Skip to content
Baseline PLM

Blog

What we learned running Windchill on Kubernetes

Method-server sizing, vault storage, and why rollbacks need rehearsal. Notes from operating Windchill on AKS in production.

, by Baseline PLM teamTopics: kubernetes, cloud, operations

Windchill runs well in containers, but not by accident. A few things we learned the hard way.

Size the JVM for the pod, not the node

Method servers that are given memory limits without matching JVM settings get killed at the worst moment. Set heap explicitly and leave headroom for metaspace and native memory.

Treat the vault as a first-class dependency

File vaults on cloud file shares behave differently from local disks. Latency on small files matters more than throughput. Measure it before go-live, and monitor it afterwards.

Rehearse rollbacks

A rollback that has only been described is not a rollback. Every pipeline we build includes a rollback job that is exercised on the test environment with every release.

Clone environments on demand

The single biggest quality-of-life improvement for most teams is being able to refresh a test environment from production in a couple of hours. Once that exists, testing stops being negotiable.

Tell us where Windchill is slowing you down.

A 45-minute call with a consultant who has run Windchill in production. No slides, no sales script.