Did you know that 47% of users expect a webpage to load in under 2 seconds, and a 1-second delay can reduce conversions by 7%? In large-scale applications, ensuring fast API responses and a smooth frontend experience isn’t just a luxury—it’s a necessity. Yet, as applications grow, memory leaks, inefficient data handling, and unoptimized rendering can cripple performance.

This talk dives deep into real-world performance challenges faced in high-traffic React & Node.js applications, such as those powering live sports platforms. We’ll explore techniques for reducing API response times, mitigating memory leaks in server-side JavaScript, and optimizing frontend rendering with AG Grid for handling vast datasets. Through real-world debugging examples and Chrome DevTools insights, attendees will gain actionable strategies to improve speed, scalability, and efficiency in their applications.

Key Takeaways:
Reducing API Latency – Optimizing database queries, caching strategies, and async processing for faster Node.js responses.
Memory Leak Detection & Prevention – Using Chrome DevTools to identify and fix memory issues in React & Node.js.
Frontend Performance Optimization – Improving UI responsiveness when handling large datasets with AG Grid and virtualization.
Best Practices for Scaling Applications – Balancing state management, network requests, and UI rendering for smooth user experiences.
By the end of this session, developers will walk away with proven techniques to build high-performing, scalable applications while avoiding common pitfalls in React & Node.js.

Did you know that Node.js can handle thousands of concurrent connections on a single thread, yet struggles with CPU-intensive tasks? Understanding the difference between concurrency and parallelism is key to optimizing performance in high-scale applications.

This talk takes a deep dive into Node.js’ asynchronous model, explaining how the Event Loop, non-blocking I/O, and Worker Threads enable efficient multitasking. Using real-world examples from API handling and real-time sports data processing, we’ll explore when to rely on Node’s async model and when to offload work to Worker Threads for better performance.

Key Takeaways:
Concurrency vs. Parallelism in Node.js – How they work and when to use each approach.
Deep Dive into the Event Loop – Understanding microtasks, macrotasks, and asynchronous execution.
When to Use Worker Threads – Offloading CPU-heavy tasks to prevent blocking the main thread.
Real-World Performance Optimizations – Lessons from handling large-scale API requests and real-time data updates.
By the end of this session, attendees will have a clear understanding of Node.js’ execution model and the best practices for achieving optimal performance in high-load applications.