gitlab-ci-patterns
Build GitLab CI/CD Pipelines with Multi-Stage Workflows
Também disponível em: wshobson
Manual GitLab CI pipeline creation is time-consuming and error-prone. This skill provides proven patterns for multi-stage workflows, caching strategies, and deployment automation.
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Testar
A utilizar "gitlab-ci-patterns". Create a basic GitLab CI pipeline for a Python project
Resultado esperado:
Generates a .gitlab-ci.yml with stages for linting, testing, and building, including pytest configuration, coverage reporting, and artifact collection.
A utilizar "gitlab-ci-patterns". Set up Kubernetes deployment from GitLab CI
Resultado esperado:
Produces deployment jobs with kubectl configuration, environment definitions, rollout status checks, and proper namespace targeting for staging and production.
Auditoria de Segurança
SeguroStatic analyzer flagged 24 potential issues, all determined to be false positives. External command detections are markdown code block delimiters, not actual shell execution. URL references are documentation examples in YAML templates. No cryptographic code exists. This is a safe documentation skill with GitLab CI YAML examples.
Pontuação de qualidade
O Que Você Pode Construir
DevOps Engineer Setting Up New Project
Quickly establish a complete CI/CD pipeline with testing, building, and deployment stages following GitLab best practices.
Development Team Migrating to GitLab
Convert existing CI workflows to GitLab CI format with equivalent functionality and improved caching strategies.
Platform Engineer Building Templates
Create reusable pipeline templates and configurations for multiple projects within an organization.
Tente Estes Prompts
Create a GitLab CI pipeline for a Node.js project with build, test, and deploy stages. Include caching for node_modules and artifact collection for the dist folder.
Generate a GitLab CI job that builds a Docker image, tags it with the commit SHA and latest, and pushes to the GitLab container registry.
Create GitLab CI jobs for deploying to staging and production environments. Staging should deploy automatically on develop branch, production requires manual approval on main branch.
Design a complete Terraform pipeline with validation, planning, and apply stages. Include proper artifact handling for plans and manual approval for production changes.
Melhores Práticas
- Use specific image tags instead of latest to ensure reproducible builds
- Cache dependencies appropriately to reduce pipeline execution time
- Implement manual approval gates for production deployments
Evitar
- Storing secrets directly in .gitlab-ci.yml instead of using CI/CD variables
- Using overly broad artifact paths that bloat pipeline storage
- Skipping test stages to speed up pipelines, compromising code quality
Perguntas Frequentes
How do I securely store API keys and credentials in GitLab CI?
What is the difference between cache and artifacts in GitLab CI?
How do I trigger a pipeline only on specific branches?
Can I run multiple jobs in parallel in GitLab CI?
How do I create a pipeline that runs on a schedule?
What are GitLab CI templates and how do I use them?
Detalhes do Desenvolvedor
Autor
sickn33Licença
MIT
Repositório
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/gitlab-ci-patternsReferência
main
Estrutura de arquivos
📄 SKILL.md