Reliability engineering
Kubernetes Capacity Governance
Python tooling that scanned Kubernetes namespace quotas, HPA limits, and Karpenter capacity before scale risks turned into incidents.
Professional case study
200+ namespaces analyzed
45+ teams warned
6 environments covered
Problem
Namespace quotas could silently block workloads from scaling to HPA maximums during peak traffic. Existing checks did not give teams an actionable view before the risk mattered.
Action
Built Python tooling around Kubernetes data to analyze 200+ namespaces across 6 environments, compare workload requests with quota limits, aggregate risk by nodepool, and prepare clear remediation messages.
Outcome
Warned 45+ teams before peak-traffic risk became incidents and validated quota suggestions against Karpenter capacity limits.
engineering takeaways
Reusable patterns from the work.
These notes focus on the engineering judgment, tradeoffs, and patterns behind the work.
- Compared theoretical maximum scaling with actual resource requests and infrastructure capacity.
- Included practical communication so product teams could act on the findings.
- Balanced safety with the risk of over-alerting by documenting assumptions and follow-up improvements.
stack
contact