/gke-basics
Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, configuring Workload Identity, or deciding between Autopilot and Standard modes. Don't use for specialized
$ npx -y skills add google/skills --skill gke-basics --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/gke-basics
Context preview
The summary Claude sees to decide when to auto-load this skill.
Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, configuring Workload Identity, or deciding between Autopilot and Standard modes. Don't use for specialized
SKILL.md
gke-basics.SKILL.mdname: gke-basics
metadata:
category: Containers
description: >-
Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection,
and workload deployment. Use when creating GKE clusters, fetching kubectl credentials,
configuring Workload Identity, or deciding between Autopilot and Standard modes.
Don't use for specialized GKE networking (use gke-networking), advanced security hardening
(use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades).
GKE Basics & Critical Gotchas
Managed Kubernetes platform on Google Cloud. Defaults to Autopilot mode unless Standard is explicitly required.
Key Selection Rules: Autopilot vs. Standard
- **Default to Autopilot** for almost all workloads.
- **Use Standard ONLY if:**
- Custom node OS kernel parameters (`sysctl`) are required.
- Custom node taints or specific hardware node pools are required.
- DaemonSets require raw `hostPath` mounts to the host OS filesystem.
- When explaining why Standard is required over Autopilot, explicitly cite all matching restrictions (e.g., custom sysctls and custom node taints).
- *For advanced cluster architecture or complex node pool creation planning, refer to `gke-cluster-creation`.*
Critical Gotchas & Best Practices
1. **Private Autopilot Clusters:**
- Use `--enable-private-nodes` for private node IP addresses.
- Use `--enable-private-endpoint` to disable public IP access to the control plane.
- Restrict control plane access with `--enable-master-authorized-networks` and `--master-authorized-networks=CIDR_BLOCK`:
gcloud container clusters create-auto CLUSTER_NAME --region=REGION \
--enable-private-nodes \
--enable-private-endpoint \
--enable-master-authorized-networks \
--master-authorized-networks=CIDR_BLOCK2. **Workload Identity (IAM Binding):**
- Never mount raw GCP Service Account JSON keys in Pods.
- Annotate the Kubernetes ServiceAccount (`KSA`) to bind to the Google Service Account (`GSA`):
metadata:
annotations:
iam.gke.io/gcp-service-account: GSA_NAME@PROJECT_ID.iam.gserviceaccount.com3. **Autopilot Resource Requests:**
- In Autopilot, CPU requests must be specified in increments of 250m (0.25 vCPU). If an unaligned CPU request (e.g., 300m) is requested, round up to the nearest 250m increment (500m / 0.5 vCPU).
- Resource requests equal limits automatically. Omit `limits` to allow Autopilot to set defaults matching `requests`.
4. **Cluster Credentials:**
- Always explicitly specify `--region` (for regional clusters) or `--zone` (for zonal clusters) when fetching credentials:
gcloud container clusters get-credentials CLUSTER_NAME --region=REGION --quiet
Reference Directory
- [Core Concepts](references/core-concepts.md): Architecture, cluster modes (Autopilot vs Standard), networking, scaling, and security model.
- [CLI Usage & Tool Reference](references/cli-reference.md): Tool preference hierarchy (MCP vs gcloud vs kubectl), `gcloud container` commands, and user preference overrides.
- [Client Libraries](references/client-library-usage.md): Official Kubernetes and Google Cloud Container client libraries in Python, Go, Node.js, and Java.
- [MCP Usage](references/mcp-usage.md): Connecting to and using the 23 structured GKE MCP tools for cluster management, K8s resources, and diagnostics.
- [Infrastructure as Code](references/iac-usage.md): Terraform examples for `google_container_cluster` (Autopilot), Kubernetes provider resources, and YAML samples.
Read more
name: gke-basics metadata: category: Containers description: >- Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, configuring Workload Identity, or deciding between Autopilot and Standard modes. Don't use for specialized GKE networking (use gke-networking), advanced security hardening (use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades).
GKE Basics & Critical Gotchas
Managed Kubernetes platform on Google Cloud. Defaults to Autopilot mode unless Standard is explicitly required.
Key Selection Rules: Autopilot vs. Standard
- **Default to Autopilot** for almost all workloads.
- **Use Standard ONLY if:**
- Custom node OS kernel parameters (`sysctl`) are required.
- Custom node taints or specific hardware node pools are required.
- DaemonSets require raw `hostPath` mounts to the host OS filesystem.
- When explaining why Standard is required over Autopilot, explicitly cite all matching restrictions (e.g., custom sysctls and custom node taints).
- *For advanced cluster architecture or complex node pool creation planning, refer to `gke-cluster-creation`.*
Critical Gotchas & Best Practices
1. **Private Autopilot Clusters:**
- Use `--enable-private-nodes` for private node IP addresses.
- Use `--enable-private-endpoint` to disable public IP access to the control plane.
- Restrict control plane access with `--enable-master-authorized-networks` and `--master-authorized-networks=CIDR_BLOCK`:
gcloud container clusters create-auto CLUSTER_NAME --region=REGION \
--enable-private-nodes \
--enable-private-endpoint \
--enable-master-authorized-networks \
--master-authorized-networks=CIDR_BLOCK2. **Workload Identity (IAM Binding):**
- Never mount raw GCP Service Account JSON keys in Pods.
- Annotate the Kubernetes ServiceAccount (`KSA`) to bind to the Google Service Account (`GSA`):
metadata:
annotations:
iam.gke.io/gcp-service-account: GSA_NAME@PROJECT_ID.iam.gserviceaccount.com3. **Autopilot Resource Requests:**
- In Autopilot, CPU requests must be specified in increments of 250m (0.25 vCPU). If an unaligned CPU request (e.g., 300m) is requested, round up to the nearest 250m increment (500m / 0.5 vCPU).
- Resource requests equal limits automatically. Omit `limits` to allow Autopilot to set defaults matching `requests`.
4. **Cluster Credentials:**
- Always explicitly specify `--region` (for regional clusters) or `--zone` (for zonal clusters) when fetching credentials:
gcloud container clusters get-credentials CLUSTER_NAME --region=REGION --quiet
Reference Directory
- [Core Concepts](references/core-concepts.md): Architecture, cluster modes (Autopilot vs Standard), networking, scaling, and security model.
- [CLI Usage & Tool Reference](references/cli-reference.md): Tool preference hierarchy (MCP vs gcloud vs kubectl), `gcloud container` commands, and user preference overrides.
- [Client Libraries](references/client-library-usage.md): Official Kubernetes and Google Cloud Container client libraries in Python, Go, Node.js, and Java.
- [MCP Usage](references/mcp-usage.md): Connecting to and using the 23 structured GKE MCP tools for cluster management, K8s resources, and diagnostics.
- [Infrastructure as Code](references/iac-usage.md): Terraform examples for `google_container_cluster` (Autopilot), Kubernetes provider resources, and YAML samples.
This repository contains Agent Skills for Google products and technologies, including Google Cloud. This repository is under active development.
Repo: google/skills
Other skills on google-skills.
- /data-manager-api-audience-ingestion
Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an
Open skill - /data-manager-api-event-ingestion
Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads,
Open skill - /data-manager-api-setup
Guides developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the
Open skill - /google-ads-api-account-diagnostics
Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share
Open skill - /google-ads-api-mcp-setup
Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve
Open skill - /google-ads-api-quickstart
Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USER_PERMISSION_DENIED, login_customer_id issues, and
Open skill

