Most load testing tools show you a graph. AccessLoad shows you why your site slowed down — which query, which service, which endpoint — and what to fix. Built by the engineering team behind India's leading accessibility compliance platform.
AccessLoad doesn't just flood your server and show you a chart. Every run ends with an AI-generated analysis that names the bottleneck and tells your team where to look.
Watch requests per second, error rates, p50/p95/p99 latency, and active virtual users as your test runs — not after the fact.
After every run, an AI model reads your results and produces a plain-English report: which endpoints degraded, at what load threshold, and what to investigate first.
Split load across multiple regions or deploy workers inside your private VPC. Simulate realistic geographic traffic without coordinating infrastructure yourself.
Trigger tests from GitHub Actions, GitLab CI, or Jenkins. Set pass/fail thresholds — a run that degrades beyond your SLA fails the pipeline automatically.
Export a branded PDF report per run — suitable for client delivery, tender submissions, or internal QA sign-off. Covers summary, charts, and AI findings.
Test staging environments, internal APIs, or pre-production systems that aren't publicly reachable — workers connect through your private network directly.
No config files to write. No infrastructure to set up. Just point AccessLoad at your URL and tell it how hard to hit it.
Set the target URL, virtual user count, ramp-up pattern, and duration. Quick Test mode gets you running in under 30 seconds.
AccessLoad distributes the load across worker nodes — cloud-hosted or inside your network. No servers to provision.
Real-time dashboard shows latency, throughput, error rates, and active VUs as the test runs. Stop early if you see what you need.
A plain-English breakdown of what degraded, at what load level, and what the likely cause is — ready to paste into your Jira ticket.
The difference between a load testing tool and a load testing tool that's actually useful in an incident post-mortem.
| Capability | AccessLoad | Typical OSS tool | Enterprise SaaS |
|---|---|---|---|
| Real-time metrics dashboard | ✓ | ✓ | ✓ |
| AI-generated bottleneck analysis | ✓ | ✗ | ✗ |
| PDF report for client/tender delivery | ✓ | ✗ | Add-on |
| Private network / internal API testing | ✓ | Manual setup | ✓ |
| CI/CD pipeline integration | ✓ | Partial | ✓ |
| GIGW 3.0 performance evidence pack | ✓ | ✗ | ✗ |
| India-based data residency option | ✓ | N/A | Rarely |
| Built by a GOI-authorized compliance lab | ✓ | ✗ | ✗ |
AccessLoad is one tool in Ornate Software Solutions' portfolio. The same firm runs ITQCR — the GOI-authorized, STQC-SAB-SETL-1 empanelled testing lab that certifies Indian government websites.
WCAG 2.2, GIGW 3.0 and STQC continuous scanning with annotated screenshot evidence per issue.
Automated PDF/UA compliance with Indian language OCR. 60 seconds per document.
NVDA simulation, video proof, and STQC/GIGW audit packs. Expert-led, not just automated.
Full GIGW / WCAG certification by India's GOI-authorized STQC-SAB-SETL-1 empanelled lab.
Standard load testing generates traffic from a single machine. Distributed testing coordinates multiple geographically spread load generators — avoiding bottlenecks at the test tool itself and simulating real-world traffic from multiple regions simultaneously. For Indian government portals serving millions of citizens across states, distributed testing is the only accurate way to size infrastructure.
Traditional tools show you aggregate charts — response time, error rate, throughput. AccessLoad's AI engine correlates client-side metrics with server-side telemetry you connect (APM agents, cloud metrics, database slow query logs). It groups co-occurring anomalies into root-cause hypotheses: "database connection pool saturation at 800 VUs" rather than "response time increased at 800 VUs." The output is plain English, ready to paste into your Jira ticket.
Yes. AccessLoad accepts JMeter, k6, Gatling, and Locust scripts. Your existing test assets run as-is — AccessLoad adds distributed execution across regional nodes and the AI analysis layer on top. No rewriting required.
The p95 (95th percentile) means 95% of your users see a response faster than that number. Averages are distorted by outliers — a few very slow requests can mask widespread degradation. Industry standard is p95 under 500ms at peak load. AccessLoad tracks p50, p95, and p99 in real time and alerts when thresholds are breached.
Load testing confirms behaviour at expected peak traffic. Stress testing finds the breaking point beyond that peak. Soak testing (endurance) verifies stability over hours or days — catching memory leaks and connection pool exhaustion that only appear over time. Spike testing simulates sudden traffic surges from product launches or flash sales. AccessLoad supports all four scenarios.
Yes. AccessLoad provides a CLI and REST API for triggering tests from Jenkins, GitHub Actions, GitLab CI, and other pipelines. You define SLA thresholds — a run that exceeds them (e.g., p95 over 800ms at 500 VUs) automatically fails the build, blocking the deployment before it reaches production.
Yes. GIGW 3.0 requires government websites to be tested for performance under real load conditions — not just accessibility. AccessLoad generates a GIGW 3.0 performance evidence pack structured for STQC submission: peak capacity, p95 at test load, error rates, and AI-identified bottlenecks. It is the only Indian load testing platform that provides this directly.