After several years working in the container space, I still hear in a lot of sessions and meetings that Kubernetes is not meant for running stateful applications. Of course, stateless apps are a lot more easier, less challenging and disposable than stateful apps. But in the end, almost every useful application depends on data. Kubernetes is a great choice to scale up/down apps and adapt them to demand, but if a database/broker/other-stateful-app cannot scale similarly, we can guess where the bottleneck and the limits would be.

Recently, I had a situation where I needed to introspect on the memory of a java program running on kubernetes. The usual procedure is connecting to the container, getting a dump, collecting this dump from a standalone laptop/host and analyzing it offline. However, I wanted to explore some other alternatives, so I would get here some additional techniques that can be used either from developers or for operations doing debugging or forensics.

Prometheus and grafana have been established as de-facto stacks for kubernetes cluster monitoring, at least in the upstream communities. Once a cluster has the stack available, kubernetes and other application components are exposing their metrics. There is a need to create curated alerts based on those metrics and dashboards that give a high level view of what is happening. There is an effort to create those artifacts in a templated way.