Redis caching and queues
We use Redis to keep products fast: caching in front of PostgreSQL, queues for background work, and sessions, hosted on AWS.
Caching that takes load off the database
The fastest query is the one you never run. We use Redis to cache hot data and expensive results in memory, so pages render quickly and your database is not hammered by the same lookups over and over. We add sensible expiry and invalidation so users still see fresh data, applying caching where the numbers justify it rather than everywhere.
- In-memory caching for hot data
- Sensible expiry and invalidation
- Less load on PostgreSQL
Queues and background work
Redis is a solid broker for background jobs. We use it behind Celery and similar workers so slow tasks, emails, exports, and processing run off the request path. Users get an instant response while the heavy lifting happens in the background, which keeps the product feeling fast even when the work behind it is not.
- Broker for background jobs
- Work kept off the request path
- Instant responses for users
Sessions, rate limiting, and more
Beyond caching, Redis is great for sessions, rate limiting, leaderboards, and real-time counters. We use the right data structures for each job so these features are fast and simple rather than bolted onto the main database. It is a versatile tool, and we apply it where it genuinely earns its place.
- Sessions and rate limiting
- Real-time counters and leaderboards
- The right structure per job
Managed and reliable on AWS
We run Redis on AWS ElastiCache, configured for the durability and availability your use case needs, with monitoring so you can see hit rates and memory. It is defined as infrastructure as code alongside the rest of your stack, so it is repeatable and easy to reason about.
- AWS ElastiCache
- Monitored hit rates and memory
- Defined as code
Part of the wider stack
Redis supports our Django and FastAPI backends and our approach to scalable architecture.
Redis questions
Caching hot data and expensive results, as a broker for background jobs, and for sessions, rate limiting, and real-time counters. It takes load off PostgreSQL and keeps the product responsive.
Not if it is done right. We set sensible expiry and invalidate caches when the underlying data changes, so users see fresh results while still getting the speed benefit.
On AWS ElastiCache, configured for the availability your use case needs, monitored, and defined as infrastructure as code alongside the rest of your stack.
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