How does this skill improve GitLab pipeline performance?

It implements advanced caching strategies and artifact management to reduce build times and resource consumption across jobs.

Is it compatible with Kubernetes deployments?

Yes, the skill provides specific patterns for deploying applications to Kubernetes clusters using kubectl and managing multi-environment rollout statuses.

Does it support automated security scanning?

Yes, it includes patterns for SAST, dependency scanning, and container vulnerability checks using industry-standard tools like Trivy.

Can I use this for Infrastructure as Code (IaC)?

Absolutely. It features dedicated templates for Terraform validation, planning, and auto-apply stages within the GitLab ecosystem.

GitLab CI/CD Patterns

Name: GitLab CI/CD Patterns
Author: GaitanS

byGaitanS

Deployment & DevOps

Automates the creation and optimization of GitLab CI/CD pipelines using production-ready templates and best practices.

About

This skill provides Claude with advanced expertise in building, optimizing, and securing GitLab CI/CD pipelines. It includes pre-configured patterns for multi-stage workflows, efficient caching strategies, Docker containerization, Kubernetes deployments, and Infrastructure as Code (Terraform) pipelines. By leveraging these standardized templates, developers can reduce pipeline execution time, implement robust security scanning, and ensure consistent deployment environments across staging and production.

Key Features

Automated security scanning including SAST and container vulnerability checks
Optimized caching strategies and artifact management
Multi-stage pipeline architecture for build, test, and deployment
Docker-in-Docker (DinD) build and registry integration patterns
0 GitHub stars
Infrastructure as Code (IaC) integration with Terraform templates

Use Cases

Improving pipeline performance through distributed runners and efficient caching
Migrating manual deployment processes to scalable GitLab CI/CD workflows
Setting up automated testing and deployment for containerized applications

About

Key Features

Automated security scanning including SAST and container vulnerability checks
Optimized caching strategies and artifact management
Multi-stage pipeline architecture for build, test, and deployment
Docker-in-Docker (DinD) build and registry integration patterns
0 GitHub stars
Infrastructure as Code (IaC) integration with Terraform templates

Use Cases

Improving pipeline performance through distributed runners and efficient caching
Migrating manual deployment processes to scalable GitLab CI/CD workflows
Setting up automated testing and deployment for containerized applications