Wrong requests are a common source of either overspending or instability: the container assumes more CPU than the node can fairly provide, or memory limits invite OOM kills.
AI suggestions in Opsy are a starting point for engineering judgment, not autopilot. Teams cross-check with load profiles, SLOs, and budget; then apply changes in a controlled way.
FinOps and engineering often speak different languages: invoices versus latency. Shared utilization views and suggested bands help align without blame.
Optimization loop
Gather metrics → spot workloads with obvious headroom or risk → form a hypothesis → validate with load or canary tests → lock new limits. Opsy accelerates steps up to the hypothesis.
Risks and care
Aggressive CPU cuts can harm latency; low memory limits can kill Pods on spikes. Post-change observation and fast rollback matter.
Highlights
- CPU and memory hints grounded in observed usage
- Less eyeball padding and cluster waste
- Lower OOM risk from underestimated limits
- Shared vocabulary for engineering and FinOps
- Fits infrastructure change review practices
- Pairs with monitoring and release history
- Especially helpful as similar services multiply