Load tests that answer real questions
Most performance tests answer "does the system respond" when the real question is "where does it break, and why." We run performance tests that model real traffic, push past your projected ceiling, and produce a report that tells you what to fix — with evidence.
Test types we run
Load Testing
Expected traffic, sustained. Baselines you can compare against every release.
Stress Testing
Beyond expected traffic. Find the breaking point and the failure mode.
Soak Testing
Steady traffic over hours or days. Surfaces memory leaks and connection-pool exhaustion.
Spike Testing
Sudden traffic bursts — Black Friday, viral moments, batch job kick-offs.
Scalability Testing
How does the system scale as you add nodes, replicas, or shards?
Chaos-Adjacent
What happens when a downstream degrades under load? Blast-radius testing.
Tools we build in
- k6 — our default. JavaScript scenarios, great cloud runner, clean output.
- Gatling — Scala-based DSL, best-in-class simulation modeling.
- JMeter — the classic. When you need it, you know why.
- Locust — Python-first teams, distributed by default.
What the report actually says
Not just p50/p95/p99 charts. We ship reports that name the concrete bottleneck (database lock contention, unindexed query, connection pool saturation, GC pressure), pair it with the evidence (traces, flame graphs, slow-query logs), and give you a ranked remediation list. Every finding maps to a JIRA-ready ticket.
Related
Often runs alongside API testing. For frontend performance (Lighthouse, Core Web Vitals), that's usually a shorter engagement — ask us how it fits.