Optimizing FastAPI with SQLAlchemy for High Concurrent Users - Slow Database Queries on Postgres
I'm having trouble with I'm relatively new to this, so bear with me. I'm currently working with important performance optimization with my FastAPI application when handling a high number of concurrent users. I have implemented SQLAlchemy to interact with a Postgres database, but I've noticed that as the number of users increases, my API response times degrade noticeably, with some endpoints taking over 5 seconds to respond. Here's a simplified version of my endpoint that retrieves user data: ```python from fastapi import FastAPI, Depends from sqlalchemy.orm import Session from myapp.database import get_db from myapp.models import User app = FastAPI() @app.get('/users/{user_id}') async def read_user(user_id: int, db: Session = Depends(get_db)): user = db.query(User).filter(User.id == user_id).first() return user ``` I've made sure to use async SQLAlchemy with the async session, but it still doesn't seem to improve performance. I suspect that the way I'm querying the database might be causing the slowdown. The table has about 100,000 rows, and it seems like the queries are causing lock contention as multiple users hit the endpoint simultaneously. I've tried adding indexes on `User.id` but haven't seen any improvements. Additionally, I'm using connection pooling with a pool size of 5 and max overflow of 10, but under high load, I still see connection timeouts in my logs: ``` sqlalchemy.exc.OperationalError: (psycopg2.OperationalError) timeout expired ``` I'm wondering if I should consider query optimization techniques, or if there's a better way to configure my FastAPI app to handle more concurrent users effectively. Are there any best practices or design patterns that I could apply in this scenario? Any insights or suggestions would be greatly appreciated! How would you solve this? I've been using Python for about a year now. What's the correct way to implement this? I'm working on a microservice that needs to handle this. What's the correct way to implement this?