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IL-0094Student pods filled the shared nodes of a JupyterHub cluster and starved the hub's core pods, freezing the hub2i2c2020- Symptoms
At 08:52 PM IST a report came in from WER that many students could not access the JupyterHub and that it was frozen; pages were stuck and nothing was usable. A rise in activity was visible by 09:02 PM, but the usual fixes, such as opening an incognito window and restarting servers, did not help.
- Trigger
WER students' pods used a good chunk of their memory limit (tests had shown they almost always use just under 1G of their 2G limit, against a 512M guarantee) on nodes shared with the hub's core pods.
- Root cause
- Component
- Contributing factor
- Detection
WER reported stuck pages and students unable to reach the hub in a GitHub issue (2i2c-org/docs#27).
- Remediation
- removed memory overcommit for the WER students
- raised resource guarantees for all core pods, which restarted them and moved some to a new node
- Action items
- Put user pods in a separate pool so they do not create pressure on the core pods (infrastructure#89)
- Set limits on the support infrastructure (Prometheus, Grafana, ingress) as well (infrastructure#90)
- Document and think about overcommit ratios for memory usage (infrastructure#91)
- Set up better Grafana dashboards to monitor resource usage (infrastructure#92)
- Document how people can get kubectl access to the cluster so others can look into issues too (infrastructure#87)
- Lessons
Core pods without resource guarantees get whatever is left on a node, so when user pods on the same nodes fill the CPU and memory, the hub that serves everyone freezes. The memory overcommit ratio has to come from measured use: WER students used just under 1G against a 512M guarantee, which a 4x overcommit could not hold.
This case involves Container memory limit and Node pool. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.