Understanding and Resolving PostgreSQL "Too Many Clients" Error

The error you're experiencing is a common issue when PostgreSQL reaches its maximum allowed client connections. Let's analyze the potential causes and solutions.

Potential Causes

1. Connection Pooling Issues: Your current configuration uses conn_max_age=600, which means Django keeps connections open for 10 minutes. With three Daphne processes, each thread in each process maintains its own connection.

2. Connection Leaks: Connections might not be properly closed, especially in long-running processes outside Django's request-response cycle.

3. Database Configuration: PostgreSQL has a default limit on the maximum number of concurrent connections.

4. Sudden Traffic Spike: While you mentioned no abnormal traffic, even normal traffic patterns can cause issues if connections aren't managed efficiently.

Diagnosis Steps

1. Check Current PostgreSQL Connections:

   SQLCopied
   SELECT count(*) FROM pg_stat_activity;

2. Identify Connection Sources:

   SQLCopied
   SELECT client_addr, usename, count(*) 
   FROM pg_stat_activity 
   GROUP BY client_addr, usename 
   ORDER BY count(*) DESC;

3. Look for Idle Connections:

   SQLCopied
   SELECT * FROM pg_stat_activity WHERE state = 'idle';

Solutions

1. Adjust conn_max_age

While you're skeptical, adjusting conn_max_age can help. With three Daphne processes, each potentially running multiple threads, you could be maintaining many connections unnecessarily:

PYTHONCopied
DATABASES = {
    "default": {
        **dj_database_url.parse(
            os.environ.get("DATABASE_URL", False), conn_max_age=300  # Reduced to 5 minutes
        ),
        "ATOMIC_REQUESTS": True,
    }
}

2. Implement Connection Health Checks

Enable connection health checks to ensure Django doesn't try to use connections that have been terminated by the database:

PYTHONCopied
DATABASES = {
    "default": {
        **dj_database_url.parse(
            os.environ.get("DATABASE_URL", False), conn_max_age=600
        ),
        "ATOMIC_REQUESTS": True,
        "CONN_HEALTH_CHECKS": True,
    }
}

3. Close Connections in Long-Running Processes

If you have background tasks or long-running processes, make sure to explicitly close connections:

PYTHONCopied
from django.db import close_old_connections

# At the end of your long-running process
close_old_connections()

4. Increase PostgreSQL's Connection Limit

If your server can handle it, you might consider increasing the maximum connections in PostgreSQL:

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ALTER SYSTEM SET max_connections = 200;  # Adjust based on your server capacity

Remember to restart PostgreSQL after changing this setting.

5. Consider Connection Pooling

For production environments with multiple workers, consider implementing a connection pooling solution like PgBouncer.

Is It Malicious Activity?

This error can occur without malicious activity due to configuration issues or connection leaks. However, if you suspect malicious activity:

1. Check your access logs for unusual patterns
2. Monitor for abnormal request rates
3. Look for suspicious IP addresses making many connections

Conclusion

The most likely cause is a combination of your conn_max_age setting and the number of worker threads across your three Daphne processes. Each thread maintains its own connection, and with a 10-minute connection lifetime, these can accumulate quickly.

Start by implementing connection health checks and possibly reducing conn_max_age. Monitor the situation and if problems persist, consider implementing a proper connection pooling solution.