Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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Configure GitLab CI/CD pipelines and runners for automated building, testing, and deployment. Create .gitlab-ci.yml configurations, manage runners, and implement DevOps workflows. Use when working with GitLab repositories or self-hosted GitLab instances.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Automate your software delivery pipeline with GitLab's integrated CI/CD system.
Use this skill when:
Create .gitlab-ci.yml in repository root:
stages:
- build
- test
- deploy
variables:
NODE_VERSION: "20"
build:
stage: build
image: node:${NODE_VERSION}
script:
- npm ci
- npm run build
artifacts:
paths:
- dist/
expire_in: 1 hour
test:
stage: test
image: node:${NODE_VERSION}
script:
- npm ci
- npm test
coverage: '/Coverage: \d+\.\d+%/'
deploy:
stage: deploy
script:
- ./deploy.sh
environment:
name: production
url: https://example.com
only:
- main
deploy:
script: ./deploy.sh
rules:
- if: $CI_COMMIT_BRANCH == "main"
when: manual
- if: $CI_PIPELINE_SOURCE == "merge_request_event"
when: never
- when: on_success
test:
stage: test
parallel: 3
script:
- npm test -- --shard=$CI_NODE_INDEX/$CI_NODE_TOTAL
test:
stage: test
parallel:
matrix:
- NODE_VERSION: ["18", "20", "22"]
OS: ["alpine", "slim"]
image: node:${NODE_VERSION}-${OS}
script:
- npm test
cache:
key:
files:
- package-lock.json
paths:
- node_modules/
policy: pull-push
build:
cache:
key: build-cache
paths:
- .cache/
policy: pull
build:
artifacts:
paths:
- dist/
- coverage/
reports:
junit: junit.xml
coverage_report:
coverage_format: cobertura
path: coverage/cobertura.xml
expire_in: 1 week
when: always
deploy_staging:
stage: deploy
script:
- deploy --env staging
environment:
name: staging
url: https://staging.example.com
on_stop: stop_staging
stop_staging:
stage: deploy
script:
- undeploy --env staging
environment:
name: staging
action: stop
when: manual
build_image:
stage: build
image: docker:24
services:
- docker:24-dind
variables:
DOCKER_TLS_CERTDIR: "/certs"
script:
- docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
- docker build -t $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA .
- docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
# Download and install
curl -L https://packages.gitlab.com/install/repositories/runner/gitlab-runner/script.deb.sh | sudo bash
sudo apt install gitlab-runner
# Register runner
sudo gitlab-runner register \
--url https://gitlab.com/ \
--registration-token TOKEN \
--executor docker \
--docker-image alpine:latest
# /etc/gitlab-runner/config.toml
[[runners]]
name = "docker-runner"
url = "https://gitlab.com/"
token = "TOKEN"
executor = "docker"
[runners.docker]
image = "alpine:latest"
privileged = true
volumes = ["/cache", "/var/run/docker.sock:/var/run/docker.sock"]
build:
tags:
- docker
- linux
script:
- make build
Define in Settings > CI/CD > Variables:
AWS_ACCESS_KEY_ID (protected, masked)AWS_SECRET_ACCESS_KEY (protected, masked)deploy:
script:
- aws s3 sync dist/ s3://$S3_BUCKET
variables:
AWS_DEFAULT_REGION: us-east-1
include:
- template: Security/SAST.gitlab-ci.yml
- project: 'group/shared-ci'
file: '/templates/deploy.yml'
- local: '/ci/jobs.yml'
.base_job:
image: node:20
before_script:
- npm ci
build:
extends: .base_job
script:
- npm run build
test:
extends: .base_job
script:
- npm test
trigger_downstream:
stage: deploy
trigger:
project: group/downstream-project
branch: main
strategy: depend
Problem: Jobs stay pending Solution: Check runner availability and tags matching
Problem: Cannot connect to Docker daemon
Solution: Use docker:dind service with proper TLS configuration
Problem: Cache misses between jobs Solution: Verify cache key and ensure runners share distributed cache
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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
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Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
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Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
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Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
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Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
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