WSGI servers (Gunicorn, uWSGI) in Flask - Performance & Optimization

Performance: WSGI servers (Gunicorn, uWSGI)

HIGH IMPACT

This affects how fast your Flask app starts serving requests and handles concurrent users, impacting server response time and throughput.

Serving a Flask app to multiple users efficiently

Flask

gunicorn -w 4 -b 0.0.0.0:8000 myapp:app  # Using Gunicorn with multiple workers

Gunicorn runs multiple worker processes to handle many requests concurrently, improving throughput and responsiveness.

📈 Performance Gainhandles multiple requests in parallel, reducing request wait time and improving INP

Serving a Flask app to multiple users efficiently

Flask

app.run()  # Using Flask's built-in server in production

Flask's built-in server is single-threaded and not designed for production, causing slow response and blocking under load.

📉 Performance Costblocks requests under concurrent load, leading to high latency and poor INP

Performance Comparison

Pattern	Concurrency	Request Latency	Resource Usage	Verdict
Flask built-in server	Single-threaded	High under load	Low but inefficient	[X] Bad
Gunicorn with multiple workers	Multi-process	Low	Moderate CPU/memory	[OK] Good
uWSGI single process/thread	Single-threaded	High latency	Low but blocking	[X] Bad
uWSGI multiple processes/threads	Multi-process/thread	Low latency	Higher resource use but efficient	[OK] Good

Rendering Pipeline

WSGI servers receive HTTP requests, pass them to the Flask app, then send back responses. Efficient concurrency reduces waiting time before response generation.

→Request Handling

→Application Processing

→Response Sending

⚠️ BottleneckRequest Handling when concurrency is low or server is single-threaded

Core Web Vital Affected

INP

This affects how fast your Flask app starts serving requests and handles concurrent users, impacting server response time and throughput.

Optimization Tips

1Never use Flask's built-in server for production; use a WSGI server like Gunicorn or uWSGI.

2Configure multiple worker processes and threads to handle concurrent requests efficiently.

3Monitor server response times under load to adjust concurrency settings for best performance.

Performance Quiz - 3 Questions

Why is using Flask's built-in server in production a bad idea for performance?

A It is single-threaded and blocks requests under load

B It uses too much memory

C It does not support HTTP

D It automatically caches responses

DevTools: Network and Performance panels

How to check: Use Network panel to measure response times under load; use Performance panel to record request handling delays and CPU usage.

What to look for: Look for consistent low response times and no long blocking periods indicating good concurrency and server responsiveness.