Tool · Reality Check
Kubernetes efficiency
How much of your provisioned cluster capacity is headroom you're paying for — from three numbers you already know.
Directional, not an audit — computed only from what you enter, entirely in your browser.
Use a representative p95 over 14–30 days, peaks included.
Directional read
≈2 nodes of conservative headroom
Requests are pinning ~35% more capacity than the workload uses. The real number is conditional on placement, DaemonSets, AZ spread, disruption budgets and autoscaling lag — but the gap is worth a look.
How we govern Kubernetes capacityRecommended next step
Cloud Cost & FinOps Audit
~2 weeks · fixed fee
Cost baseline + prioritised savings roadmap you own
Book this reviewConfidence: directional — computed only from what you enter, entirely in your browser. Not an audit.
If the verdict stings
The fixed-scope Kubernetes Production-Readiness Review turns this two-minute read into a findings report and a prioritised plan — fixed fee, agreed at a 30-minute scoping call.
The discipline behind it
This instrument encodes how we approach kubernetes & platform engineering on real engagements — the same judgement, applied by hand, with your actual system in front of us.
The thinking behind this instrument
All field notesKubernetes cost optimisation: a utilisation problem, not a price problem
The average cluster uses about 10% of its CPU — fix sizing before touching pricing.
21 min read
Kubernetes & platformKarpenter vs the cluster autoscaler: getting node scaling right
Cluster autoscaler or Karpenter: the choice that decides how much of your bill is waste.
19 min read
Kubernetes & platformAutoscaling for traffic spikes: beyond a single HPA
Layer pod, node and event-driven scaling — a lone HPA won't survive launch day.
21 min read
Want the same read on your real system?
Bring the numbers this tool asked you for. A senior engineer will tell you what they mean on your architecture — no sales layer.