Technical requirements

The code examples in this chapter will be simpler to follow if you have the following installed and running on your machine:

• Postman or another API development tool
• A local Kubernetes cluster manager like minikube or kind
• The Kubernetes CLI tool, kubectl

There are several different conda environment .yml files contained in the Chapter08 folder in the book’s GitHub repo for the technical examples, as there are a few different sub-components. These are:

• mlewp-chapter08-train: This specifies the environment for running the training scripts.
• mlewp-chapter08-serve: This specifies the environment for the local FastAPI web service build.
• mlewp-chapter08-register: This gives the environment specification for running the MLflow tracking server.

In each case, create the Conda environment, as usual, with:

conda env create –f <ENVIRONMENT_NAME>.yml

The Kubernetes examples in this...