Load testing services Australia - KiwiQA JMeter Gatling k6
Load Testing Services · Australia & USA

Load Testing Services
using JMeter, Gatling & k6.

KiwiQA's load testing practice combines JMeter, Gatling and k6 with cloud-native distributed load generation — simulating thousands of concurrent users from Australian and global locations to find the breaking point before your users do.

Load Testing Capabilities
JMeter / Gatling / k6
Primary load tools
Cloud Distributed
Multi-region load generation
10,000+
Virtual users per test run
p50/p95/p99
Latency percentile reporting
API Load Testing
REST / GraphQL / gRPC
AU Load Points
Sydney & Melbourne injectors
K-SPARC Load Testing Framework
Concurrent User SimulationCloud-scale
API & Web Load TestingAll protocols
Australian & US Load OriginMulti-region
Bottleneck Root-Cause AnalysisFull metrics
Related services:Performance TestingTest AutomationEnterprise TestingGet a QuoteE-commerce Load Testing Guide
The Problem

Load testing without a structured framework
finds the wrong problems too late.

A load test that runs 500 virtual users through your homepage tells you almost nothing useful. A structured load test built from production analytics finds the database connection pool that exhausts at 800 concurrent checkouts on Click Frenzy launch day.

Pain Points We Solve
✗
Scripts that simulate the wrong journeys
Test scripts simulating artificial user paths produce load results that don't reflect production failure modes — giving false confidence against the wrong bottlenecks.
✗
Round-number user counts miss the real threshold
Testing at 100, 500 or 1,000 virtual users misses the specific concurrency point — often an irregular number like 847 — where your architecture actually fails.
✗
Auto-scaling latency is invisible in short tests
Cloud auto-scaling has 2–5 minute launch latency. Load tests that run for less than 15 minutes never see the degradation window that your real users hit.
✗
p99 latency is 5–10x p50 under load
Applications sized on average latency routinely breach SLA at the tail percentiles that real users experience — but only become visible under sustained concurrent load.
✗
Burstable instances deplete credits under sustained load
AWS T-series and Azure B-series instances exhaust CPU credits under sustained load — an invisible failure mode that only manifests in tests longer than four hours.
Breaking Point0200 VU600 VU1200 VU
Load Curve Reality
Your system breaks
at a specific point.
We find it before launch.
Connection pool exhaustion
Database deadlock threshold
Memory leak under sustained load
Cache invalidation storm
Industry Reality
$5.6M
Average cost of an unplanned outage for Australian enterprises (IDC)
63%
Of performance incidents occur during peak traffic events not covered by load tests
2–5 min
Cloud auto-scaling lag that standard short-run load tests never expose
p99
Latency percentile that real users hit — invisible when sized on p50 averages
Load Testing Services

Six load testing disciplines.
One structured engagement.

Every KiwiQA load test is built from production analytics — real user journeys, real concurrency distributions and real peak patterns — not synthetic round numbers.

01
Website Load Testing
Page load simulation, user session recording and concurrent user ramp-up testing against production infrastructure — not staging.
10,000+ VU
02
API Load Testing
REST, GraphQL and gRPC endpoint load testing — throughput benchmarking, error rate under sustained concurrency, timeout validation.
gRPC / REST
03
Database Load Testing
Query performance profiling under concurrent load, connection pool exhaustion testing and deadlock detection at production-scale traffic.
Pool Exhaustion
04
Cloud Load Testing
AWS, Azure and GCP distributed load generation — validating auto-scaling behaviour, cold-start latency and spot instance eviction resilience.
Multi-Region
05
E-commerce Peak Testing
Load models built from analytics for Click Frenzy, EOFY and Black Friday — simulating real checkout, search and cart concurrency patterns.
Peak Simulation
06
Mobile App Load Testing
Backend API simulation at mobile usage patterns — burst traffic, intermittent connectivity and elevated payload retry behaviour.
Mobile Patterns
Load Testing Toolchain

JMeter, Gatling, k6.
Right tool for every protocol.

Tool selection is driven by your protocol, your team's CI/CD stack and your reporting requirements — not by which tool KiwiQA prefers. We are tool-agnostic and proficient in all three.

Apache JMeter
Distributed · 50+ injectors
Distributed mode across 50+ cloud injectors. Handles HTTP, JDBC, LDAP, FTP, SOAP and JMS protocols. Ideal for sustained soak tests and complex transaction simulation with parameterised data feeds.
Distributed mode
50+ injectors
Cloud deployment
JDBC / SQL
SOAP / REST
Gatling
High-throughput · Scala/Java
High-throughput API and microservices load testing using Scala DSL. Generates detailed HTML reports with percentile breakdowns. Preferred for gRPC, REST and WebSocket protocols requiring precise concurrency control.
Scala DSL
gRPC support
WebSocket
HTML reports
Maven / SBT
k6
JavaScript · DevOps-native
JavaScript-based load testing with native CI/CD integration. Runs in GitHub Actions, GitLab CI and Jenkins pipelines. Real-time streaming to Grafana Cloud. Ideal for API contract testing under load and threshold-driven pass/fail gates.
JavaScript
GitHub Actions
Grafana Cloud
Threshold gates
npm ecosystem
Monitoring & Observability Stack
Grafana + InfluxDB
CloudWatch
Azure Monitor
Datadog Integration
BlazeMeter Cloud
New Relic APM
Prometheus
Jaeger Tracing
ELK Stack
Methodology

K-SPARC: the 5-phase
performance engineering framework.

