01
Latency spikes under load
Blocking I/O and unpooled database connections exhausting worker threads.
APIs slowing down or failing under traffic spikes
High-concurrency API scaling and throughput optimization
Find where an API breaks under load, then fix the bottlenecks: blocking I/O, connection limits, missing caches and missing backpressure.
Symptoms
Signs your platform has this problem
If several of these sound familiar, the plan below is where we would start.
02
502 and 504 errors
Proxies timing out as application worker queues overflow.
03
Lock contention
High write concurrency causing lock waits and deadlocks on hot rows.
Remediation plan
How we fix it, step by step
Each phase ends with a measurement, so you can see what changed before the next one starts.
01
Load testing with k6
Finding the breaking point with load tests that match your real traffic mix.
02
Async request handling
Converting blocking handlers to async I/O, or moving hot paths to a faster service where that pays off.
03
Caching and rate limiting
Serving repeat reads from the CDN and Redis, and limiting abusive clients.
04
Connection pooling
Using RDS Proxy or PgBouncer so many API workers share a small pool of database connections.
Technical checklist
Remediation checklist
What we check before a change goes to production:
- Load test the API with k6 at and above the expected peak
- Replace blocking I/O with asynchronous handlers
- Cache hot reads in Redis with explicit invalidation
- Add circuit breakers and token-bucket rate limits at the gateway
What we measure
We take a baseline first and report the same measurements after each change, from your own monitoring — evidence, not promised results.
- Breaking point
- Requests per second before errors rise, from load tests
- p99 latency
- Under the target load, before and after
- Error rate
- 5xx responses during load tests and real peaks
Related service
Custom software
Custom software for Indian SMEs and startups, built around your workflow with an agreed scope, review milestones, clear ownership and documented handover.
Explore Custom softwareQuestions
Questions about this remediation
We run k6 load tests that ramp traffic sharply — from more than one region where it matters — and watch latency, errors and database load to find the first bottleneck.
Usually caching: serving repeat reads from a CDN and Redis takes load off the backend immediately. How much it helps depends on how cacheable your traffic is, which the load-test traces show.
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Want an engineer to look at this with you?
Send us the symptoms and any metrics you have. We'll reply within one business day, set up a call and agree what to measure before anything changes.