Record the database connection limit, deployment worker counts and the settings for connection lifetime or pooling. Gather the error time and current database connection observations.

1. Estimate the combined demand from application processes and threads, background workers, administration tools and other applications sharing the database.

2. Review Django connection settings for the selected backend and execution model. Persistent connections and explicit pools need deliberate limits; ASGI deployments have specific guidance for persistent connection handling.

3. Look for long-running transactions, blocked queries or workers that retain connections while waiting on unrelated external services.

4. Reduce unnecessary concurrency or connection lifetime where appropriate, then use a backend-supported pool if it fits the architecture. Leave capacity for maintenance and recovery access.

5. Repeat a representative load test and observe connection counts, query latency and application error rates together.

Confirm the application operates below the usable connection ceiling during its expected traffic peak and scheduled work. A lower worker count is useful only if requests still complete within acceptable time.

If connections rise after every deployment, investigate old processes that did not stop. If a few sessions remain blocked, identify the owning query before terminating anything.

• Choosing a database connection pool size
• Choosing WSGI or ASGI for Django hosting
• Measuring application latency by dependency
• Configuring Django hosts and CSRF origins behind HTTPS

• Django database connections
• Django asynchronous support