Load Testing Real React Applications for Production Performance

In this talk, we'll explore how we built comprehensive load testing for React applications at Mattermost, achieving 100,000 concurrent users in production-like environments. We'll begin by revealing why traditional API testing missed critical browser issues that only emerged at scale. Next, we'll demonstrate our open-source tool that uses Playwright to run thousands of real browsers, measuring React-specific metrics like component render times, memory leaks, and state management bottlenecks. Finally, we'll share the optimization journey that reduced browser memory and enabled true production readiness, ensuring our React application performs flawlessly for enterprise customers.

Following is the structure and topics of the talk I intend to present:
1. Introduction
1.1. Self-introduction
1.2. The 100k user challenge from Fortune 500 customer
1.3. Why API testing wasn't enough

2. The Production Readiness Problem
2.1. Server metrics showed green, browsers were crashing
2.2. What "production-like" really means for React apps
2.3. The gap between development and production performance

3. Full-Stack Load Testing Architecture
3.1. Overview of our unified testing system
3.2. Coordinator pattern managing both server agents and browser instances
3.3. Real browser automation with Playwright at scale
3.4. Infrastructure as code with Terraform

4. Testing Real React Applications
4.1. Simulating actual user behavior in browsers
4.2. Measuring React-specific metrics (render times, re-renders, memory)
4.3. WebSocket to Redux to React component pipeline
4.4. Finding memory leaks that only appear after hours

5. The Journey to 100k Users
5.1. Progressive scaling discoveries (10k → 25k → 50k → 75k → 100k)
5.2. Critical issues found at each scale point
5.3. Correlation between browser degradation and server health

6. React Optimizations That Mattered

7. Measuring Production Performance
7.1. Unified metrics: Server + Browser in one dashboard
7.2. What metrics actually predict user experience
7.3. Setting performance budgets for React apps
7.4. Continuous performance testing in CI/CD

8. Lessons & Conclusion
8.1. Key takeaways for React developers
8.2. Open-source tools available today
8.3. Future directions
8.4. Q&A