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K3d

As explained in Distributed Machine Learning Patterns

A lightweight command-line wrapper for running k3s clusters in Docker.

k3d is a lightweight command-line wrapper that runs k3s, a minimal Kubernetes distribution, inside Docker. It quickly creates single-node or multinode Kubernetes clusters for local development. section 8.2.1

A typical local workflow uses k3d to:

Create a local cluster

Run `k3d cluster create distml --image rancher/k3s:v1.25.3-rc3-k3s1`, then use kubectl to verify the resulting node.

How Distributed Machine Learning Patterns covers it

How deep it goes
Explains the wrapper’s role and demonstrates cluster creation, node inspection, namespaces, and subsequent Pod operations.
Examples
Uses a distml cluster, node listings, the basics namespace, and a whalesay Pod.
What it assumes
Assumes familiarity with Docker and Kubernetes command-line workflows while introducing cluster and namespace setup.
What you can do after
Operate a local k3s cluster through k3d and inspect it with kubectl.
How it connects
Connects Docker, k3s, Kubernetes, kubectl, namespaces, and cluster contexts.
Cover of Distributed Machine Learning Patterns
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