Caching at Scale in Django: Lessons from Production | Johnny Metz

The author shares production lessons on scaling a multi-tenant Django API through aggressive caching in Redis rather than relying solely on database upgrades. Key techniques include splitting responses into user-specific IDs and globally shared base objects, maintaining long TTLs with immediate signal-based invalidation, and configuring robust fallback behavior for Redis outages. During a three-month rollout, these strategies reduced database queries and web CPU by half while handling significant traffic growth. Open article →