Say Bye to Kubectx !

I have been a great fan of kubectx and kubectl which has been a fast way to switch between clusters and namespaces until I came across Docker for Mac 18.02. With the newer Docker for Mac 18.02 RC build, it is just a matter of a “toggle”. Life has become too easy to switch between dev, QA & production environment.

[Updated(2-Feb-2018) : Docker for Mac 18.02.0 CE RC2 build now comes with Kubernetes v1.9.2 for the first time. I upgraded my macOS High Sierra to RC2 build today and it just works flawlessly. Check it out]

New to Kubernetes Namespace Vs Context ?

Generally, software development teams partition their development pipelines into discrete units. These units take various forms in a discrete layout –

          Dev  >> Testing|QA >> Staging >> Production

The resulting layouts are ideally suited to Kubernetes Namespaces. Each environment or stage in the pipeline becomes a unique namespace.

In Kubernetes terminology, Namespaces are the way to partition a single Kubernetes cluster into multiple virtual clusters. Namespaces are a logical partitioning capability that enable one Kubernetes cluster to be used by multiple users, teams of users, or a single user with multiple applications without concern for undesired interaction. Each user, team of users, or application may exist within its Namespace, isolated from every other user of the cluster and operating as if it were the sole user of the cluster.

A major benefit of applying namespaces to the development cycle is that the naming of software components (e.g. micro-services/endpoints) can be maintained without collision across the different environments. This is due to the isolation of the Kubernetes namespaces. The fact that each namespace is logically discrete allows the development teams to work within an isolated “development” namespace.

Say, you have two clusters, one for development work and one for scratch work. In the development cluster, your frontend developers work in a namespace called frontend, and your storage developers work in a namespace called storage. In your scratch cluster, developers work in the default namespace, or they create auxiliary namespaces as they see fit. Access to the development cluster requires authentication by certificate. Access to the scratch cluster requires authentication by username and password.

Shown below is an example which clearly shows a file config-demo with this content:

apiVersion: v1
kind: Config
preferences: {}

clusters:
- cluster:
  name: development
- cluster:
  name: scratch

users:
- name: developer
- name: experimenter

contexts:
- context:
  name: dev-frontend
- context:
  name: dev-storage
- context:
  name: exp-scratch

As shown above, a configuration file describes clusters, users, and contexts. Your config-demo file has the framework to describe two clusters, two users, and three contexts.

Under this blog post, I will showcase how to create 3 difference contexts – Google Cloud, Docker for Desktop & Minikube first and then how easy is it to toggle between them under Docker for Mac Platform. Let’s get started –

Pre-requisite:

• Docker For Mac 18.02 RC2 build

• Enable Kubernetes under Preference Pane

Installing Minikube

sysctl -a | grep machdep.cpu.features | grep VMX

Ajeets-MacBook-Air:~ ajeetraina$ brew update && brew install kubectl && brew cask install minikube

Ajeets-MacBook-Air:~ ajeetraina$ minikube start
Starting local Kubernetes v1.9.0 cluster...
Starting VM...
Downloading Minikube ISO
 142.22 MB / 142.22 MB [============================================] 100.00% 0s
Getting VM IP address...
Moving files into cluster...
Downloading localkube binary
 162.41 MB / 162.41 MB [============================================] 100.00% 0s
 0 B / 65 B [----------------------------------------------------------]   0.00%
 65 B / 65 B [======================================================] 100.00% 0sSetting up certs...
Connecting to cluster...
Setting up kubeconfig...
Starting cluster components...
Kubectl is now configured to use the cluster.
Loading cached images from config file.

Ajeets-MacBook-Air:~ ajeetraina$ kubectl config get-contexts
CURRENT   NAME                          CLUSTER                      AUTHINFO             NAMESPACE
         docker-for-desktop            docker-for-desktop-cluster   docker-for-desktop
         gce                                                        cluster-admin
         kubernetes-admin@kubernetes   kubernetes                   kubernetes-admin
*         minikube                      minikube                     minikube

Ajeets-MacBook-Air:testenviron ajeetraina$ docker swarm init
Swarm initialized: current node (zfxiqqjpjmwbvhm1ahjwio3s7) is now a manager.

To add a worker to this swarm, run the following command:

    docker swarm join --token SWMTKN-1-4vnxn6cbq4gtsjjvaluucncc8m71aexe11dhbm40aoxfqnr7s3-bevjmv2qpklluuhm6ufrfoas2 192.168.65.3:2377

To add a manager to this swarm, run 'docker swarm join-token manager' and follow the instructions.

