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gokubernetes-operatoroperator-sdk

Build a Kubernetes Operator For rolling updates

I have created a Kubernetes application (Say deployment D1, using docker image I1), that will run on client clusters.

Requirement 1 :

Now, I want to roll updates whenever I update my docker image I1, without any efforts from client side (Somehow, client cluster should automatically pull the latest docker image)

Requirement 2:

Whenever, I update a particular configMap, the client cluster should automatically start using the new configMap

How should I achieve this ?

  1. Using Kubernetes Cronjobs ?
  2. Kubernetes Operators ?
  3. Or something else ?

I heard that k8s Operator can be useful

Solution

  • Starting with the Requirement 2:

    Whenever, I update a particular configMap, the client cluster should automatically start using the new configMap

    If configmap is mounted to the deployment it will get auto-updated however if getting injected as the Environment restart is only option unless you are using the sidecar solution or restarting the process.

    For ref : Update configmap without restarting POD

    How should I achieve this ?

    • ImagePullpolicy is not a good option i am seeing however, in that case, manual intervention is required to restart deployment and it pulls the latest image from the client side and it won't be in a controlled manner.

    Using Kubernetes Cronjobs ?

    • Cronjobs you will run which side ? If client-side it's fine to do that way also.

      Else you can keep deployment with Exposed API which will run Job to update the deployment with the latest tag when any image gets pushed to your docker registry.

    Kubernetes Operators ?

    • An operator is a good native K8s option you can write in Go, Python or your preferred language with/without Operator framework or Client Libraries.

    Or something else?

    If you just looking for updating the deployment, Go with running the API in the deployment or Job you can schedule in a controlled manner, no issue with the operator too would be a more native and a good approach if you can create, manage & deploy one.

    If in the future you have a requirement to manage all clusters (deployment, service, firewall, network) of multiple clients from a single source of truth place you can explore the Anthos.

    Config management from Git repo sync with Anthos