Lab 28 - Telepresence Demo¶

🎯 Quick Start¶

Deploy the demo and start intercepting in minutes:

# 1. Setup everything
./setup.sh

# 2. Quick start intercept
./quickstart.sh

# 3. Navigate to backend app
cd resources/backend-app

# 4. Setup Python environment (first time)
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

# 5. Start intercepting
telepresence intercept backend --port 5000 --namespace telepresence-demo

# 6. Run locally
python app.py

# 7. Test via frontend
kubectl port-forward -n telepresence-demo svc/frontend 8080:80
# Open http://localhost:8080

📁 Lab Structure¶

32-Telepresence/
├── README.md              # Complete guide with theory and exercises
├── EXAMPLES.md            # 12 practical examples
├── TROUBLESHOOTING.md     # Common issues and solutions
├── setup.sh              # Automated setup script
├── cleanup.sh            # Cleanup script
├── test.sh               # Test script
├── quickstart.sh         # Quick start guide
└── resources/
    ├── 01-namespace.yaml           # Namespace definition
    ├── 02-dataservice.yaml         # Data service deployment
    ├── 03-backend.yaml             # Backend service deployment
    ├── 04-frontend.yaml            # Frontend deployment
    ├── BUILD.md                     # Docker build instructions
    ├── backend-app/
    │   ├── app.py                   # Backend Python application
    │   ├── requirements.txt         # Python dependencies
    │   └── Dockerfile              # Backend Docker image
    ├── dataservice-app/
    │   ├── app.py                   # Data service application
    │   ├── requirements.txt         # Python dependencies
    │   └── Dockerfile              # Data service Docker image
    └── frontend-app/
        ├── index.html               # Frontend HTML/JS
        ├── nginx.conf              # Nginx configuration
        └── Dockerfile              # Frontend Docker image

🚀 What You’ll Learn¶

Installation & Setup
Install Telepresence CLI
Connect to Kubernetes cluster
Deploy Traffic Manager
Basic Intercepts
Global intercepts (all traffic)
Personal intercepts (header-based)
Preview URLs (shareable links)
Development Workflows
Local debugging with cluster access
Hot reload development
Integration testing
Advanced Features
Volume mounts
Environment variable sync
Docker mode

📚 Documentation¶

README.md - Complete guide (50+ pages)
Theory and concepts
Installation steps
4 hands-on exercises
Best practices
Troubleshooting
EXAMPLES.md - 12 Practical Examples
Basic workflows
VS Code debugging
Team collaboration
Integration testing
TROUBLESHOOTING.md - Problem Solving
10 common issues
Solutions and workarounds
Debug commands

🛠️ Scripts¶

setup.sh - Deploy all resources automatically
cleanup.sh - Remove all demo resources
test.sh - Verify deployment and connectivity
quickstart.sh - Quick start guide for intercepting

🎓 Exercises¶

Exercise 1: Basic Intercept¶

Route all backend traffic to your local machine

Exercise 2: Preview URLs¶

Create shareable links for stakeholder review

Exercise 3: Global Intercept¶

Test breaking changes safely

Exercise 4: Personal Intercept¶

Use header-based routing for team development

🏗️ Demo Architecture¶

┌─────────────────┐
│   Frontend      │
│   (Nginx)       │
└────────┬────────┘
         │
         ▼
┌─────────────────┐      ┌──────────────┐
│   Backend       │─────▶│ Data Service │
│   (Python)      │      │  (Python)    │
└─────────────────┘      └──────────────┘

Intercept Point: Backend service - Local development with cluster access - Real-time testing with other services - No container builds required

⚡ Key Features Demonstrated¶

✅ Fast inner-loop development
✅ Service mesh integration
✅ Real-time code changes
✅ Team collaboration
✅ Production debugging
✅ Integration testing
✅ Preview URLs
✅ Environment sync

🔧 Prerequisites¶

Kubernetes cluster (Minikube, Kind, or cloud)
kubectl configured
Admin access to cluster
Python 3.11+
Docker (optional)

📝 Common Commands¶

# Connect
telepresence connect

# List services
telepresence list --namespace telepresence-demo

# Intercept
telepresence intercept backend --port 5000 --namespace telepresence-demo

# Status
telepresence status

# Leave intercept
telepresence leave backend

# Disconnect
telepresence quit

# Cleanup
telepresence uninstall --everything

🎯 Learning Outcomes¶

After completing this lab, you will:

Understand Telepresence architecture
Install and configure Telepresence
Create and manage intercepts
Debug services with local tools
Collaborate using personal intercepts
Share changes via preview URLs
Integrate Telepresence into workflows
Troubleshoot common issues

🌟 Best Practices¶

Use personal intercepts in shared environments
Keep telepresence connected during development
Leverage hot reload for fast feedback
Export environment variables once, reuse
Monitor Traffic Manager logs
Clean up intercepts when done
Use preview URLs for demos
Document team intercept conventions

🐛 Troubleshooting¶

If you encounter issues:

Check TROUBLESHOOTING.md
Run ./test.sh to verify setup
Check telepresence status
Enable debug: telepresence loglevel debug
View logs: kubectl logs -n ambassador deployment/traffic-manager

🔗 Resources¶

Official Docs: https://www.telepresence.io/docs/
GitHub: https://github.com/telepresenceio/telepresence
Community Slack: https://a8r.io/slack
Video Tutorials: https://www.youtube.com/c/Datawire

🧹 Cleanup¶

# Remove demo resources
./cleanup.sh

# Or manually
kubectl delete namespace telepresence-demo
telepresence quit
telepresence uninstall --everything

💡 Next Steps¶

After mastering this lab:

Integrate Telepresence into CI/CD
Create team workflows
Explore Ambassador Cloud features
Set up automated testing
Configure for your specific stack
Share knowledge with team

Happy Coding! 🚀

Questions? Check the README.md for detailed information or EXAMPLES.md for practical use cases.