Safe deployments with Temporal Worker Versioning on Kubernetes

This post details the practical application of Temporal Worker Versioning on Kubernetes. It demonstrates how to set up a research agent Workflow, intentionally break it with a naive deployment causing non-determinism errors, and then resolve this by installing and using the Temporal Worker Controller. The post explains the concept of "rainbow deployments" where multiple worker versions coexist on the same task queue, with the Temporal Server routing tasks based on worker build IDs. It covers the use of `TemporalWorkerDeployment` resources to manage worker lifecycles, progressive rollouts, and the handling of long-running and idle Workflows during version transitions using `Continue-as-New` and version pinning.