autoscale-edit

name	autoscale-edit
description	Set Kubernetes autoscaling as config-as-data with the cub-autoscale CLI — edit a HorizontalPodAutoscaler's min/max replicas and cpu/memory targets, convert an HPA to a KEDA ScaledObject, apply reusable autoscaling profiles to one Unit or across a whole selector, and promote changes downstream. Use for "raise the HPA max to 20", "set cpu target to 60%", "convert this HPA to KEDA", "make every prod HPA scale out earlier", "apply the hpa-range profile", "roll the autoscaling change downstream". Dry-run by default; requires --commit --change-desc. Not for read-only checks (use autoscale-audit / autoscale-findings) or enforcement Triggers (use autoscale-guardrails).
phase	act
allowed-tools	Bash(cub-autoscale --help) Bash(cub-autoscale * --help) Bash(cub auth status) Bash(cub-autoscale preflight) Bash(cub-autoscale list *) Bash(cub-autoscale findings *) Bash(cub-autoscale set-hpa *) Bash(cub-autoscale convert-keda *) Bash(cub-autoscale profile) Bash(cub-autoscale profile *) Bash(cub-autoscale fleet-edit *) Bash(cub-autoscale promote *)

autoscale-edit

Set how workloads autoscale — as data, dry-run by default. One HPA, an HPA→KEDA conversion, a profile across a --where selector, or promoted downstream.

• set-hpa <space>/<unit> [--min N] [--max N] [--cpu PCT] [--memory PCT] — edit an HPA's replica bounds and/or cpu/memory utilization targets.
• convert-keda <space>/<unit> — rewrite an HPA as an equivalent KEDA ScaledObject (preserves min/max and cpu/memory metrics). Runs the convert-hpa-to-keda function in an embedded executor in-process — no server-side function, no worker.
• profile install | list | apply — the autoscaling profile library (stored Invocations): hpa-conservative (cpu 60%), hpa-aggressive (cpu 85%), and parameterized hpa-range (--param min=… --param max=…).
• fleet-edit --profile <slug> [--where …] — apply a profile across a selector of autoscaler Units in one operation.
• promote — override-preserving upgrade of downstream Units.

All edit Units but do not apply them to a cluster — rolling out is a separate cub unit apply.

Why this matters

cub-autoscale edits the source of record with set-yq under the hood (and the embedded executor for convert-keda); everything is dry-run by default and requires --commit --change-desc, and never bypasses ApplyGates. A pinned autoscaler (min == max) can't scale — widen the bounds. KEDA ScaledObjects also need the KEDA operator installed in the target cluster before they'll do anything.

When to use

• "Raise web's HPA to 3–20 and cpu 60%." → set-hpa web-prod/web --min 3 --max 20 --cpu 60.
• "Convert this HPA to KEDA." → convert-keda <space>/<unit>.
• "Set every prod HPA to scale out earlier." → fleet-edit --profile hpa-conservative --environment prod.
• "Set explicit bounds via a profile." → profile apply hpa-range <space>/<unit> --param min=3 --param max=15.
• "Roll the autoscaling change downstream." → promote --component <c>.

Do not load for

• Read-only checks — use autoscale-audit / autoscale-findings.
• Enforcement Triggers (a pinned-autoscaler warning, schema validation) — use autoscale-guardrails.
• Applying Units to a cluster — that is cub unit apply.

Preflight gates

1. cub-autoscale preflight succeeds. If it fails, ask the user to run cub auth login (interactive) and retry.
2. For profile apply / fleet-edit, the library exists — run cub-autoscale profile install once if profile list is empty.
3. The user has write permission on the target Space(s).

The loop

1. See the gap: cub-autoscale findings / cub-autoscale list.
2. Preview (dry-run — the default):

   cub-autoscale set-hpa web-prod/web --min 3 --max 20 --cpu 60
   cub-autoscale convert-keda web-prod/web
   cub-autoscale fleet-edit --profile hpa-conservative --environment prod
   

3. Commit with --commit --change-desc (summary + verbatim user prompt).
4. Verify: cub-autoscale list --where "Slug = '<unit>'" shows the new bounds/kind; findings clears.
5. Roll out is a separate step — hand off to cub-apply.

Safety

• Don't pin an autoscaler: keep min < max. set-hpa rejects --min > --max.
• convert-keda only translates cpu/memory Resource metrics; Pods/Object/External metrics aren't converted (KEDA needs a matching scaler) — review the dry-run output.
• Scope fleet-edit narrowly (dry-run shows the count) before a fleet-wide commit.

Stop conditions

• An ApplyGate attaches (a validating Trigger failed). Do not bypass — fix the data (or the rule), via triggers-and-applygates.
• The user wants to apply to a cluster — hand off to cub-apply.

Tool boundary

Allowed: set-hpa, convert-keda, profile, fleet-edit, promote (dry-run by default; --commit passes --change-desc), and the read commands. Not allowed: bypassing gates, kubectl mutations, applying to clusters.

References

• cub-autoscale set-hpa --help, … convert-keda --help, … profile --help, … fleet-edit --help, … promote --help.
• Companion skills: autoscale-audit, autoscale-findings, autoscale-guardrails, promote-release, triggers-and-applygates, cub-apply.