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gke-storage

Manages GKE storage, including PVCs, PersistentVolumes, Filestore, and GCS FUSE. Use when configuring GKE storage, creating PVCs, or setting up GCS FUSE on GKE. For diagnosing storage failures (volume attach/mount errors, disk performance/node storage pressure, or Cloud Storage FUSE OOM), use the gke-storage-troubleshooting skill instead. Don't use for database administration or replication strategies outside volume provisioning context.

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vaila-multimodaltoolbox/vaila

연동 도구Kubernetes

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GKE Storage

This reference covers storage configuration for GKE clusters including persistent disks, file storage, and cloud storage integration.

MCP Tools: apply_k8s_manifest, get_k8s_resource, describe_k8s_resource, get_cluster

Golden Path Storage Defaults

The golden path Autopilot config enables these CSI drivers:

Driver	Golden Path	Access Mode	Use Case
Compute Engine	Enabled (default)	ReadWriteOnce	Block storage for
: Persistent Disk : : : databases, :
: CSI : : : single-pod workloads :
Google Cloud	Enabled	ReadWriteMany	Shared NFS for
: Filestore CSI : : : multi-pod access :
Cloud Storage	Enabled	ReadWriteMany /	Mount GCS buckets as
: FUSE CSI : : ReadOnlyMany : volumes :
Parallelstore	Enabled	ReadWriteMany	High-performance
: CSI : : : parallel file system :
Boot disk type	`pd-balanced`	N/A	Node boot disks

StorageClasses

Default StorageClasses

GKE provides built-in StorageClasses:

StorageClass	Disk Type	Use Case
`standard-rwo`	`pd-standard`	Cost-effective, low IOPS
`premium-rwo`	`pd-ssd`	High IOPS, databases
`standard-rwx`	Filestore (Basic HDD)	Shared NFS
`premium-rwx`	Filestore (Basic SSD)	Shared NFS, higher performance

Custom StorageClass

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: fast-regional
provisioner: pd.csi.storage.gke.io
parameters:
  type: pd-ssd
  replication-type: regional-pd    # Replicate across 2 zones
volumeBindingMode: WaitForFirstConsumer
allowVolumeExpansion: true         # Always enable for production

PersistentVolumeClaims

Block Storage (ReadWriteOnce)

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: database-pvc
spec:
  accessModes:
  - ReadWriteOnce
  storageClassName: premium-rwo
  resources:
    requests:
      storage: 100Gi

Shared File Storage (ReadWriteMany via Filestore)

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: shared-data
spec:
  accessModes:
  - ReadWriteMany
  storageClassName: standard-rwx
  resources:
    requests:
      storage: 1Ti    # Filestore minimum is 1 TiB for Basic tier

GCS Bucket Mount (Cloud Storage FUSE)

Mount a GCS bucket as a volume without a PVC:

apiVersion: v1
kind: Pod
metadata:
  name: gcs-reader
  annotations:
    gke-gcsfuse/volumes: "true"
spec:
  containers:
  - name: reader
    image: busybox
    command: ["ls", "/data"]
    volumeMounts:
    - name: gcs-bucket
      mountPath: /data
  volumes:
  - name: gcs-bucket
    csi:
      driver: gcsfuse.csi.storage.gke.io
      readOnly: true
      volumeAttributes:
        bucketName: <BUCKET_NAME>

Requires Workload Identity for the pod's service account to have storage.objectViewer on the bucket.

Volume Expansion

If allowVolumeExpansion: true is set on the StorageClass, resize by updating the PVC:

# kubectl
kubectl patch pvc <PVC_NAME> -p '{"spec":{"resources":{"requests":{"storage":"200Gi"}}}}'

# MCP (preferred)
patch_k8s_resource(parent="...", resourceType="persistentvolumeclaim", name="<PVC_NAME>",
  patch='{"spec":{"resources":{"requests":{"storage":"200Gi"}}}}')

Kubernetes automatically resizes the filesystem.

Best Practices

Always enable volume expansion: Set allowVolumeExpansion: true on all StorageClasses
Use regional PDs for production: replication-type: regional-pd replicates across 2 zones for HA
Use WaitForFirstConsumer: Ensures the PV is provisioned in the same zone as the pod
Choose the right disk type: pd-ssd for databases, pd-balanced (golden path default) for general use, pd-standard for cold storage
Use Filestore for shared access: When multiple pods need to read/write the same files
Use GCS FUSE for data pipelines: Mount buckets directly for ML training data, logs, etc.
Back up PVCs: Use Backup for GKE (see the gke-backup-dr skill) to protect persistent data

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같은 저장소의 스킬

agent-platform-alert-configuration

무료

Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.

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vaila-multimodaltoolbox/vaila212026년 10월 20일 업데이트

agent-platform-deploy

무료

Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for public Vertex AI deployments (use the `vertex-deploy` skill) or for running model evaluations (use the `agent-platform-eval-flywheel` skill).

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vaila-multimodaltoolbox/vaila212026년 10월 20일 업데이트

agent-platform-endpoint-management

무료

Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vaila-multimodaltoolbox/vaila212026년 10월 20일 업데이트

agent-platform-eval-flywheel

무료

Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.

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vaila-multimodaltoolbox/vaila212026년 10월 20일 업데이트

agent-platform-inference

무료

Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.

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vaila-multimodaltoolbox/vaila212026년 10월 20일 업데이트

agent-platform-migrate-from-ai-studio

무료

Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).

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vaila-multimodaltoolbox/vaila212026년 10월 20일 업데이트

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설치

명령으로 설치

npx skills add https://github.com/vaila-multimodaltoolbox/vaila --skill gke-storage

터미널에 붙여 넣고 실행합니다(Node.js 필요). Claude Code, Codex 등 설치할 에이전트를 고를 수 있습니다.

에이전트에게 부탁하기

다음 Agent Skill을 설치해 주세요.
https://github.com/vaila-multimodaltoolbox/vaila/tree/main/.agents/skills/gke-storage

먼저 SKILL.md와 첨부 파일의 내용을 확인해 수상한 처리(외부 전송, 인증 정보 읽기 등)가 없는지 확인한 뒤 Claude Code는 ~/.claude/skills/gke-storage/, Codex는 ~/.agents/skills/gke-storage/ 에 배치해 주세요.

이 문장을 그대로 Claude Code나 Codex에 보내면 내용을 확인한 뒤 설치해 줍니다.

GitHub에서 소스 보기

저장소: vaila-multimodaltoolbox/vaila
스타: 21
포크: 9
카테고리: 인프라·DevOps
라이선스: AGPL-3.0
원문 언어: 영어
최종 업데이트: 2026년 10월 20일

스킬은 에이전트를 위한 지시와 스크립트의 묶음입니다. cccskills는 내용의 안전성을 보증하지 않습니다. 설치하기 전에 내용을 확인하세요.