Real World Django Q&A
summary
Start by optimizing for developer productivity and use known tools: Postgres + Redis + Varnish rather than exotic databases. Instrument and monitor from day one (New Relic, Graphite/Grafana, ELK) and keep recent searchable logs (about 3–7 days). When a slow query kills pages, replace the hot path (example: move pagination state to Redis, keep Postgres for row retrieval) and add caching with jitter or thundering‑herd protection. Use pg_stat_statements and request‑level tracing to find the real bottleneck; if the team is constantly firefighting, scale architecture or hire ops.
AI-written summary · about
chapters (10)
- 0:00Introduction and panel
- 1:43Avoiding premature optimization
- 5:44Performance vs. scalability
- 8:16Strategies for handling growth
- 11:24Missing features in Django
- 17:26The evolution of NoSQL and data
- 21:30Deployment tooling Q&A
- 23:54Monitoring and logging practices
- 32:08Improving documentation and tools
- 37:21Platform services and scaling
related talks
47mBuilding Scalable Web Apps
17mOff the Beaten Path: Exploring Unusual Roads to Django Performance
41mProduction Django: Building a Highly Scalable, Secure Django Site
41mEmbracing the Monolith in Small Teams
01h 06mEffective Django
52mData Driven Cache Invalidation
28mPython: Ludicrous mode (with Django)
45mCaching: A trip down the rabbit hole