A GitHub Template for learning Platform Engineering & SRE practices with AWS EKS
This is a production-ready GitHub template for a structured 6-8 week learning journey through modern platform engineering and Site Reliability Engineering (SRE) practices.
Perfect for:
- 💼 Building a portfolio project to showcase platform engineering skills
- 📚 Learning AWS EKS, Kubernetes, and Infrastructure as Code
- 🎓 Transitioning into Platform Engineering or SRE roles
- 🚀 Understanding production-grade reliability patterns
- 💡 Hands-on experience with real cloud infrastructure
By the end of this 8-week journey, you'll have:
✅ Production-grade EKS cluster running on AWS ✅ Containerized microservice with FastAPI ✅ Full CI/CD pipeline with GitHub Actions ✅ Infrastructure as Code using Terraform ✅ Comprehensive observability with CloudWatch ✅ Chaos engineering experiments documented ✅ Portfolio-ready case study to showcase ✅ Real production experience to discuss in interviews
Click the green "Use this template" button at the top of this page, then:
- Select "Create a new repository"
- Name your repo (e.g.,
my-reliability-lab) - Choose Public visibility (for portfolio)
- Click "Create repository from template"
# Clone your new repository
git clone git@github.com:YOUR-USERNAME/my-reliability-lab.git
cd my-reliability-lab
# Navigate to the lab directory
cd reliability-lab
# Run customization script
chmod +x .github/template-cleanup.sh
./.github/template-cleanup.sh YOUR-USERNAME my-reliability-lab
# Commit customizations
git add .
git commit -m "chore: customize template"
git push# Install dependencies
python3 -m venv venv
source venv/bin/activate
make dev
# Run tests
make test
# Start the app
cd deploy/compose
docker-compose upThen open docs/lab-roadmap.md and begin Week 1!
reliability-lab/
├── services/sample-app/ # FastAPI microservice
│ ├── app/main.py # Application code
│ ├── tests/ # Test suite
│ └── Dockerfile # Multi-stage build
├── deploy/
│ ├── compose/ # Local development
│ ├── k8s/ # Kubernetes manifests
│ └── terraform/ # Infrastructure as Code
├── ops/
│ ├── observability/ # Monitoring configs
│ └── security/ # Security baselines
├── docs/
│ ├── architecture/adr/ # Architecture decisions
│ ├── lab-roadmap/ # Week-by-week guides
│ ├── runbooks/ # Operational procedures
│ └── reliability/ # SRE concepts
└── .github/workflows/ # CI/CD pipelines
| Week | Focus | Time | Outcome |
|---|---|---|---|
| 1 | EKS & Containerization | 10-15h | App running on EKS |
| 2 | Terraform & AWS Baseline | 10-15h | IaC foundation |
| 3 | Kubernetes Hardening | 10-15h | Production patterns |
| 4 | CI/CD Pipeline | 10-15h | Automated deployments |
| 5 | Observability | 10-15h | Metrics, logs, SLOs |
| 6 | Chaos Engineering | 10-15h | Resilience testing |
| 7-8 | Polish & Portfolio | 15-20h | Case study complete |
Total: 75-110 hours over 6-8 weeks
✅ Security First
- Non-root containers
- Trivy security scanning
- IAM least-privilege patterns
- No secrets in code (IRSA + Secrets Manager)
✅ Cost Optimized
- Designed for AWS Free Tier where possible
- Cost-conscious architecture decisions
- ~$90-180 total budget (with optimization)
- Guidance on scaling to $0 between sessions
✅ Best Practices
- Multi-stage Docker builds
- Kubernetes health probes
- Infrastructure as Code
- Comprehensive testing
- Pre-commit hooks
✅ Documentation
- Architecture Decision Records (ADRs)
- Operational runbooks
- SRE concepts and glossary
- Portfolio-ready case study template
For an enhanced learning experience, use this template with the companion Reliability Lab Setup Guide repository.