Every KiwiQA load test is executed within the K-SPARC performance engineering framework — a structured 5-phase methodology that ensures load tests answer engineering questions, not just produce numbers.

S
Survey
Instrument production analytics to derive real user journey distributions, session durations, geographic origin ratios and peak concurrency windows.
P
Prepare
Build parameterised load scripts from production data. Define concurrency profiles: ramp-up, steady-state and spike scenarios calibrated to real traffic shapes.
A
Appraise
Execute baseline load runs. Establish p50/p95/p99 latency baselines, throughput ceilings and error rate thresholds under controlled concurrency.
R
Rationalise
Root-cause analysis of every bottleneck discovered: connection pool sizing, query plan regressions, memory leak signatures and cache invalidation storms.
C
Combine
Consolidate findings into a prioritised remediation roadmap. Validate fixes with targeted regression load runs before sign-off.
Full methodology detail: ·
Client Testimonial

What our load testing
clients say.

“
We ran JMeter scripts ourselves and thought we were load tested. KiwiQA's team rebuilt our test from production analytics data. The real user journey distribution was completely different to our assumptions — and it found a database connection pool issue we'd never have seen with our scripts. That issue would have taken down our platform during the EOFY sale.
E
Engineering Manager
Australian E-commerce Retailer
Load Testing Insights

Expert guides on
performance engineering.

E-commerce Load Testing: AU Peak Events Guide
Performance Testing
E-commerce Load Testing: AU Peak Events Guide
Three AU peak events: Black Friday, Click Frenzy and EOFY. Performance testing approaches that keep e-commerce platforms online under maximum load.
19 Jul 202611 min read →
Performance vs Load vs Stress Testing Differences
Performance Testing
Performance vs Load vs Stress Testing Differences
Performance, load and stress testing are not the same thing. Here's what each measures and why choosing the right test for the right scenario actually matters.
7 Feb 20257 min read →
Functional vs Non-Functional Testing Explained
Performance Testing
Functional vs Non-Functional Testing Explained
Most teams underinvest in non-functional testing until a performance incident or security breach forces the issue. Here's why it matters.
22 Mar 20257 min read →
FAQ

Frequently asked questions

Everything you need to know — answered.

What is load testing and how is it different to performance testing?
+

Load testing is a subset of performance testing that applies a defined volume of concurrent users or requests to measure system behaviour under expected or peak demand. Performance testing is broader — it encompasses load, stress, spike, soak and endurance testing. Load testing answers whether your system handles your target concurrency. Performance testing answers whether it handles everything else too.

What tools does KiwiQA use for load testing?
+

KiwiQA primarily uses Apache JMeter (distributed mode, 50+ injectors), Gatling (Scala/Java, high-throughput API testing) and k6 (JavaScript-based, modern DevOps integration). We select tooling based on protocol, team integration requirements and reporting needs. All tests run with Grafana and InfluxDB real-time dashboards, with optional integration into Datadog or CloudWatch.

How many virtual users do you simulate in a load test?
+

We simulate the number of concurrent users your system requires — not an arbitrary round number. We derive target concurrency from production analytics, peak hour transaction data and projected growth. For e-commerce clients during sale events, this typically ranges from 2,000 to 50,000 concurrent users across distributed cloud injectors.

How do you load test an API?
+

API load testing requires building realistic request payloads, authentication token handling, session state management and accurate think-time distribution. We instrument each endpoint independently and as part of realistic user journeys. We measure throughput (requests/second), error rate under load, p50/p95/p99 latency percentiles and connection timeout behaviour at threshold concurrency.

How long does a load test engagement take?
+

A targeted API or single-service load test takes 3–5 days including script development, baseline execution and reporting. A full e-commerce platform load test with distributed cloud injectors, production-analytics-derived user journeys and peak event simulation typically takes 2–4 weeks. We can accelerate with existing scripts or production HAR recordings.

What is distributed cloud load testing?
+

Distributed cloud load testing generates load from multiple geographic regions simultaneously using cloud infrastructure — AWS EC2, Azure VMs or managed load platforms. It eliminates single-injector bottlenecks, simulates realistic geographic user distribution and tests CDN and regional routing behaviour. It's the only way to accurately simulate peak traffic from Australian and international users concurrently.

Load Testing Services · Australia

Find your breaking point
before your users do.

JMeter, Gatling and k6 load testing built from your production analytics — not synthetic user counts. Australian and US cloud injectors, p50/p95/p99 latency reporting and root-cause analysis included.

10K+
Virtual users per test run
from AU & US cloud injectors
K-SPARC methodology · JMeter · Gatling · k6 · 24-hour response