Official agent skill

Gke Batch Hpc

Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing.

OfficialApache-2.0Auto-check passedDevOps & Cloud

Install Gke Batch Hpc

skills CLI

$ npx skills add google/skills --skill gke-batch-hpc -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install google/skills gke-batch-hpc --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/gke-batch-hpc .claude/skills/gke-batch-hpc && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "gke-batch-hpc" agent skill from https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc into .claude/skills/gke-batch-hpc/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gke-batch-hpc", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add google/skills --skill gke-batch-hpc -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install google/skills gke-batch-hpc --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/cloud/gke-batch-hpc .agents/skills/gke-batch-hpc && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "gke-batch-hpc" agent skill from https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc into .agents/skills/gke-batch-hpc/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gke-batch-hpc", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add google/skills --skill gke-batch-hpc -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install google/skills gke-batch-hpc --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/cloud/gke-batch-hpc .cursor/skills/gke-batch-hpc && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "gke-batch-hpc" agent skill from https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc into .cursor/skills/gke-batch-hpc/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gke-batch-hpc", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/google/skills.git --path skills/cloud/gke-batch-hpc

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add google/skills --skill gke-batch-hpc -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install google/skills gke-batch-hpc --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/cloud/gke-batch-hpc .gemini/skills/gke-batch-hpc && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "gke-batch-hpc" agent skill from https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc into .gemini/skills/gke-batch-hpc/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gke-batch-hpc", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install google/skills gke-batch-hpc

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add google/skills --skill gke-batch-hpc -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/cloud/gke-batch-hpc .github/skills/gke-batch-hpc && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "gke-batch-hpc" agent skill from https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc into .github/skills/gke-batch-hpc/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gke-batch-hpc", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add google/skills --skill gke-batch-hpc -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install google/skills gke-batch-hpc --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/cloud/gke-batch-hpc .opencode/skills/gke-batch-hpc && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "gke-batch-hpc" agent skill from https://github.com/google/skills/tree/main/skills/cloud/gke-batch-hpc into .opencode/skills/gke-batch-hpc/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gke-batch-hpc", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: gke-batch-hpc
GitHub stars: 21k
Token cost: ~1.4k tokens
SKILL.md length: 309 words
Files: 1
Skills in repo: 147
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing.

Running GKE batch jobs
SKILL.md covers When to Use, Batch Processing on GKE, HPC on GKE and Cost Optimization for Batch/HPC, plus 1 more section
Calls kubectl and gcloud; reaches github.com and raw.githubusercontent.com
Configuring GKE HPC

What it does

Gke Batch Hpc is an agent skill from google/skills, published by the product's own GitHub organization. Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead).

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Background jobs, Deployment and Container orchestration. It works with Google Kubernetes Engine and Kubernetes. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.

When your agent uses it

Running GKE batch jobs
Configuring GKE HPC
Setting up GKE job queues
Standard web application deployments (use gke-app-onboarding instead)

Example prompts

“/gke-batch-hpc”

What it can do on your machine

Read from SKILL.md and the folder at commit 7d97937. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- kubectl
- gcloud
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- github.com
- raw.githubusercontent.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gke Batch Hpc loads about 1.4k tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 309 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~66
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from google/skills at commit 7d97937, republished under its Apache-2.0 licence (© google). 309 words, ~1,425 tokens.

Download SKILL.mdSave it as .claude/skills/gke-batch-hpc/SKILL.md (or your agent's skills folder).

name: gke-batch-hpc
description: Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead).
metadata.version: 1.0.0
metadata.category: Containers

GKE Batch & HPC Workloads

This reference covers running batch processing and high-performance computing (HPC) workloads on GKE.

