Django Backend Performance Optimization

I have several full-stack products in production—an online course manager, a housekeeping management tool, an HR portal, and an online bookstore—and I’m now focusing on squeezing every millisecond out of their Django back-ends.
Your task is to step into one of these projects (the choice will depend on your past experience and interest) and raise its performance ceiling. Database queries, caching layers, asynchronous tasks, and deployment tweaks are all fair game as long as they translate into faster response times under load.

What I’ll share once we start:
• Source code and current deployment setup (Docker + PostgreSQL + Redis)
• Baseline benchmarks and target response-time goals
• A short list of user flows that must remain unchanged functionally

What I need back:
• Optimised Django code or configurations committed to Git
• Before-and-after performance metrics gathered with standard tools (e.g., Django Debug Toolbar, Locust, or JMeter)
• A concise report explaining each change so I can replicate the approach across the rest of my systems

If you’re comfortable profiling, refactoring, and tuning Django builds for real-world traffic, let’s talk.