We simulate thousands of concurrent users or requests hitting your API/web app to measure scalability, disk IO, database latency, and response degradations. Scenarios match real production behavior based on user journeys, time-of-day patterns, or auto-scaling dependencies.

We gradually increase load until the application breaks, exposing CPU peaks, connection limits, memory leaks, and queue overflows. Results reveal operational limits and hard constraints before customers encounter failures at peak usage.

We run sustained multi-hour or multi-day traffic tests to identify memory leaks, thread starvation, slow DB growth, and performance degradation caused by resource exhaustion — impossible to detect in short burst tests.

We run JMeter workers or LoadRunner injectors across multiple locations and cloud nodes to simulate geo-based traffic and measure CDN hit-rate, cache misses, and edge performance.

We correlate load test metrics with logs, APM tools, DB slow queries, and infra dashboards to pinpoint exact failure sources — whether in network, database, cache, CPU, or code logic layers.

We provide full reports with throughput, latency percentiles, error ratios, scalability curves, and hardware requirements. Teams receive tuning steps, infra sizing, and deployment readiness grading.