MCP Tools: apply_k8s_manifest, get_k8s_resource, describe_k8s_resource, get_k8s_logs, delete_k8s_resource, list_k8s_events

When to Use

Running batch data processing pipelines
HPC simulations (CFD, molecular dynamics, financial modeling)
Large-scale parallel computation (MPI, MapReduce)
ML training jobs
CI/CD build farms

Batch Processing on GKE

Kubernetes Jobs

yaml

apiVersion: batch/v1
kind: Job
metadata:
  name: batch-job
spec:
  parallelism: 10
  completions: 100
  backoffLimit: 3
  template:
    spec:
      containers:
      - name: worker
        image: <IMAGE>
        resources:
          requests:
            cpu: "1"
            memory: "2Gi"
      restartPolicy: Never

JobSet (for Complex Multi-Job Workflows)

The golden path enables JobSet monitoring (JOBSET in monitoringConfig).

yaml

apiVersion: jobset.x-k8s.io/v1alpha2
kind: JobSet
metadata:
  name: training-job
spec:
  replicatedJobs:
  - name: workers
    replicas: 4
    template:
      spec:
        parallelism: 1
        completions: 1
        template:
          spec:
            containers:
            - name: worker
              image: <IMAGE>
              resources:
                requests:
                  cpu: "4"
                  memory: "8Gi"

Kueue (Job Queuing)

Kueue manages job scheduling and resource allocation for batch workloads:

bash

# Install Kueue
kubectl apply --server-side -f https://github.com/kubernetes-sigs/kueue/releases/latest/download/manifests.yaml

yaml

# Define a ClusterQueue
apiVersion: kueue.x-k8s.io/v1beta1
kind: ClusterQueue
metadata:
  name: batch-queue
spec:
  namespaceSelector: {}
  resourceGroups:
  - coveredResources: ["cpu", "memory"]
    flavors:
    - name: default
      resources:
      - name: "cpu"
        nominalQuota: 100
      - name: "memory"
        nominalQuota: "200Gi"
---
# Allow a namespace to use the queue
apiVersion: kueue.x-k8s.io/v1beta1
kind: LocalQueue
metadata:
  name: batch-local
  namespace: batch-jobs
spec:
  clusterQueue: batch-queue

HPC on GKE

Compact Placement (Low-Latency Networking)

For tightly-coupled HPC workloads that need low-latency inter-node communication:

bash

# Standard clusters: create node pool with compact placement
gcloud container node-pools create hpc-pool \
  --cluster <CLUSTER_NAME> --region <REGION> \
  --machine-type c3-standard-44 \
  --placement-type COMPACT \
  --num-nodes 8 \
  --enable-autoscaling --min-nodes 0 --max-nodes 16 \
  --quiet

MPI Workloads

Use the MPI Operator for MPI-based HPC applications:

bash

# Install MPI Operator
kubectl apply -f https://raw.githubusercontent.com/kubeflow/mpi-operator/master/deploy/v2beta1/mpi-operator.yaml

yaml

apiVersion: kubeflow.org/v2beta1
kind: MPIJob
metadata:
  name: hpc-simulation
spec:
  slotsPerWorker: 4
  mpiReplicaSpecs:
    Launcher:
      replicas: 1
      template:
        spec:
          containers:
          - name: launcher
            image: <MPI_IMAGE>
            command: ["mpirun", "-np", "32", "./simulation"]
            resources:
              requests:
                cpu: "1"
                memory: "2Gi"
              limits:
                cpu: "2"
                memory: "4Gi"
    Worker:
      replicas: 8
      template:
        spec:
          containers:
          - name: worker
            image: <MPI_IMAGE>
            resources:
              requests:
                cpu: "4"
                memory: "8Gi"
              limits:
                cpu: "8"
                memory: "16Gi"

Cost Optimization for Batch/HPC

Spot VMs for Batch

Batch workloads are ideal Spot VM candidates (interruptible, can checkpoint). Use a ComputeClass with Spot-first priority and activeMigration to return to Spot when available. See the gke-compute-classes skill for the Spot-with-fallback pattern.

Scale-to-Zero

For batch clusters, allow node pools to scale to zero when no jobs are running:

Autopilot (golden path): Automatic, nodes scale to zero when no pods are scheduled
Standard: Set --min-nodes 0 on batch node pools

Best Practices & Production Guidelines

Resource Quotas: Always specify resource requests and limits (CPU, memory, and optionally GPU/TPU) for all batch/HPC manifests. This is critical for Kueue admission, autoscaling, and preventing resource starvation in the cluster.
TPU/Spot Cluster Maintenance: For long-running AI training runs on Spot VMs/TPUs, advise using GKE maintenance exclusions to block automatic cluster upgrades/reboots during the active training window to minimize unnecessary preemption.
MPI Workloads: Use the Kubeflow Training Operator to orchestrate distributed MPI applications via the MPIJob custom resource.
Kueue & JobSet: Use Kueue for multi-tenant job queueing and fair sharing; use JobSet for multi-component tightly coupled workloads.
Resilience: Always set a backoffLimit on Jobs, and implement application-level checkpointing (e.g., using Orbax or PyTorch checkpointing) to survive Spot VM preemption.

