Scott Hanselman

After building a Raspberry Pi Kubernetes Cluster, I wanted to see how quickly I could get up to speed on Kubernetes in Azure.

• I installed the Azure CLI (Command Line Interface) in a few minutes - works on Windows, Mac or Linux.
• I also remembered that I don't really need to install anything locally. I could just use the Azure Cloud Shell directly from within VS Code. I'd get a bash shell, Azure CLI, and automatically logged in without doing anything manual.
• Anyway, while needlessly installing the Azure CLI locally, I read up on the Azure Container Service (AKS) here. There's walkthrough for creating an AKS Cluster here. You can actually run through the whole tutorial in the browser with an in-browser shell.
• After logging in with "az login" I made a new resource group to hold everything with "az group create -l centralus -n aks-hanselman." It's in the centralus and it's named aks-hanselman.
• Then I created a managed container service like this:
  C:\Users\scott\Source>az aks create -g aks-hanselman -n hanselkube --generate-ssh-keys
  / Running ...
• This runs for a few minutes while creating, then when it's done, I can get ahold of the credentials I need with
  C:\Users\scott\Source>az aks get-credentials --resource-group aks-hanselman --name hanselkube
  Merged "hanselkube" as current context in C:\Users\scott\.kube\config
• I can install Kubenetes CLI "kubectl" easily with "az aks install-cli"
  Then list out the nodes that are ready to go!
  C:\Users\scott\Source>kubectl get nodes
  NAME                       STATUS    ROLES     AGE       VERSION
  aks-nodepool1-13823488-0   Ready     agent     1m        v1.7.7
  aks-nodepool1-13823488-1   Ready     agent     1m        v1.7.7
  aks-nodepool1-13823488-2   Ready     agent     1m        v1.7.7

A year ago, Glenn Condron and I made a silly web app while recording a Microsoft Virtual Academy. We use it for demos and to show how even old (now over a year) containers can still be easily and reliably deployed. It's up at https://hub.docker.com/r/glennc/fancypants/.

I'll deploy it to my new Kubernetes Cluster up in Azure by making this yaml file:

apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: fancypants
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: fancypants
    spec:
      containers:
      - name: fancypants
        image: glennc/fancypants:latest
        ports:
        - containerPort: 80
---
apiVersion: v1
kind: Service
metadata:
  name: fancypants
spec:
  type: LoadBalancer
  ports:
  - port: 80
  selector:
    app: fancypants

I saved it as fancypants.yml, then run kubectl create -f fancypants.yml.

I can run kubectl proxy and then hit http://localhost:8001/api/v1/namespaces/kube-system/services/http:kubernetes-dashboard:/proxy/#!/overview?namespace=default to look at the Kubernetes Dashboard, proxyed locally, but all running in Azure.

When fancypants is created and deployed, then I can find out its external IP with:

C:\Users\scott\Sources>kubectl get service
NAME         TYPE           CLUSTER-IP     EXTERNAL-IP     PORT(S)        AGE
fancypants   LoadBalancer   10.0.116.145   52.165.232.77   80:31040/TCP   7m
kubernetes   ClusterIP      10.0.0.1       <none>          443/TCP        18m

There's my IP, I hit it and boom, I've got fancypants in the managed cloud. I only have to pay for the VMs I'm using, and not for the VM that manages Kubernetes. That means the "kube-system" namespace is free, I pay for other namespaces like my "default" one.

Best part? When I'm done, I can just delete the resource group and take it all away. Per minute billing.

C:\Users\scott\Sources>az group delete -n aks-hanselman --yes

Super fun and just took about 30 min to install, read about, try it out, write this blog post, then delete. Try it yourself!

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About Scott

Scott Hanselman is a former professor, former Chief Architect in finance, now speaker, consultant, father, diabetic, and Microsoft employee. He is a failed stand-up comic, a cornrower, and a book author.

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