Fix the data layer first
Before adding services, caches or queues, look at query patterns. Missing indexes, N+1 access patterns and unbounded result sets account for most performance collapses we are called in to diagnose.
These are also the cheapest problems to fix, and fixing them often removes the perceived need for a larger architectural change.
Cache deliberately
Caching without an invalidation strategy converts a performance problem into a correctness problem. Decide per data type how stale a value may be, and make that decision explicit in code.
Make scaling boring
Stateless application servers, externalised sessions, idempotent background jobs and a load test that runs in CI turn scaling into a configuration change rather than a project.
- Stateless services behind a load balancer
- Connection pooling sized to the database, not the app
- Background work in queues with retry and dead-letter handling
- Load tests against realistic data volumes
Written by Nexora Engineering. If you would like to discuss how this applies to your environment, we are happy to talk it through.
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