본문으로 건너뛰기
cccskills
무료GitHub에 공개

gke-workload-security

Audit and strengthen security for applications running on GKE. Configure pod traffic restrictions, sandbox isolation, namespace security standards, and Secret Manager volume mounts to protect workloads at the application and namespace level.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).

설치 방법 보기

이럴 때 유용합니다

  • Auditing GKE security settings
  • Restricting communication within a namespace
  • Isolating risky pods and applying security standards
  • Mounting Secret Manager secrets as pod volumes

포함된 파일(4)

  • SKILL.md7.6 KB
  • assets/default-deny-netpol.yaml235 B
  • assets/workload-identity-pod.yaml1.2 KB
  • scripts/audit_cluster.sh2.2 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

GKE Workload Security

Routing Note: For Workload Identity KSA/GSA bindings, open gke-workload-identity/SKILL.md. For cluster-level security flags (--database-encryption-key, --security-posture, RBAC, Shielded Nodes, Binary Authorization), open gke-platform-security/SKILL.md.

This skill provides workflows and best practices for securing GKE workloads. It covers security auditing, Identity and Access Management (Workload Identity), Network Security (Network Policies), and Node Security.

Workflows

1. Security Audit

Assess the current security posture of your cluster using the provided audit script.

Prerequisites:

  • gcloud CLI authenticated.
  • jq command-line JSON processor installed.

Capabilities:

  • Checks for Workload Identity.
  • Verifies Network Policy is enabled.
  • Checks if Shielded Nodes are enabled.
  • Checks if Binary Authorization is enabled.
  • Checks for Private Cluster configuration.

Command:

scripts/audit_cluster.sh <cluster-name> <region> <project-id>

2. Configure Workload Identity

Workload Identity allows Kubernetes Service Accounts (KSAs) to impersonate Google Service Accounts (GSAs). This is the recommended method for workloads to access Google Cloud APIs.

Steps:

  1. Create Namespace and KSA:

    kubectl create namespace workload-identity-test-ns
    kubectl create serviceaccount <ksa-name> \
        --namespace workload-identity-test-ns
    
  2. Bind KSA to GSA:

    gcloud iam service-accounts add-iam-policy-binding <gsa-name>@<project-id>.iam.gserviceaccount.com \
        --role roles/iam.workloadIdentityUser \
        --member "serviceAccount:<project-id>.svc.id.goog[workload-identity-test-ns/<ksa-name>]"
    
  3. Annotate KSA:

    kubectl annotate serviceaccount <ksa-name> \
        --namespace workload-identity-test-ns \
        iam.gke.io/gcp-service-account=<gsa-name>@<project-id>.iam.gserviceaccount.com
    
  4. Verify Example Pod: Use existing asset assets/workload-identity-pod.yaml to test the configuration. Update the <ksa-name> in the file first.

    kubectl apply -f assets/workload-identity-pod.yaml -n workload-identity-test-ns
    

3. Implement Network Policies

Control traffic flow between Pods using Network Policies. By default, all traffic is allowed.

Enable Network Policy Enforcement:

gcloud container clusters update <cluster-name> \
    --update-addons=NetworkPolicy=ENABLED \
    --region <region>

[!NOTE] If your cluster uses Dataplane V2 (--enable-dataplane-v2), Network Policy enforcement is built-in and this step is not required (and may fail).

Apply Default Deny Policy: Isolate namespaces by denying all ingress and egress traffic by default.

Replace <target-namespace> with the namespace you want to isolate.

kubectl apply -f assets/default-deny-netpol.yaml -n <target-namespace>

4. GKE Sandbox (gVisor) Pod Isolation

Run untrusted workloads in a sandbox for extra kernel isolation. (Note: Enabling Shielded Nodes (--enable-shielded-nodes) and GKE Sandbox (--enable-gke-sandbox) at the cluster control plane level are platform-level actions covered in the gke-platform-security skill.)

Run a Sandboxed Pod: Add runtimeClassName: gvisor to your Pod spec:

apiVersion: v1
kind: Pod
metadata:
  name: sandboxed-pod
spec:
  runtimeClassName: gvisor
  containers:
  - name: app
    image: nginx

5. Pod Security Standards

Enforce security policies on namespaces using labels.

Enforce Restricted Profile:

kubectl label --overwrite ns <namespace> \
    pod-security.kubernetes.io/enforce=restricted \
    pod-security.kubernetes.io/enforce-version=latest

[!NOTE] Using latest ensures you use the policies corresponding to the cluster's current version. You can pin it to a specific version (e.g., v1.30) to lock down the namespace to policies of a specific release.

6. Secret Manager Integration (CSI Driver)

Mount secrets from Google Cloud Secret Manager directly as volumes in your pods.

Prerequisites: Secret Manager CSI driver must be enabled on the cluster.

Example SecretProviderClass:

apiVersion: secrets-store.csi.x-k8s.io/v1
kind: SecretProviderClass
metadata:
  name: my-secret-provider
spec:
  provider: gcp
  parameters:
    secrets: |
      - resourceName: "projects/<project-id>/secrets/my-secret/versions/latest"
        fileName: "my-secret-file"

Example Pod Spec excerpt:

spec:
  containers:
    - name: my-app
      volumeMounts:
        - name: secrets-store-inline
          mountPath: "/mnt/secrets"
          readOnly: true
  volumes:
    - name: secrets-store-inline
      csi:
        driver: secrets-store.csi.k8s.io
        readOnly: true
        volumeAttributes:
          secretProviderClass: "my-secret-provider"

7. Enable Network Policy Logging

If using GKE Dataplane V2, you can log allowed and denied connections.

Steps:

  1. Configure the NetworkLogging custom resource.

Example NetworkLogging Manifest:

apiVersion: networking.gke.io/v1alpha1
kind: NetworkLogging
metadata:
  name: default
spec:
  cluster:
    allow:
      log: true
      delegate: true
    deny:
      log: true
      delegate: true

This will log connection details to Cloud Logging.

Best Practices

  1. Least Privilege: Always use Workload Identity with minimal IAM roles. Avoid using Node default service accounts.
  2. Network Isolation: Use Network Policies to restrict Pod-to-Pod communication. Enable Network Policy Logging for visibility.
  3. Image Security: Use Binary Authorization to ensure only trusted images are deployed.
  4. Secret Management: Use Secret Manager CSI driver instead of default Kubernetes secrets for sensitive data.
  5. Pod Security: Enforce baseline or restricted Pod Security Standards on all non-system namespaces.
  6. Policy Enforcement: Consider using Policy Controller (Gatekeeper) to enforce custom security and compliance policies across the cluster.

Resources

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 17일 업데이트

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 17일 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 17일 업데이트

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 17일 업데이트

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 17일 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 17일 업데이트

google의 스킬 모두 보기

이 스킬의 문제 신고