The setup guide provides:
- Claude AI configuration as your personal SRE mentor
- Step-by-step onboarding instructions
- Weekly coaching content
- Learning reinforcement exercises
- Community support
With AI assistance, you get:
- Real-time explanations of complex concepts
- Troubleshooting help when stuck
- Best practices recommendations
- Cost optimization guidance
- Portfolio-building advice
- 🎯 Are transitioning into Platform Engineering or SRE roles
- 📚 Learn best by building real projects
- 💼 Need portfolio projects to showcase
- 🚀 Want hands-on AWS and Kubernetes experience
- 💰 Have a budget of $100-200 for learning
- ⏰ Can dedicate 10-15 hours per week for 6-8 weeks
- ✅ Basic programming (Python helpful but not required)
- ✅ Git and GitHub fundamentals
- ✅ Command line basics
- ✅ Basic cloud concepts (AWS account setup)
⚠️ No Kubernetes expertise needed - you'll learn it!⚠️ No Terraform expertise needed - you'll learn it!
Expected Costs:
- Week 1: $10-20 (EKS cluster exploration)
- Weeks 2-6: $15-20/week (active development)
- Weeks 7-8: $5-10 (polish & documentation)
- Total: $90-180 (6-8 weeks)
Optimization Tips:
- Scale EKS nodes to 0 when not working
- Delete LoadBalancers between sessions
- Use CloudWatch (free tier) instead of paid tools
- Destroy infrastructure between weeks if taking breaks
Ultra-budget option: ~$30/month by running only on weekends
- AWS account (personal tier is fine)
- GitHub account
- Claude.ai account (optional, for AI assistance)
- Docker Desktop
- AWS CLI v2
- kubectl
- Terraform
- Python 3.11+
- Git
- Make
Verify prerequisites:
docker --version
aws --version
kubectl version --client
terraform --version
python3 --version- TEMPLATE.md - Detailed template usage guide
- README.md - Project overview
- CLAUDE.md - AI assistant guidance
- docs/lab-roadmap.md - 8-week learning plan
After completing this lab, you'll be able to:
- ✅ Deploy and manage AWS EKS clusters
- ✅ Write Infrastructure as Code with Terraform
- ✅ Build production-ready containerized applications
- ✅ Implement CI/CD pipelines with GitHub Actions
- ✅ Configure observability and monitoring
- ✅ Apply Kubernetes production patterns (HPA, PDB, IRSA)
- ✅ Conduct chaos engineering experiments
- ✅ Implement security best practices
- ✅ Public GitHub repository showcasing skills
- ✅ Architecture diagrams and documentation
- ✅ Technical case study writeup
- ✅ Evidence of production-grade work
- ✅ Demonstrable problem-solving ability
- ✅ Real infrastructure experience to discuss
- ✅ Understanding of SRE principles
- ✅ Cost and security awareness
- ✅ Production incident handling experience
- ✅ Clear articulation of technical decisions
- ✅ Production-grade, not toy examples
- ✅ Cost-conscious throughout
- ✅ Security-first approach
- ✅ Portfolio-ready outcomes
- ✅ Complete infrastructure, not just snippets
- ✅ Structured learning path with clear milestones
- ✅ Explanations included - understand the "why"
- ✅ Guided troubleshooting - learn to debug
- ✅ Time-boxed - complete in 6-8 weeks
- ✅ Budget-friendly - under $200 total
Found an issue? Have an improvement?
- Fork this repository
- Create a feature branch
- Make your changes
- Submit a Pull Request
All contributions welcome - from typo fixes to new features!
Completed the lab? We'd love to hear about it!
- ⭐ Star this repository
- 📝 Share your case study (link in Discussions)
- 🐦 Tweet with #ReliabilityLab
- 💼 Add to your LinkedIn portfolio
- 📸 Share screenshots in Discussions
- Template Issues: Open a GitHub Issue
- Learning Questions: Use GitHub Discussions
- Community: Join relevant Slack channels (CNCF, AWS)
- AI Assistance: Use the setup-guide companion repo
MIT License - see LICENSE
Free to use for learning, portfolio, or commercial purposes.
Inspired by:
- Google SRE Book
- AWS Well-Architected Framework
- Kubernetes Best Practices
- Production engineering experiences
- Community feedback and contributions
- Click "Use this template" above
- Clone your new repository
- Run the customization script
- Start Week 1!
Your platform engineering journey begins now! 🎓
Questions? Check Discussions or open an Issue
Template Version: 1.0.0 Last Updated: 2025-11-01 Maintained by: YOUR-USERNAME