container-density-audit

스타4

포크0

업데이트2026년 7월 18일 15:25

Audit Kubernetes/container clusters for poor bin-packing — inflated resource requests vs actual usage, low node utilization, missing autoscaling, pods hoarding capacity. Use this skill whenever the user shares k8s manifests, kubectl top / metrics-server output, cluster utilization data, or asks about node counts, pod density, cluster efficiency, or Kubernetes sustainability. Part of Lean Agentic AI Skills; emits lean-findings.json.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

출처

navveenb

navveenb/lean-agentic-ai-skills

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Container Density Audit

Producer skill. Input: manifests (requests/limits), kubectl top nodes/pods output, cluster autoscaler config, node inventory. Output: lean-findings.json.

In Kubernetes the scheduler believes requests, not reality. Every pod requesting 4x what it uses forces the cluster to run nodes that are "full" on paper and idle in silicon. Density is the M-lever: fewer nodes for the same work.

Subject type: emit subject.type: "container-platform" in findings.

Signatures

Request inflation — usage-to-request ratio < 30% across a workload's pods. High. Evidence: actual vs requested from metrics. Fix: lower requests (state the new value and the headroom retained) or install VPA in recommend mode first.
Missing requests entirely — scheduler flying blind; density unmanageable. Medium-high.
Limits == requests everywhere for burstable workloads — no bursting, forced oversizing. Medium (context-dependent — Guaranteed QoS may be deliberate; ask/flag rather than assert).
Node utilization — fleet p95 CPU/mem below ~50% with stable pod count → node pool downsizing or consolidation candidate. High.
No cluster autoscaler / no scale-down — scale-down-disabled annotations everywhere, generous over-provisioning buffers. Medium.
System overhead — daemonsets summing to a large slice of small nodes → fewer, larger nodes often pack better. Low-medium; name the trade-off (blast radius).
Missing PodDisruptionBudgets blocking consolidation — autoscaler can't drain. Low.

Honesty rules

Bin-packing tighter trades against noisy-neighbor risk and surge headroom; every density recommendation states retained headroom. Never recommend request cuts from a utilization window that misses known peaks — say what the window was.

Cost signal (countable)

Cost driver: node-hours (or the cluster's billed capacity unit). cost_signal.observed names the current node fleet size and utilisation, direction reflects the consolidation opportunity qualitatively.

Not this skill's job

VM-level sizing (right-size-compute), whether workloads belong on k8s at all (vm-to-serverless-advisor).

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name

container-density-audit

description

Container Density Audit

Producer skill. Input: manifests (requests/limits), kubectl top nodes/pods output, cluster autoscaler config, node inventory. Output: lean-findings.json.

Subject type: emit subject.type: "container-platform" in findings.

Signatures

Request inflation — usage-to-request ratio < 30% across a workload's pods. High. Evidence: actual vs requested from metrics. Fix: lower requests (state the new value and the headroom retained) or install VPA in recommend mode first.
Missing requests entirely — scheduler flying blind; density unmanageable. Medium-high.
Limits == requests everywhere for burstable workloads — no bursting, forced oversizing. Medium (context-dependent — Guaranteed QoS may be deliberate; ask/flag rather than assert).
Node utilization — fleet p95 CPU/mem below ~50% with stable pod count → node pool downsizing or consolidation candidate. High.
No cluster autoscaler / no scale-down — scale-down-disabled annotations everywhere, generous over-provisioning buffers. Medium.
System overhead — daemonsets summing to a large slice of small nodes → fewer, larger nodes often pack better. Low-medium; name the trade-off (blast radius).
Missing PodDisruptionBudgets blocking consolidation — autoscaler can't drain. Low.

Honesty rules

Cost signal (countable)

Not this skill's job

VM-level sizing (right-size-compute), whether workloads belong on k8s at all (vm-to-serverless-advisor).