Files

Just SKILL.md in skills/cloud/gke-batch-hpc of google/skills.

Open the folder on GitHubat commit 7d97937

Compare with similar skills

Gke Batch Hpc next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Gke Batch Hpc compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Gke Batch Hpc this skillgoogle/skills	21k	—	~1.4k	Automated safety check: Pass	Apache-2.0	today
Mirrord Operatoraiskillstore/marketplace	430	—	~4.6k	Automated safety check: Pass	None	yesterday
KubeShark for KubernetesLukasNiessen/kubernetes-skill	444	—	~1.2k	Automated safety check: Pass	MIT	25 days ago
Kcli Cluster Deploymentkarmab/kcli	653	—	~1.5k	Automated safety check: Pass	Apache-2.0	yesterday
Deploying Cloud K8saiskillstore/marketplace	430	—	~2.1k	Automated safety check: Pass	None	yesterday
Akka.NET Management and DiscoveryAaronontheweb/dotnet-skills	1.2k	1 repos	~2.5k	Automated safety check: Pass	MIT	20 days ago

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Questions about Gke Batch Hpc

What does Gke Batch Hpc do?

Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Gke Batch Hpc is an agent skill from google/skills, published by the product's own GitHub organization. Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing.

When should I use Gke Batch Hpc?

Gke Batch Hpc fits situations like: running GKE batch jobs; configuring GKE HPC; setting up GKE job queues; standard web application deployments (use gke-app-onboarding instead).

How do I install Gke Batch Hpc in Claude Code?

Run `npx skills add google/skills --skill gke-batch-hpc -a claude-code`. Or copy the skill folder (skills/cloud/gke-batch-hpc in google/skills) into .claude/skills/gke-batch-hpc in your project. Claude Code loads it when a task matches its description.

How do I install Gke Batch Hpc in Codex?

Run `npx skills add google/skills --skill gke-batch-hpc -a codex`. Or copy the skill folder (skills/cloud/gke-batch-hpc in google/skills) into .agents/skills/gke-batch-hpc in your project. Codex loads it when a task matches its description.

Can I use Gke Batch Hpc in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill gke-batch-hpc -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gke-batch-hpc, .gemini/skills/gke-batch-hpc, .github/skills/gke-batch-hpc and .opencode/skills/gke-batch-hpc in your project.

What does Gke Batch Hpc need to run?

Going by SKILL.md and its folder, Gke Batch Hpc needs the command-line tools its instructions call (kubectl and gcloud).

Does Gke Batch Hpc access the network?

SKILL.md names 2 domains. In commands or code: github.com and raw.githubusercontent.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Gke Batch Hpc safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Gke Batch Hpc use?

Gke Batch Hpc is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gke Batch Hpc use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Gke Batch Hpc?

Skills that share tags, products or a category with Gke Batch Hpc: Mirrord Operator (aiskillstore/marketplace, 430 stars), KubeShark for Kubernetes (LukasNiessen/kubernetes-skill, 444 stars), Kcli Cluster Deployment (karmab/kcli, 653 stars) and Deploying Cloud K8s (aiskillstore/marketplace, 430 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gke Batch Hpc?

google (a GitHub organization, an official publisher) maintains it in google/skills, which has 21,032 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on October 8, 2026.

Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Gke Batch Hpc

Facts

At a glance

What it does

When your agent uses it

Example prompts

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

GKE Batch & HPC Workloads

When to Use

Batch Processing on GKE

Kubernetes Jobs

JobSet (for Complex Multi-Job Workflows)

Kueue (Job Queuing)

HPC on GKE

Compact Placement (Low-Latency Networking)

MPI Workloads

Cost Optimization for Batch/HPC

Spot VMs for Batch

Scale-to-Zero

Best Practices & Production Guidelines

Files

Compare with similar skills

Similar skills

More from google/skills

Related

Questions about Gke Batch Hpc