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    22 Mar, 2021
    5 Steps to Build a Cloud Strategy on AWS
    Cloud ,

    Are you looking to build a cloud strategy on AWS? Amazon Web Services, commonly abbreviated as AWS, is a secure cloud services platform where you can use computer power to store your database info and perform other content delivery functions for your business. The worldwide cloud service helps you connect with businesses and clients from […]

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    19 Mar, 2021
    Adding a MachineHealthCheck using Kustomize
    Cloud

    MachineHealthChecks are a powerful feature in the Kubernetes Cluster API (CAPI), and something I played around with not too long ago on TGIK 143. Recently, I was helping to document the use of kustomize with Cluster API for inclusion in the upstream CAPI documentation, and I learned a simple trick with kustomize that I’d apparently overlooked in the past. If you’ve used kustomize for any great length of time you probably already know and have used the functionality I’ll describe in this post, but if you’re new to kustomize or, like me, a user of kustomize that hasn’t had time to dig into all of its functionality, then read on and see how you can use kustomize to add a MachineHealthCheck to a CAPI workload cluster.

    If you’re not familiar with kustomize, then reading my introduction to kustomize may be useful before continuing on with the rest of this article.

    In this use case—adding a MachineHealthCheck to an workload cluster in CAPI—I’ll work from the assumption that you have a “base” CAPI workload cluster definition (perhaps one you’ve generated using clusterctl config cluster). In the directory where this workload cluster manifest exists, you’d need to add a kustomization.yaml to specify resources. It would look something like this:

    ---
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources: - base.yaml

    Now, let’s say you want to add a MachineHealthCheck for this workload cluster. You’d create a kustomize overlay directory, and in that overlay directory you’d place (at least) two files:

    1. Another kustomization.yaml file (more on that in a moment)
    2. A YAML manifest for a MachineHealthCheck

    (I say “at least” two files because you could also place other patches or other resources in the directory as well.)

    The YAML manifest for the MachineHealthCheck is straightforward; I’ll only point out to make sure to specify the correct cluster name and deployment name, taking into account any “namePrefix” or “nameSuffix” directives you may be using.

    The kustomization.yaml would look something like this:

    ---
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources: - ../../base - workload-mhc.yaml

    Now, you may also include various other directives, but the key here is in the “resources” section. It does, of course, specify the base configuration, but it also lists the MachineHealthCheck manifest that resides in this overlay directory. When you run kustomize build ., kustomize will combine the specified resources together. In this case, that means it will combine the base workload cluster manifest and the MachineHealthCheck manifest, and the end result—when you feed this to kubectl apply—will be a new workload cluster and a MachineHealthCheck to go along with it.

    The functionality of combining resources in an overlay is a core part of the functionality of kustomize, but for some reason I hadn’t leveraged it yet. Kudos to the Cluster API Provider for Azure (CAPZ) team for illustrating this use case in the creation of workload cluster template “flavors." Now that I know it’s there, I can begin to see other potential use cases, such as adding extra MachineDeployments to a base workload cluster configuration.

    I hope this information is useful. As I said, if you’re a long-time kustomize user, this is probably not news to you, but for others who are still exploring all the various pieces of functionality that kustomize offers I hope this opens up some new possibilities for you. I welcome all constructive feedback; feel free to reach out to me on the Kubernetes Slack instance or contact me on Twitter.

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