Loading...
Loading...
Quality Assurance & Testing
Test how your application handles traffic and load
Ensure your application can handle traffic spikes and high load. We use tools like k6, JMeter, and LoadForge to test performance under stress and identify bo...
Performance testing reveals how your application behaves under load—before your users experience slowdowns or crashes. We simulate hundreds or thousands of concurrent users using k6, Apache JMeter, or LoadForge, measuring response times, throughput, and resource usage. Our tests identify bottlenecks in database queries, API endpoints, and server resources, providing actionable recommendations for optimization.
Everything you need for success
How we work with you
Define expected traffic, performance goals, and scenarios
Create load test scripts and user scenarios
Establish current performance baseline metrics
Run load tests with increasing user loads
Analyze results, identify bottlenecks and issues
Provide optimization roadmap and improvements
What you'll achieve
Know your application's capacity limits
Avoid downtime during traffic spikes
Identify and fix bottlenecks before launch
Plan infrastructure scaling effectively
Improve user experience under load
Reduce server costs through optimization
Everything you need to know
Start with expected traffic. If you average 100 concurrent users, test 200-300 (2-3x normal). Then stress test to failure—500, 1000, 2000 users—to find breaking point. Also spike test: jump from 100 to 500 users instantly (simulates viral traffic or email blast). Goal: know capacity limits and what breaks first.
k6 (JavaScript-based, modern, excellent developer experience, free and paid tiers). JMeter (Java-based, mature, more complex but very powerful, free). Artillery (Node.js-based, good for simple tests). LoadForge or Loader.io (cloud-based, easy setup, paid). For most projects: k6 is best balance of power and usability.
Key metrics: Response time (p50, p95, p99 percentiles—not just average!), throughput (requests/second), error rate, concurrent users supported. Server metrics: CPU usage, memory usage, database connections, query times. Good targets: p95 response time <500ms, error rate <0.1%, database queries <100ms.
Yes. Testing identifies bottlenecks, then we optimize. Common fixes: database query optimization (N+1 queries, missing indexes), Redis caching for repeated queries, CDN for static assets, connection pooling, code-level optimizations. We provide prioritized recommendations: quick wins first (caching), then structural changes if needed.
Let's discuss your project and how we can help you achieve your goals.