Before a Kubernetes upgrade or a routine node drain, cluster operators still check each application by hand to see whether it will survive. The Kubernetes project wants to replace that ritual with a shared, testable standard, and on Tuesday it announced a Workload Conformance Working Group to write one.

Certified Kubernetes tests the cluster, and Kubernetes AI Conformance tests whether a cluster can run AI and ML workloads. Nothing comparable exists for the workloads themselves, wrote Nabarun Pal of Broadcom on behalf of the group. The failures operators find are familiar ones: an app that can’t tolerate disruption shows up during a drain, an upgrade breaks something that still depends on a removed API version, and some workloads request privileges they don’t need or reserve resources they never use.

What the group plans to produce

The charter lists three deliverables: a specification of workload behavior for each Kubernetes minor version, a method for testing each requirement against a running workload,…