Results for “gitlab-ci”

Build a GitLab CI/CD pipeline with automated checks for vulnerable code, dependencies, container images, running applications, and exposed secrets. Covers scanner configuration, consolidated findings, and approval policies for serious vulnerabilities before production deployment.

• Add automated security scans to .gitlab-ci.yml
• Check dependencies and container images for known vulnerabilities
• Detect credentials and API keys committed to source control

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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Validate, lint, audit, or fix .gitlab-ci.yml pipelines, stages, and jobs.

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Create, generate, or scaffold .gitlab-ci.yml pipelines, stages, and jobs.

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Use this skill when authoring or debugging GitLab CI/CD pipelines (.gitlab-ci.yml) — e.g. "add a CI pipeline for this Drupal project", "run phpcs/phpstan/phpunit in GitLab CI", "deploy with drush from a pipeline", "why is my job not running", "cache composer dependencies", or anything involving stages, rules, artifacts, environments, or GitLab runners.

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Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.

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Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret Tespit.

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Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.

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Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.

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Build GitLab workflows that automate building, testing, and deployment. The skill covers pipeline stages, dependency caching, runners that execute jobs, and manual approval before production deployment, with examples for Docker, Kubernetes, and Terraform.

• Automating builds and tests in GitLab
• Reviewing caches to improve pipeline performance
• Separating staging and production deployments

Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

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Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

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Generate and optimize CI/CD pipelines for GitLab CI and CircleCI. Use when a user asks to set up GitLab CI, create a CircleCI pipeline, build a CI pipeline for GitLab, automate deployments with CircleCI, add test automation to GitLab, or configure continuous integration on non-GitHub platforms. For GitHub Actions pipelines, use the github-actions skill instead.

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World-class continuous integration and deployment - GitHub Actions, GitLab CI, deployment strategies, and the battle scars from pipelines that broke productionUse when "ci/cd, cicd, pipeline, github actions, gitlab ci, circleci, jenkins, workflow, deployment, deploy, release, blue green, canary, rollback, build, test automation, continuous integration, continuous deployment, cicd, github-actions, gitlab-ci, deployment, automation, devops, pipelines, continuous-integration, continuous-deployment" mentioned.

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CI/CD is the backbone of modern software delivery. Continuous Integration catches bugs early. Continuous Deployment gets features to users fast. But poorly designed pipelines can be slow, flaky, and a source of constant frustration. This skill covers GitHub Actions (the most popular), GitLab CI, and general pipeline design principles. The focus is on pipelines that are fast, reliable, and maintainable. 2025 reality: Your pipeline is infrastructure code. It deserves the same care as your application. A flaky test in CI is worse than no test - it teaches developers to ignore failures. Use when "github actions, gitlab ci, ci cd, pipeline, workflow, deploy automation, continuous integration, continuous deployment, build pipeline, yaml workflow, ci-cd, github-actions, gitlab-ci, devops, automation, deployment, pipelines" mentioned.

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Use when designing or validating GitLab CI/CD and automatic release lifecycles, inspecting pipeline and job state read-only, composing non-interactive merge-request commands, or setting up protected refs and release credentials. Also covers reusable components and inputs, GitLab Functions, gitlab-ci-local, glab command composition, and GitLab Flavored Markdown. For pipeline execution or retry requests, provide inspection and command drafting while leaving execution to the operator.

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スケーラブルな自動化のためのマルチステージワークフロー、キャッシング、分散ランナーを備えたGitLab CI/CDパイプラインを構築。GitLab CI/CDの実装、パイプラインパフォーマンスの最適化、または自動テストとデプロイメントのセットアップ時に使用。

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Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

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Expert en CI/CD pipeline v2 (GitHub Actions, GitLab CI, Jenkins, ArgoCD, progressive delivery)

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Expert en pipelines CI/CD (GitHub Actions, GitLab CI, Jenkins, ArgoCD, progressive delivery)

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