Kubernetes Cost Optimization Checklist (25 Steps)
A practical checklist covering right-sizing, spot instances, namespace quotas, and HPA tuning.
TL;DRBlog Key takeaways
• Kubernetes Cost Optimization Checklist (25 Steps): 25 actionable steps to reduce Kubernetes costs: resource requests/limits, spot/preemptible nodes, HPA tuning, namespace isolation, and more.
• Devopsify provides a tenant-scoped control plane with governed execution and audit.
• AI assistance is read-only and proposal-based; humans approve.
• Try the pattern in demo mode with zero credentials.
Devopsify is a tenant-scoped infrastructure control plane that unifies multi-cloud inventory, topology, governed provisioning, delivery operations, audit, and AI-assisted investigation under one declarative graph. A practical checklist covering right-sizing, spot instances, namespace quotas, and HPA tuning. This post examines the practical steps, trade-offs, and operational signals that make the pattern reviewable and auditable, from inventory discovery to policy evaluation and deployment waves.
Resource requests and limits
The single biggest cost lever in Kubernetes is ensuring every container has accurate resource requests and limits. Over-provisioned pods waste money; under-provisioned pods get throttled or killed. Use `kubectl top pods` to measure actual usage, then adjust requests accordingly. Set limits slightly above peak observed usage.
Cost optimization checklist
- Set resource requests based on 7-day average CPU/memory usage
- Set resource limits at 1.5× peak observed usage
- Use Horizontal Pod Autoscaler with appropriate min/max bounds
- Run non-critical workloads on spot/preemptible instances
- Right-size node groups using cluster autoscaler
- Enable pod disruption budgets to prevent unnecessary rescheduling
- Use namespace resource quotas to prevent runaway resource consumption
- Audit and remove unused services, deployments, and replicasets
- Use efficient container images (distroless, Alpine, multi-stage builds)
- Implement image pull policies wisely (IfNotPresent vs Always)
- Schedule non-urgent batch jobs during off-peak hours
- Use vertical pod autoscaler for workloads with variable demand
- Consolidate small deployments into shared namespaces where safe
- Review and clean up unused persistent volumes and snapshots
- Monitor egress traffic costs: use internal endpoints when possible
- Use node selectors and tolerations to optimize node utilization
- Implement graceful shutdown handling to avoid paying for idle pods
- Use readiness probes to prevent routing traffic to unready pods
- Consider serverless alternatives for bursty, unpredictable workloads
- Review GPU resource allocation: only assign when actually needed
- Use Karpenter or similar auto-scalers for dynamic node provisioning
- Implement cost allocation tags across all resources
- Set up budget alerts at namespace and team levels
- Run monthly cost reviews with engineering leads
- Document cost optimization decisions as runbook entries
| Aspect | Without Devopsify | With Devopsify |
|---|---|---|
| Inventory | Siloed consoles | ✓ Unified graph |
| Policy | Manual review | ✓ Pre-apply gate |
| Audit | Screenshots | ✓ Per-change trail |
How does this pattern fit your operating model?
- Connect read-first via SDK adapters or on-prem agents.
- Discover drift and topology on schedule.
- Govern attach policy and approvals.
- Operate propose with AI, approve as human, execute with audit.
Common Questions
How does Devopsify ensure the pattern is auditable?
Every proposed change carries its inventory snapshot, policy result, required approvals, and execution result as one traceable record: no gaps, no screenshots.
Can I try this without credentials?
Yes. Demo mode uses labeled mock data. Walk the same inventory, policy, and AI investigation flows with zero cloud credentials.
Does AI execute changes?
No. AI investigates and proposes; humans approve and policy gates enforce. Execution is platform-only and fully audited.
References
Cover photo via Openverse under a Creative Commons license. Illustrative imagery only.
This is a pattern, not a promise.
Every story here is an illustrative implementation pattern. To verify one against your own estate, start in demo mode (zero credentials) or request guided access.
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