Kubernetes Orchestrator

How to orchestrate pipelines with Kubernetes

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The Kubernetes orchestrator is an orchestrator flavor provided with the ZenML kubernetes integration that runs your pipelines on a Kubernetes cluster.

When to use it

You should use the Kubernetes orchestrator if:

• you're looking lightweight way of running your pipelines on Kubernetes.

• you don't need a UI to list all your pipelines runs.

• you're not willing to maintain Kubeflow Pipelines on your Kubernetes cluster.

• you're not interested in paying for managed solutions like Vertex.

How to deploy it

The Kubernetes orchestrator requires a Kubernetes cluster in order to run. There are many ways to deploy a Kubernetes cluster using different cloud providers or on your custom infrastructure and we can't possibly cover all of them, but you can check out our cloud guide ZenML Cloud Guide for some complete stack deployments which use the Kubernetes orchestrator.

How to use it

To use the Kubernetes orchestrator, we need:

• The ZenML kubernetes integration installed. If you haven't done so, run

  zenml integration install kubernetes

• Docker installed and running.

• kubectl installed.

• A remote artifact store as part of your stack.

• A remote metadata store as part of your stack. If you want to use a MySQL database deployed in your Kubernetes cluster, you can use the Kubernetes metadata store. For a more production-ready setup we suggest using a MySQL metatadata store instead.

• A remote container registry as part of your stack.

• A Kubernetes cluster deployed and the name of your Kubernetes context which points to this cluster. Run kubectl config get-contexts to see a list of available contexts.

We can then register the orchestrator and use it in our active stack:

zenml orchestrator register <NAME> \
    --flavor=kubernetes \
    --kubernetes_context=<KUBERNETES_CONTEXT>

# Add the orchestrator to the active stack
zenml stack update -o <NAME>

ZenML will build a Docker image called <CONTAINER_REGISTRY_URI>/zenml:<PIPELINE_NAME> which includes your code and use it to run your pipeline steps in Kubernetes. Check out this page if you want to learn more about how ZenML builds these images and how you can customize them.

You can now run any ZenML pipeline using the Kubernetes orchestrator:

python file_that_runs_a_zenml_pipeline.py

A concrete example of using the Kubernetes orchestrator can be found here.

For more information and a full list of configurable attributes of the Kubernetes orchestrator, check out the API Docs.