01
The database
Unindexed queries, N+1 patterns and connection-pool exhaustion account for the majority of load failures we diagnose.
LIVE CAPACITY MODEL
Load Testing Services
Simulate the traffic you actually expect, measure what happens, and fix the bottleneck before your users meet it.
THRESHOLD
Direct answer / 01
What is load testing?
Load testing is performance testing that simulates the volume of concurrent users a system is expected to handle, then measures response time, throughput and error rate under that load. It answers a direct question: will the application stay fast and stable at the traffic we plan for? A load test uses a workload model built from real usage patterns, runs against a production-like environment, and is paired with server-side monitoring so any slowdown can be traced to the specific component causing it.
What it covers
Load testing, done properly
Covers all aspects of system behaviour under varied conditions. We conduct load testing to simulate typical user activity, stress testing to find system limits, soak testing for stability over time, and spike testing to assess response to sudden surges in traffic. This comprehensive analysis helps you pinpoint bottlenecks and optimise infrastructure for a consistently reliable user experience.
Workload models built from your real analytics, not synthetic guesses
Concurrency ramped in stages so degradation curves are visible, not just pass/fail
Response time reported at p50, p95 and p99 — averages hide the users who suffer
Throughput, error rate and saturation measured per journey
Server-side metrics correlated: CPU, memory, connection pools, query time, queue depth
A retest after remediation to prove the fix, with a repeatable script you keep
01 — Model
02 — Apply load
03 — Diagnose
Findings
Where the bottleneck usually turns out to be
02
A third party
Payment, identity and shipping APIs frequently become the ceiling. Timeouts and circuit breakers matter more than your own throughput.
03
Caching and session state
Missing or wrongly scoped caches, plus sticky session state, quietly cap horizontal scaling long before the servers are busy.
Useful answers
Questions,
clarified.
Load testing simulates the number of concurrent users a system is expected to serve and measures response time, throughput and error rate under that load, to confirm the application performs acceptably at planned traffic levels.
Load testing verifies behaviour at expected traffic. Stress testing deliberately pushes beyond that level to find the breaking point and observe how the system fails and recovers.
Enough to represent your realistic peak, usually derived from analytics: peak concurrent sessions, plus headroom for growth and campaign spikes. Testing an arbitrary round number tells you very little.
Primarily k6 for scripted, version-controlled load tests, plus Apache JMeter and Gatling where protocol coverage or existing scripts make them the better fit.
A production-like environment with representative data volume is strongly preferred. Testing against an under-sized environment produces numbers that don't transfer to production.
Before every major launch or campaign, after significant architectural change, and as a scheduled baseline each quarter so gradual regressions are caught before they become incidents.
Next signal
Turn uncertainty into a clear plan.
Tell us what you are building and where quality or design is slowing you down.
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