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- ⚡Docker Production Simulation | Scaling Flask + Postgres with Nginx & Monitoring
⚡Docker Production Simulation | Scaling Flask + Postgres with Nginx & Monitoring
DevOps Labs — Debugging & Scaling Like Real Production Engineers
🎯 Why This Simulation Matters
Running a single Flask app in Docker is easy.
But in production, things get messy:
Multiple services (Flask + Postgres)
Load balancing (Nginx)
Monitoring (so you know what’s breaking before users complain)
Without these pieces, your Docker setup will fail under real-world load.
This episode simulates a mini production environment where we’ll break, scale, and debug — just like engineers do at work.
▶️ What You’ll Learn in This Video
Hands-on demo: https://youtu.be/nWiy6eaS5FU
📌 Architecture Setup
Flask app container
Postgres database container
Nginx as reverse proxy & load balancer
Monitoring with cAdvisor & live logs
📌 Simulating Load & Failures
Push traffic → watch logs explode
Trigger Postgres connection issues
Debug Nginx routing errors
Nginx automatically balances traffic across all Flask containers
📌 Best Practices
Separate containers for app, DB, and proxy
Always add monitoring to Docker stacks
Test scaling locally before deploying to cloud
👉 Watch the full video here: https://youtu.be/nWiy6eaS5FU
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🛠 Takeaway Example Command
❌ Single container (default):
docker compose up -d
✅ Scale to 3 containers (manual flag):
docker compose up --scale app=3 -d
💡 This gives you instant horizontal scaling without touching Compose files.
💡 Why This Guide Stands Out
🚀 Real-world production simulation → Not just “Docker run”, but multi-service scaling.
🔎 Debug-driven → You’ll see errors in logs, routing, and DB connections.
🏭 Production-ready → By the end, you’ll know how to scale & monitor a mini production stack on your laptop.
This isn’t just Docker theory — it’s a production simulation you’ll actually reproduce.
👋 Final Note
If you enjoyed this breakdown, hit subscribe to my newsletter.
Every week I share real DevOps outages, interview prep, and hands-on labs you can reproduce — so you’ll never be caught off guard in production.
— Arbaz
📺 YouTube: Learn with DevOps Engineer
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