Is it compatible with private GitLab Runners?

Yes, the patterns are designed to work across both shared GitLab.com runners and distributed private runners, including configurations for Docker-in-Docker (DinD).

Can it help with cloud infrastructure deployments?

Yes, it includes specific patterns for Terraform plan/apply workflows and multi-environment Kubernetes deployments via kubectl and environment tracking.

Does it support automated security scanning?

Absolutely, it provides ready-to-use templates for GitLab SAST, Dependency Scanning, and Trivy container image scanning to catch vulnerabilities early.

How does this skill improve GitLab pipeline performance?

It implements sophisticated caching strategies, such as branch-specific slugs and pull-push policies, to minimize redundant dependency downloads and speed up job execution.

GitLab CI Pipeline Patterns

Name: GitLab CI Pipeline Patterns
Author: Microck

byMicrock

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Deployment & DevOps

Streamlines the creation of high-performance GitLab CI/CD pipelines with multi-stage workflows and optimized caching strategies.

About

This skill provides Claude with standardized patterns for architecting, optimizing, and maintaining GitLab CI/CD pipelines. It includes production-ready templates for containerized builds, multi-environment Kubernetes deployments, Infrastructure as Code with Terraform, and integrated security scanning. Whether you are migrating from another CI tool or fine-tuning existing runners for performance, this skill ensures industry best practices like artifact management, specific image tagging, and efficient dependency caching are applied consistently across your DevOps workflows.

Key Features

Optimized caching and artifact management to reduce runner execution time
Security-first templates for SAST, dependency scanning, and Trivy audits
Native patterns for Docker builds, Kubernetes rollouts, and Terraform workflows
Multi-stage pipeline architecture for build, test, and deployment cycles
Advanced workflow support for dynamic child pipelines and manual approval gates
89 GitHub stars

Use Cases

Reducing build costs and times through intelligent job caching and runner optimization
Automating Kubernetes deployments with environment-specific configurations
Implementing shift-left security with automated vulnerability scanning in merge requests

About

Key Features

Optimized caching and artifact management to reduce runner execution time
Security-first templates for SAST, dependency scanning, and Trivy audits
Native patterns for Docker builds, Kubernetes rollouts, and Terraform workflows
Multi-stage pipeline architecture for build, test, and deployment cycles
Advanced workflow support for dynamic child pipelines and manual approval gates
89 GitHub stars

Use Cases

Reducing build costs and times through intelligent job caching and runner optimization
Automating Kubernetes deployments with environment-specific configurations
Implementing shift-left security with automated vulnerability scanning in merge requests