Kubernetes Agents for Cluster Cost Control

Dashboards tell you after the fact. An in-cluster agent can enforce budgets and prevent spend spikes before they hit your AWS bill.

What a cost agent should do

Discover owners: enforce labels (owner, team, cost-center) and create gaps reports.
Estimate cost in-cluster: combine price sheets with requested/used CPU/Memory, storage, and egress.
Enforce guardrails: reject manifests with missing limits, block requests above quota, cap HPA max when burn rate spikes.
Feedback in CI/CD: comment on PRs with projected cost deltas; fail checks if budgets are exceeded.
Track traffic costs: capture egress and cross-AZ bytes per namespace; most surprises are network, not compute.

Real-time control: agents run admission webhooks; dashboards are passive.
Context: agents see the manifest and service metadata; billing data alone can’t block a deploy.
Drift detection: agents can watch for removed limits, noisy sidecars, or cross-AZ traffic and open tickets automatically.

Deploy in each cluster with least-privilege RBAC and audit mode first.
Store price sheets in ConfigMaps; refresh weekly.
Emit metrics: cost.estimate.usd, guardrail.violations, waste.cpu, waste.memory, and egress.bytes.
Provide overrides with expiry (e.g., 14 days) to avoid long-lived exceptions.
Log every allow/deny decision with reasons so developers can self-serve fixes.
Run a weekly synthetic deploy to ensure the webhook is healthy; degraded webhooks silently disable guardrails.

20–40% waste reduction by blocking no-limit pods and over-requests.
Fewer cost incidents; burn-rate alerts are tied to real Kubernetes resources.
Better unit economics; every service ships with cost SLOs and budgets by default.
Faster incident RCAs because the agent records label, limit, and HPA changes tied to cost spikes.

If your EKS bill surprises you, put an agent in the cluster—not just a chart on the wall.***

👨‍💻

Founder & CEO