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AI/ML Examples on Kubernetes

Welcome to the AI/ML examples section! Our goal is to provide a collection of community-curated, open-source reference manifests for deploying and managing AI/ML workloads, MLOps toolchains, and end-to-end platforms on Kubernetes.

This area is under active development as part of a broader initiative to enhance the kubernetes/examples repository. We aim to simplify the developer and operator experience for AI applications on Kubernetes, promoting best practices and interoperability.

Vision for AI/ML Examples

We envision this section housing examples such as:

  • Setups for distributed training frameworks.
  • Configurations for model serving solutions.
  • Blueprints for data versioning and experiment tracking integrations.
  • End-to-end MLOps platform examples.
  • "AI Kits" designed to help AI/ML experts quickly get started on Kubernetes.

Call for Contributions

The success of this initiative depends on community contributions! If you have expertise in running AI/ML workloads on Kubernetes or ideas for valuable examples, we strongly encourage you to contribute.

We are particularly interested in examples that are:

  • Educational and provide an easy start for AI/ML practitioners new to Kubernetes.
  • Modular and showcase best practices.
  • Cover a diverse range of tools and MLOps stages.

Current Status

This section is currently being populated. Check back soon for our first set of AI/ML examples!