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autoscale-audit

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UpdatedJuly 2, 2026 at 01:54

Inventory and report Kubernetes autoscaling stored in ConfigHub across a fleet with the cub-autoscale CLI — HorizontalPodAutoscalers and KEDA ScaledObjects: each one's scale target, min/max replicas, and whether it is pinned (min == max). Use for "what autoscalers do we have?", "list our HPAs / ScaledObjects", "which workloads are autoscaled?", "per-cluster autoscaler counts", "is autoscaler X pinned?". Not for autoscaling findings/anti-patterns (use autoscale-findings), edits or HPA→KEDA conversion (use autoscale-edit), or live cluster state (use kubectl); analysis is over ConfigHub-managed Units only.

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name	autoscale-audit
description	Inventory and report Kubernetes autoscaling stored in ConfigHub across a fleet with the cub-autoscale CLI — HorizontalPodAutoscalers and KEDA ScaledObjects: each one's scale target, min/max replicas, and whether it is pinned (min == max). Use for "what autoscalers do we have?", "list our HPAs / ScaledObjects", "which workloads are autoscaled?", "per-cluster autoscaler counts", "is autoscaler X pinned?". Not for autoscaling findings/anti-patterns (use autoscale-findings), edits or HPA→KEDA conversion (use autoscale-edit), or live cluster state (use kubectl); analysis is over ConfigHub-managed Units only.
phase	verify
allowed-tools	Bash(cub-autoscale --help) Bash(cub-autoscale * --help) Bash(cub auth status) Bash(cub-autoscale preflight) Bash(cub-autoscale snapshot) Bash(cub-autoscale snapshot ) Bash(cub-autoscale list) Bash(cub-autoscale list )

autoscale-audit

Report the autoscaling ConfigHub holds — HorizontalPodAutoscalers and KEDA ScaledObjects — across the fleet. Read-only.

Why this matters

cub-autoscale loads a fleet snapshot of autoscalers and the workloads they target, so you can see at a glance which workloads scale, what their replica bounds are, and which autoscalers are pinned (min == max, so they can't actually scale). Clusters are ConfigHub Targets (the Space slug stands in for unbound Units). Analysis is over ConfigHub-managed Units only. Output is JSON by default; add -o table for humans.

When to use

"What autoscalers do we have?" / "audit autoscaling." → list.
"List our HPAs / ScaledObjects." → list (KIND column).
"Which workloads are autoscaled / not?" → snapshot (AUTOSCALED vs WORKLOADS).
"Per-cluster autoscaler counts." → snapshot.
"Is autoscaler X pinned?" → list (PINNED column).

Do not load for

Autoscaling anti-patterns, ranked (pinned, no-autoscaler, PDB-vs-minReplicas) — use autoscale-findings.
Editing an HPA, converting HPA→KEDA, applying a profile — use autoscale-edit.
Live cluster state (current replica count, HPA status) — kubectl.

Preflight gates

cub-autoscale preflight succeeds. If it fails, ask the user to run cub auth login (interactive) and retry.

The toolkit

cub-autoscale snapshot -o table — per-cluster HPA / ScaledObject / workload / autoscaled / PDB counts.
cub-autoscale list -o table — per-autoscaler kind, scale target, min/max, and whether it's pinned.

Scoping

Server-side --where plus label shorthands (--component, --environment, --region, --owner, --layer, --variant), AND-only.

Stop conditions

Snapshot empty — report it; suggest widening scope or checking cub auth status.
The question is about anti-patterns or fixing autoscaling — hand off to autoscale-findings / autoscale-edit.

Tool boundary

Read-only. Never use kubectl to answer a ConfigHub-state question.

References

cub-autoscale snapshot --help, cub-autoscale list --help.
Companion skills: autoscale-findings, autoscale-edit.

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Install and inspect the autoscaling enforcement pack with the cub-autoscale CLI — an autoscale-policy Space with two Warn=true Triggers: a vet-cel rule that flags any HPA/ScaledObject that is pinned (min == max), and a vet-schemas rule that schema-validates every mutation (the post-convert check for convert-keda output, since keda.sh is in the schema catalog) — wired to in-scope Spaces via a shared Trigger Filter. guardrails install (dry-run by default) and status (Units with ApplyWarnings/Gates). Use for "enforce that no HPA is pinned", "make sure converted ScaledObjects pass schema validation", "which autoscalers are flagged?". Not for read-only findings (use autoscale-findings) or fixing autoscaling (use autoscale-edit).

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Inventory the observability posture of Kubernetes workloads stored in ConfigHub across a fleet with the cub-observability CLI — ServiceMonitors, Services (and which expose metrics), and telemetry-sidecar presence. Use for "what ServiceMonitors / Services do we have?", "which Services expose metrics?", "which workloads have an otel sidecar?", "per-cluster observability counts". Not for ServiceMonitor coverage gaps (use observability-findings), fixes (use observability-instrument / observability-guardrails), or live cluster state (use kubectl); analysis is over ConfigHub-managed Units only.

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name	autoscale-audit
description	Inventory and report Kubernetes autoscaling stored in ConfigHub across a fleet with the cub-autoscale CLI — HorizontalPodAutoscalers and KEDA ScaledObjects: each one's scale target, min/max replicas, and whether it is pinned (min == max). Use for "what autoscalers do we have?", "list our HPAs / ScaledObjects", "which workloads are autoscaled?", "per-cluster autoscaler counts", "is autoscaler X pinned?". Not for autoscaling findings/anti-patterns (use autoscale-findings), edits or HPA→KEDA conversion (use autoscale-edit), or live cluster state (use kubectl); analysis is over ConfigHub-managed Units only.
phase	verify
allowed-tools	Bash(cub-autoscale --help) Bash(cub-autoscale * --help) Bash(cub auth status) Bash(cub-autoscale preflight) Bash(cub-autoscale snapshot) Bash(cub-autoscale snapshot ) Bash(cub-autoscale list) Bash(cub-autoscale list )

autoscale-audit

Report the autoscaling ConfigHub holds — HorizontalPodAutoscalers and KEDA ScaledObjects — across the fleet. Read-only.

Why this matters

When to use

"What autoscalers do we have?" / "audit autoscaling." → list.
"List our HPAs / ScaledObjects." → list (KIND column).
"Which workloads are autoscaled / not?" → snapshot (AUTOSCALED vs WORKLOADS).
"Per-cluster autoscaler counts." → snapshot.
"Is autoscaler X pinned?" → list (PINNED column).

Do not load for

Autoscaling anti-patterns, ranked (pinned, no-autoscaler, PDB-vs-minReplicas) — use autoscale-findings.
Editing an HPA, converting HPA→KEDA, applying a profile — use autoscale-edit.
Live cluster state (current replica count, HPA status) — kubectl.

Preflight gates

cub-autoscale preflight succeeds. If it fails, ask the user to run cub auth login (interactive) and retry.

The toolkit

cub-autoscale snapshot -o table — per-cluster HPA / ScaledObject / workload / autoscaled / PDB counts.
cub-autoscale list -o table — per-autoscaler kind, scale target, min/max, and whether it's pinned.

Scoping

Server-side --where plus label shorthands (--component, --environment, --region, --owner, --layer, --variant), AND-only.

Stop conditions

Snapshot empty — report it; suggest widening scope or checking cub auth status.
The question is about anti-patterns or fixing autoscaling — hand off to autoscale-findings / autoscale-edit.

Tool boundary

Read-only. Never use kubectl to answer a ConfigHub-state question.

References

cub-autoscale snapshot --help, cub-autoscale list --help.
Companion skills: autoscale-findings, autoscale-edit.