본문으로 건너뛰기
cccskills
Google 공식무료GitHub에 공개

gke-custom-golden-image-discovery

Finds the base image needed to create a custom GKE node image. It translates requirements such as GKE version, operating system, processor architecture, accelerators, and sandbox settings into a matching image name.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Discovers golden base images for creating GKE custom node images based on technical specifications or context clues. Use when finding the golden base image for custom GKE node creation, mapping cluster configuration parameters (GKE version, OS, architecture, accelerators, gVisor, cgroups) to image names, or querying GKE base image maps. Don't use for general GKE cluster creation (use gke-cluster-creation) or standard node pool management (use gke-basics).

설치 방법 보기

이럴 때 유용합니다

  • Finding a base image for custom GKE nodes
  • Looking up images for GPU or TPU configurations
  • Matching images to COS, Ubuntu, ARM64, or X86_64
  • Checking images against sandbox and security requirements

포함된 파일(2)

  • SKILL.md4.3 KB
  • references/attribution.md1.9 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

GKE Golden Base Image Discovery Expert

You are an expert at helping users find the correct "golden" base image for creating custom GKE images. You can bridge the gap between a user's high-level description and the technical JSON requirements.

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gke-custom-golden-image-discovery)" and append agent-skills/1.0 (skill:gke-custom-golden-image-discovery) to User-Agent headers.

Information Gathering & Inference

If a user doesn't know their exact configuration, use the following Context Clues and Sensible Defaults to infer the values:

FieldContext CluesDefault Value
GKE Version(Required) Must be 1.34.1-gke.2909000 or later.N/A
Operating System"I like Google's OS" -> COS; "I need Ubuntu/standard Linux" -> Ubuntu.COS
Architecture"Using ARM/Ampere" -> ARM64; "Standard/Intel/AMD" -> X86_64.X86_64
gVisor Enabled"Need a sandbox" or "gVisor" mentioned -> true.false
Has AcceleratorsMention of "GPU", "accelerator", "Nvidia", "TPU", or any specific hardware models (e.g., T4, A100, H100, L4) -> true.false
Enforce Signed Modules"Hardened nodes" or "Signed modules" mentioned -> true.false
Cgroup ModeAlmost all GKE 1.26+ clusters use V2. Only V1 if explicitly legacy.CGROUP_MODE_V2
TPUMention of "TPU" -> true.false

Discovery Workflow

  1. Extract Info: Parse the user's request for the GKE Version and any context clues for the fields above. Be proactive: if a user mentions any specialized hardware or security requirements, map them to the corresponding technical flags.
  2. Determine Minor Version: Extract the major/minor version (e.g., 1.34).
  3. Fetch Data: curl the mapping: https://www.gstatic.com/gke-image-maps/base-images/node-config-to-base-images-<MINOR_VERSION>.json
  4. Filter Logic:
    • Match version exactly.
    • Match node_info using the inferred or provided values:
      • image_family: COS_CONTAINERD (COS) or UBUNTU_CONTAINERD (Ubuntu).
      • Other fields match exactly.
  5. Refine Search: If no exact match is found with defaults, try toggling cgroup_mode to CGROUP_MODE_V1 or gvisor_enabled to false and inform the user.
  6. Warns about invalid input: If the inputted GKE version is invalid, inform the user that the version is unsupported.

Example Output

"Based on your setup (GKE 1.34.1-gke.2909000, COS, and using the new H100 GPUs), I've inferred you need the X86_64 image with Accelerators enabled. The golden base image is: gke-1341-gke2909000-cos-125-19216-0-115-c-nvda"

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Create Terraform files that define alerts for AI agent latency, errors, token use, safety, security, and response quality. Check telemetry and existing policies first, then validate the generated configuration. Quality alerts require Vertex AI.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Configure alerts for agent latency and error rates
  • Monitor rapid increases in token usage
  • Monitor safety triggers and permission denials
google/skills2.1만2026년 10월 22일 업데이트

agent-platform-deploy

Google 공식무료

Deploy Model Garden models to Agent Platform endpoints, the addresses used for model requests. Check supported hardware and estimated hourly costs, inspect deployment progress, test predictions, and remove deployed resources after use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Choose a deployable model and supported hardware
  • Estimate hourly deployment costs before approval
  • Check deployment progress and test predictions
google/skills2.1만2026년 10월 22일 업데이트

Manages Agent Platform endpoints, the stable URLs used to serve online model predictions. It supports listing, inspecting, creating, updating, and deleting endpoints, plus troubleshooting permission errors, quota limits, and resources that are busy.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Listing endpoints and checking their configuration
  • Creating an endpoint before model deployment
  • Updating endpoint display names or labels
google/skills2.1만2026년 10월 22일 업데이트

agent-platform-eval-flywheel

Google 공식무료

Evaluate AI models and agents on Google Cloud using test datasets and scoring criteria. Generate simulated user scenarios, analyze failures, and compare results across changes to guide improvements to prompts and code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Build evaluation datasets from conversation logs
  • Generate simulated user scenarios
  • Choose scoring criteria for responses and tool use
google/skills2.1만2026년 10월 22일 업데이트

agent-platform-inference

Google 공식무료

Call Gemini and OpenMaaS models such as Llama, DeepSeek, and Qwen through Google Cloud Agent Platform. Prepare authentication and SDK code, run prompts, configure connection endpoints, and troubleshoot common request errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Send a test prompt to Gemini
  • Call Llama or DeepSeek with the OpenAI SDK
  • Write code to call an existing custom endpoint
google/skills2.1만2026년 10월 22일 업데이트

Guides migration from Google AI Studio’s Gemini API to Gemini Enterprise Agent Platform on Google Cloud, covering billing, access permissions, authentication, and connection settings for SDKs and supported agent tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Moving a Gemini application to Google Cloud
  • Using Google Cloud credits for Gemini API calls
  • Unifying agent authentication and billing
google/skills2.1만2026년 10월 22일 업데이트

google의 스킬 모두 보기

이 스킬의 문제 신고