Ajeets-MacBook-Air:testenviron ajeetraina$ docker node ls
ID                            HOSTNAME                STATUS              AVAILABILITY        MANAGER STATUS
zfxiqqjpjmwbvhm1ahjwio3s7 *   linuxkit-025000000001   Ready               Active              Leader
Ajeets-MacBook-Air:testenviron ajeetraina$ docker stack deploy -c docker-compose.yml myapp3
Creating network myapp3_default
Creating service myapp3_db1
Creating service myapp3_web1
Ajeets-MacBook-Air:testenviron ajeetraina$ docker stack ls
NAME                SERVICES
myapp3              2

Ajeets-MacBook-Air:testenviron ajeetraina$ kubectl config get-contexts
CURRENT   NAME                          CLUSTER                      AUTHINFO             NAMESPACE
          docker-for-desktop            docker-for-desktop-cluster   docker-for-desktop
          gce                                                        cluster-admin
          kubernetes-admin@kubernetes   kubernetes                   kubernetes-admin
*         minikube                      minikube                     minikube

Ajeets-MacBook-Air:testenviron ajeetraina$ kubectl config use-context docker-for-desktop
Switched to context "docker-for-desktop".

$git clone https://github.com/ajeetraina/docker101

$cd docker101/play-with-kubernetes/examples/stack-deploy-on-mac/

$docker stack deploy -c docker-stack1.yml myapp1

$docker stack ls

$kubectl get pods

$curl localhost:8083

$docker stack rm myapp`

$docker stack deploy -c docker-stack2.yml myapp2

$docker stack ls

$kubectl get pods

Ajeets-MacBook-Air:testenviron ajeetraina$ kubectl get stacks
NAME      AGE
myapp2    22m

Ajeets-MacBook-Air:testenviron ajeetraina$ kubectl get pods
NAME                    READY     STATUS    RESTARTS   AGE
db1-d977d5f48-l6v9d     1/1       Running   0          22m
db1-d977d5f48-mpd25     1/1       Running   0          22m
web1-6886bb478f-s7mvz   1/1       Running   0          22m
web1-6886bb478f-wh824   1/1       Running   0          22m

Adding Context for Google Cloud

Pre-requisites:

• Install google-cloud-sdk on macOS
• Enable Google Cloud Engine API
• Authenticate Your Google Cloud using gcloud auth

Creating GKE Cluster Node

Ajeets-MacBook-Air:~ ajeetraina$ gcloud container clusters create k8s-lab1 --disk-size 10 --zone asia-east1-a --machine-type n1-standard-2 --num-nodes 3 --scopes compute-rw
WARNING: The behavior of --scopes will change in a future gcloud release: service-control and service-management scopes will no longer be added to what is specified in --scopes. To use these scopes, add them explicitly to --scopes. To use the new behavior, set container/new_scopes_behavior property (gcloud config set container/new_scopes_behavior true).
WARNING: Starting in Kubernetes v1.10, new clusters will no longer get compute-rw and storage-ro scopes added to what is specified in --scopes (though the latter will remain included in the default --scopes). To use these scopes, add them explicitly to --scopes. To use the new behavior, set container/new_scopes_behavior property (gcloud config set container/new_scopes_behavior true).
Creating cluster k8s-lab1...done.
Created [https://container.googleapis.com/v1/projects/spheric-temple-187614/zones/asia-east1-a/clusters/k8s-lab1].
To inspect the contents of your cluster, go to: https://console.cloud.google.com/kubernetes/workload_/gcloud/asia-east1-a/k8s-lab1?project=spheric-temple-187614
kubeconfig entry generated for k8s-lab1.
NAME      LOCATION      MASTER_VERSION  MASTER_IP       MACHINE_TYPE   NODE_VERSION  NUM_NODES  STATUS
k8s-lab1  asia-east1-a  1.7.11-gke.1    35.201.215.156  n1-standard-2  1.7.11-gke.1  3          RUNNING

Verify it on Google Cloud

Cluster

Master version	
1.7.11-gke.1 Upgrade available
Endpoint	
35.201.215.156 Show credentials
Client certificate	
Enabled
Kubernetes alpha features	
Disabled
Total size	
3
Master zone	
...

Connecting to Your GKE Cluster

You can connect to your cluster via command-line or using a dashboard too.

Ajeets-MacBook-Air:~ ajeetraina$ gcloud container clusters get-credentials k8s-lab1 --zone asia-east1-a --project spheric-temple-187614

Fetching cluster endpoint and auth data. kubeconfig entry generated for k8s-lab1.

Listing the Nodes

Ajeets-MacBook-Air:~ ajeetraina$ kubectl get nodes
NAME                                      STATUS    ROLES     AGE       VERSION
gke-k8s-lab1-default-pool-042d2598-591g   Ready     <none>    7m        v1.7.11-gke.1
gke-k8s-lab1-default-pool-042d2598-c633   Ready     <none>    7m        v1.7.11-gke.1
gke-k8s-lab1-default-pool-042d2598-q603   Ready     <none>    7m        v1.7.11-gke.1

Did you find this blog helpful?  Feel free to share your experience. Get in touch @ajeetsraina.

If you are looking out for contribution/discussion, join me at Docker Community Slack Channel.