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php editor Xiaoxin is here to introduce how to build a Kubernetes Operator for rolling updates. A Kubernetes Operator is a custom controller that extends the capabilities of the Kubernetes platform. Rolling updates are a way to gradually update an application without interrupting service. By building an Operator specifically for rolling updates, we can manage upgrades and rollbacks of the application more flexibly. This article will introduce the basic steps of building a Kubernetes Operator and explain in detail how to implement the rolling update function. Let’s take a closer look!
I have created a Kubernetes application (e.g. deploy D1, using docker image I1) that will run on a client cluster.
Requirement 1:
Now I want to do a rolling update every time I update my docker image I1 without any effort on the client side (Somehow the client cluster should automatically pull the latest docker image)
Requirement 2:
Whenever I update a specific configMap, the client cluster should automatically start using the new configMap
How should I achieve this goal?
I heard k8s Operator is useful
Start with Requirement 2:
Whenever I update a specific configMap, the client cluster should Automatically start using the new configMap
If the configmap has been installed into the deployment it will automatically update, but if injected as an environment restart is the only option unless you use a sidecar solution or restart the process.
Reference: Update configmap without restarting POD
How should I achieve this?
Using Kubernetes Cronjobs?
Which side will you run your cronjobs on? If it’s a client, that’s it Also like this.
Otherwise, you can use the exposed API to keep the deployment going, which will run the job to When pushing any image, update the deployment with the latest tag to your docker registry.
Kubernetes Operator?
or something else?
If you just want to update the deployment, run the API in a deployment or job, you can schedule it in a controlled way and there won't be any issues with the operator, it will be a more native Question If you can create, manage, and deploy a method, that's a good approach.
If in the future you need to manage all clusters (deployments, services, firewalls, networks) of multiple clients from a single source of truth, you can explore Anthos.
Configuration Management Antos for Git Repository Synchronization
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