How We Built a Distributed Load Testing System on k6 and Made Client APIs 3x Faster
Published on 1/14/2026
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Engineering
The Problem: "Everything Works" (on the Test Server)
Typical situation: a client launches a product, first 100 users — everything is great. Then marketing kicks in, ads go live, and...
— Why is the site down? You said everything was ready!
The problem is that most teams test functionality, not performance. And when they do test performance — they do it from a single machine, which doesn't reflect the real picture of distributed load.
Our Solution: Distributed Load Testing on k6
We built infrastructure for distributed load testing that simulates thousands of concurrent users from different geographic locations.
Why k6?
JavaScript scenarios — developers write tests in a familiar language, no new tools to learn
Low resource consumption — one k6 instance generates load equivalent to dozens of JMeter instances
Built-in metrics — latency, throughput, error rate out of the box
CI/CD integration — tests run automatically on every deploy
Distributed Load Architecture
Orchestrator — coordinates test execution across multiple nodes
k6 runners in Kubernetes — scalable pods that generate load
Prometheus + Grafana — real-time metrics collection and visualization
Automatic reports — after each test, the team receives a detailed breakdown
Real Results with Clients
Case 1: Marketplace
Client was preparing for Black Friday. We conducted load testing and discovered:
Catalog API "died" at 500 RPS due to unoptimized SQL queries
Session service didn't scale horizontally
Result: After optimization, the system handled 15,000 RPS. Black Friday passed without a single outage.
Case 2: Fintech Application
Critical payment API showed p99 latency of 2.5 seconds.
Found bottleneck in synchronous calls to external service
Implemented asynchronous processing with queues
Result: p99 latency dropped to 180ms — 14x improvement.
Case 3: SaaS Platform
Client complained about "random slowdowns". Couldn't reproduce locally.
Distributed test revealed race condition during concurrent requests
Issue only manifested under load from 200+ concurrent users
Result: Bug fixed before production. Saved ~$50,000 in potential losses.
What We Offer as a Service
Performance audit — we find bottlenecks before they become problems
CI/CD pipeline setup — automatic tests on every release
Monitoring and alerting — Grafana dashboards to track degradation
Optimization — we don't just show problems, we fix them
Conclusion
Load testing is not a "nice to have" — it's a mandatory step before any serious launch. It's better to find a problem on a test bench for $5,000 than to lose $500,000 on a crashed production.
If your product is preparing for growth — contact us for a performance audit.