Heroku上Django Channels+Redis部署的内存泄漏问题求助

Let's break down what's happening here and walk through actionable solutions to get your Redis memory usage under control:

1. Fix Channel Session TTL Configuration #

Looking at your Redis info output, those session keys in db1 have an average TTL of ~37 years — that's wildly excessive! The root issue is your cache configuration doesn't explicitly set a timeout, and Channels 1.x's channel session system is inheriting an incorrect, ultra-long expiration value.

Update your CACHES settings to add a reasonable timeout (24 hours/86400 seconds is a solid starting point):

CACHES = {
    'default': {
        'BACKEND': 'redis_cache.RedisCache',
        'LOCATION': os.environ.get('REDIS_URL', 'redis://localhost:6379'),
        'OPTIONS': {
            'CLIENT_CLASS': 'redis_cache.client.DefaultClient',
            'TIMEOUT': 86400,  # Auto-expire cache entries after 24 hours
        }
    },
}

This ensures even if disconnect-time cleanup fails, all channel session data will eventually be purged from Redis, preventing infinite memory growth.

2. Explicitly Clean Up Channel Sessions on Disconnect #

While the channel_session_user decorator handles basic session management, adding explicit cleanup logic to your ws_disconnect consumer will immediately free Redis resources when a client drops the connection:

Modify your consumers.py like so:

@channel_session_user
def ws_disconnect(message):
    # Run your existing business cleanup logic (e.g., remove user from online lists)
    ...
    # Flush all data tied to the current channel session
    message.channel_session.flush()
    # Optional: Delete the session key entirely from Redis for immediate cleanup
    # from django.core.cache import cache
    # cache.delete(message.channel_session.session_key)

flush() clears all data in the session, while deleting the key removes the Redis entry completely.

3. Debug the Leak to Confirm the Source #

If the above steps don't resolve the issue, use these tools to pinpoint exactly what's eating up Redis memory:

• Identify the largest keys:
  Run this command in your Heroku Redis CLI:

  redis-cli --bigkeys
  

  This will show you which keys are consuming the most space — you’ll confirm if it’s channel sessions, regular Django sessions, or leftover Channels messages causing the leak.

• Check for pending Channels messages:
  Channels 1.x's RedisChannelLayer can leave unprocessed messages in queues if workers aren’t keeping up. List all Channels-related queues and check their lengths:

  # List all Channels-managed keys
  redis-cli keys "asgi:*"
  # Check message count for a specific queue
  redis-cli llen "asgi:channel:your-target-channel-name"
  

  If you see huge queue lengths, your workers might be overwhelmed — check worker logs or consider scaling up worker dynos.

• Trim regular Django session TTL:
  Your db0 sessions have an average TTL of ~571 days, which is also longer than necessary. Shorten this by updating your Django settings:

  SESSION_COOKIE_AGE = 86400  # Expire regular sessions after 24 hours
  SESSION_EXPIRE_AT_BROWSER_CLOSE = True  # Optional: End sessions when the browser closes
  

4. Bonus: Upgrade to Channels 2.x+ (If Feasible) #

Your current Channels 1.x version is end-of-life. Channels 2.x and later (now up to 4.x) include far better Redis management, built-in session cleanup improvements, and support for modern ASGI standards. Upgrading will eliminate many of the old version’s quirks and prevent similar memory issues long-term.

内容的提问来源于stack exchange，提问作者Patrik Beck