Learning to use GitHub vs Gitlab

Today I asked Claude.ai to help me come up with a strategy for learning both GitHub and Gitlab while using each to focus on different tasks. Claude recommended a Split Strategy GitHub (Public Face):

Polished learning blog Showcase projects for employers Open source contributions Final, clean project repositories

GitLab (Learning Lab):

Messy experimental code Private practice repositories Complex CI/CD learning projects Enterprise workflow simulation

Example Learning Projects for GitLab

Multi-stage CI/CD Pipeline - Build → Test → Security Scan → Deploy Kubernetes Deployment Project - With GitLab’s K8s integration Docker Registry Practice - Host your own container images Infrastructure as Code - Terraform with GitLab CI Security-First Development - Using GitLab’s security features

This way I get the best of both platforms - GitHub for your professional presence and GitLab for advanced DevOps learning. Want me to help you plan specific projects for each platform?

GitHub vs GitLab Learning Project Plan

🎯 Strategic Platform Split

GitHub = Public Professional Portfolio
GitLab = Private Learning Laboratory

📋 GitHub Projects (Public Showcase)

Phase 1: Foundation Building

1. TadpoleToTech Learning Blog ✅ Already Done

  • What: Your current Jekyll blog documenting learning journey
  • Purpose: Professional presence, knowledge sharing, SEO benefits
  • Audience: Potential employers, fellow learners, general public

2. Personal Portfolio Website

  • Repository: frogcatchers.github.io (main site)
  • Tech Stack: HTML/CSS/JavaScript or React
  • Features: About, Projects showcase, Resume, Contact
  • Learning Goals: Web development, responsive design, GitHub Pages

3. Docker Learning Showcase

  • Repository: docker-learning-examples
  • Contents: Clean, well-documented Dockerfiles and compose files
  • Projects:
    • Multi-stage Python app build
    • Microservices architecture demo
    • Development environment containers
  • Purpose: Show Docker competency to employers

Phase 2: Integration Projects

4. CI/CD Portfolio Project

  • Repository: automated-deployment-demo
  • Tech Stack: Node.js/Python app with GitHub Actions
  • Features: Automated testing, security scanning, deployment
  • Deployment: GitHub Pages or Vercel
  • Learning Goals: Production-ready CI/CD patterns

5. Full-Stack Application

  • Repository: learning-tracker-app
  • Description: Web app to track your own learning progress
  • Tech Stack: React frontend, Node.js backend, containerized
  • Features: Learning goals, progress tracking, resource bookmarks
  • Purpose: Demonstrate full development lifecycle

Phase 3: Advanced Showcase

6. Open Source Contributions

  • Target: Contribute to Docker, Kubernetes, or AI projects
  • Goal: Show collaborative development skills
  • Documentation: Blog posts about contribution experience

🔬 GitLab Projects (Private Learning Lab)

Phase 1: DevOps Fundamentals

1. GitLab CI/CD Playground

  • Repository: ci-cd-learning-lab
  • Purpose: Experiment with complex pipelines without public scrutiny
  • Features:
    • Multi-stage pipelines (build/test/security/deploy)
    • Different deployment targets
    • Failed experiments and learning notes
  • Learning Goals: Advanced GitLab CI syntax, pipeline optimization

2. Kubernetes Learning Environment

  • Repository: k8s-practice-ground
  • Contents: Kubernetes manifests, Helm charts, practice deployments
  • Features:
    • GitLab’s Auto DevOps experimentation
    • Kubernetes integration testing
    • Cluster management practice
  • Purpose: Hands-on K8s learning without public mistakes

3. Infrastructure as Code Lab

  • Repository: iac-experiments
  • Tech Stack: Terraform, Ansible, GitLab CI
  • Purpose: Practice infrastructure automation
  • Features:
    • Cloud resource provisioning
    • Configuration management
    • Infrastructure testing

Phase 2: Enterprise Workflows

4. Multi-Environment Deployment

  • Repository: enterprise-deployment-sim
  • Environment: Simulate dev/staging/prod workflows
  • Features:
    • Environment-specific configurations
    • Approval processes
    • Rollback strategies
  • Learning Goals: Enterprise deployment patterns

5. Security-First Development

  • Repository: secure-development-lab
  • Focus: GitLab’s security scanning features
  • Features:
    • SAST/DAST scanning
    • Dependency scanning
    • Container scanning
    • Security policy enforcement

6. Microservices Architecture

  • Repository: microservices-learning-platform
  • Tech Stack: Multiple languages, Docker, Kubernetes
  • Features:
    • Service mesh experimentation
    • Inter-service communication
    • Distributed tracing
  • Purpose: Complex system architecture practice

Phase 3: Cutting-Edge Technologies

7. AI/ML Pipeline Laboratory

  • Repository: ml-ops-experiments
  • Focus: MLOps practices with GitLab
  • Features:
    • Model training pipelines
    • Automated model deployment
    • A/B testing frameworks
    • Hugging Face integration experiments

8. Blockchain Development Sandbox

  • Repository: blockchain-learning-lab
  • Purpose: Experiment with smart contracts and DApps
  • Features:
    • Solidity development environment
    • Testing frameworks
    • Deployment automation
  • Privacy: Keep experimental/learning code private

🎯 Learning Timeline & Strategy

Month 1-2: Foundation

  • GitHub: Complete portfolio website, polish blog
  • GitLab: Set up CI/CD playground, basic pipeline experiments

Month 3-4: Integration

  • GitHub: Build and deploy first full-stack application
  • GitLab: Kubernetes integration, multi-stage pipelines

Month 5-6: Advanced

  • GitHub: Open source contributions, advanced CI/CD showcase
  • GitLab: Enterprise workflows, security-first development

Month 7+: Specialization

  • GitHub: Domain-specific projects (AI, blockchain, quantum)
  • GitLab: Complex distributed systems, advanced MLOps

📊 Success Metrics

GitHub Portfolio Impact:

  • Clean, professional repositories with excellent documentation
  • Consistent contribution history showing continuous learning
  • Projects that demonstrate real-world problem-solving skills
  • Blog posts that establish thought leadership

GitLab Learning Outcomes:

  • Mastery of advanced DevOps toolchains
  • Experience with enterprise-grade workflows
  • Hands-on practice with cutting-edge technologies
  • Private space to experiment and fail safely

🔄 Cross-Platform Integration

Blog Content Strategy:

  • GitHub Projects → Blog Posts: Document your showcase projects
  • GitLab Experiments → Blog Posts: Share lessons learned (without exposing messy code)
  • Learning Labs → Polished Examples: Graduate successful GitLab experiments to GitHub

Career Development:

  • GitHub: What employers see first
  • GitLab: Advanced skills you mention in interviews
  • Blog: Thought leadership and communication skills
  • Combined: Complete picture of technical growth

🚀 Getting Started

Next Steps:

  1. Set up GitLab account and create first private repository
  2. Plan your first GitLab CI/CD experiment (simple pipeline)
  3. Create GitHub portfolio website repository
  4. Write blog post about your dual-platform learning strategy

Resource Allocation:

  • 70% GitLab: Deep learning, experimentation, complex projects
  • 30% GitHub: Polishing, showcasing, community engagement
  • Blog: Document insights from both platforms

This strategy maximizes learning opportunities while building a strong professional presence!