gke-scaling

Q: How do I install gke-scaling?

Run npx skills add https://github.com/google/skills --skill gke-scaling in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/gke-scaling/ (personal) or .claude/skills/gke-scaling/ (project).

by google

Configures GKE autoscaling, including HPA, VPA, and Node Auto-Provisioning (NAP). Use when configuring GKE autoscaling, setting up GKE HPA, setting up GKE VPA, or configuring GKE NAP. Don't use for configuring static cluster sizes or setting node-level machine styles directly (use gke-compute-classes instead).

Installs: 968
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/google/skills --skill gke-scaling

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads gke-scaling automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

GKE Workload Scaling

This reference covers scaling workloads on GKE. The golden path enables VPA, OPTIMIZE_UTILIZATION autoscaling profile, and Node Auto Provisioning by default.

MCP Tools: get_k8s_resource, describe_k8s_resource, apply_k8s_manifest, patch_k8s_resource, get_cluster, update_cluster, update_node_pool

Golden Path Scaling Defaults

Setting	Golden Path Value	Notes
`autoscaling.autoscalingProfile`	`OPTIMIZE_UTILIZATION`	Aggressive scale-down for cost savings
`verticalPodAutoscaling.enabled`	`true`	VPA recommendations available
`autoscaling.enableNodeAutoprovisioning`	`true`	NAP creates node pools on demand
GPU resource limits (T4, A100)	`1000000000` each	NAP can provision GPU nodes

Scaling Mechanisms

1. Manual Scaling

kubectl-only — no MCP equivalent for kubectl scale. Use kubectl directly.

kubectl scale deployment <DEPLOYMENT> --replicas=<N> -n <NAMESPACE>

2. Horizontal Pod Autoscaling (HPA)

Scales the number of pods based on metrics.

Quick setup (kubectl-only — no MCP equivalent for kubectl autoscale):

kubectl autoscale deployment <DEPLOYMENT> --cpu-percent=50 --min=1 --max=10

Manifest approach (recommended — use MCP apply_k8s_manifest):

See assets/hpa-example.yaml for a template.

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: <DEPLOYMENT>-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: <DEPLOYMENT>
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50

3. Vertical Pod Autoscaling (VPA)

Adjusts CPU and memory requests to match actual usage. Enabled by default on golden path.

Update modes:

Off — recommendations only (safest, start here)
Initial — sets resources only at pod creation
Auto — restarts pods to apply new resource values
InPlaceOrRecreate — updates resources without restart when possible (GKE 1.34+)

Create VPA in recommendation mode:

apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: <DEPLOYMENT>-vpa
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: <DEPLOYMENT>
  updatePolicy:
    updateMode: "Off"

Read recommendations (prefer MCP describe_k8s_resource):

# MCP (preferred)
describe_k8s_resource(parent="...", resourceType="verticalpodautoscaler", name="<DEPLOYMENT>-vpa", namespace="<NAMESPACE>")

# kubectl fallback
kubectl get vpa <DEPLOYMENT>-vpa -o jsonpath='{.status.recommendation}'

See assets/vpa-example.yaml for a full template.

4. Cluster Autoscaler / Node Auto Provisioning (NAP)

On Autopilot (golden path), node scaling is fully managed. NAP automatically creates and sizes node pools based on workload demands.

For Standard clusters:

# Enable cluster autoscaler on a node pool
gcloud container clusters update <CLUSTER_NAME> --region <REGION> \
  --enable-autoscaling --node-pool <POOL_NAME> \
  --min-nodes <MIN> --max-nodes <MAX> \
  --quiet

# Enable NAP
gcloud container clusters update <CLUSTER_NAME> --region <REGION> \
  --enable-autoprovisioning \
  --min-cpu <MIN_CPU> --max-cpu <MAX_CPU> \
  --min-memory <MIN_MEM> --max-memory <MAX_MEM> \
  --quiet

Autoscaling profiles:

Profile	Behavior	Golden Path?
`BALANCED`	Default GKE; conservative scale-down	No
`OPTIMIZE_UTILIZATION`	Aggressive scale-down; lower idle	Yes
: : resources : :

Best Practices

Define resource requests: HPA and VPA rely on accurate requests. Always set them.
Avoid metric conflicts: Do not use HPA and VPA on the same metric. Typical pattern: HPA on CPU, VPA on memory.
Pod Disruption Budgets: Define PDBs for all production workloads to ensure availability during scaling events.
HPA stabilization: HPA has a default 5-minute stabilization window. Tune behavior for faster response if needed.
VPA "Auto" caution: Auto mode restarts pods. Ensure your app handles SIGTERM gracefully. VPA requires at least 2 replicas for evictions by default.
Use ComputeClasses: For workload-specific node targeting (Spot fallback, GPU, specific machine families), use ComputeClasses instead of node selectors.

Rightsizing Workflow

Deploy VPA in Off mode for 24+ hours
Read recommendations: kubectl describe vpa <NAME>
Compare target values against current requests
Apply with 20% buffer: new_request = target * 1.2
Use patch format to update Deployment

Condition	Recommendation	Risk
CPU request >5x P95 actual	Reduce to `P95 * 1.2`	Medium
Memory request >3x P95 actual	Reduce to `P95 * 1.2`	Medium
CPU request >2x P95 actual	Rightsizing with 20% buffer	Low
No resource limits set	Add limits to prevent noisy-neighbor	Low

FAQ

What does the gke-scaling skill do?

How do I install gke-scaling?

Run npx skills add https://github.com/google/skills --skill gke-scaling in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/gke-scaling/ (personal) or .claude/skills/gke-scaling/ (project).

Which AI agents can use gke-scaling?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is gke-scaling safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains gke-scaling?

It is published by google in google/skills. It has 968 recorded installs.

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gke-scaling

Install

Install

Describe the task

Review the result

SKILL.md

GKE Workload Scaling

Golden Path Scaling Defaults

Scaling Mechanisms

1. Manual Scaling

2. Horizontal Pod Autoscaling (HPA)

3. Vertical Pod Autoscaling (VPA)

4. Cluster Autoscaler / Node Auto Provisioning (NAP)

Best Practices

Rightsizing Workflow

FAQ

More from google/skills

Popular other skills