig get po
my-nginx-2494149703-2dhrr 1/1 Running 0 2m
my-nginx-2494149703-joqb5 1/1 Running 0 2m
# Expose port 80 on the my-nginx instances via an Elastic Load Balancer
~/kubernetes/platforms/darwin/amd64/kubectl –kubeconfig=kubeconfig expose deployment my-nginx –port=80 –type=LoadBalancer
service "my-nginx" exposed
# Show result for the service
~/kubernetes/platforms/darwin/amd64/kubectl –kubeconfig=kubeconfig get svc my-nginx -o wide
my-nginx 10.x.0.y 80/TCP 3m run=my-nginx
# Describe the my-nginx service. This will show the CNAME of the ELB that
# was created and which exposes port 80
~/kubernetes/platforms/darwin/amd64/kubectl –kubeconfig=kubeconfig describe service my-nginx
Name: my-nginx
Namespace: default
Labels: run=my-nginx
Selector: run=my-nginx
Type: LoadBalancer
IP: 10.x.0.y
LoadBalancer Ingress:
Port: <unset> 80/TCP
NodePort: <unset> 31414/TCP
Endpoints: 10.a.b.c:80,10.d.e.f:80
Session Affinity: None
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
——— ——– —– —- ————- ——– —— ——-
4m 4m 1 {service-controller } Normal CreatingLoadBalancer Creating load balancer
4m 4m 1 {service-controller } Normal CreatedLoadBalancer Created load balancer[/code] Thus we have created a three node Kubernetes cluster (one controller, two workers) running two copies of the nginx container. We then setup an ELB to balance traffic between the instances.
Kubernetes certainly has operational complexity to trade off against features and robustness. There are a lot of moving parts to maintain, and at Stelligent we tend to recommend AWS ECS for situations in which it will suffice.

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