What You'll Learn:

Event Loop Optimization & Performance - Understand how the event loop really works and learn Matteo Collina's proven techniques for preventing blocking operations. We'll explore the perf_hooks module for identifying performance bottlenecks, plus practical strategies for handling CPU-intensive tasks without freezing your application.

Strategic Caching Patterns - Implement multi-layered caching strategies using Redis, in-memory stores, and HTTP caching headers. Learn when to cache, what to cache, and how to invalidate cache effectively in distributed systems.

Promise Pitfalls & Alternatives - Discover when promises become performance liabilities and explore alternatives like streams and async iterators. We'll cover memory management and the hidden costs of promise chains in high-throughput scenarios.

Worker Threads & Multithreading - Master Node.js worker threads for CPU-bound tasks, following best practices for thread pool management and data sharing. Learn when to use worker threads versus child processes, and how to architect applications that leverage multiple cores effectively.

Production Metrics & Monitoring - Implement comprehensive application metrics using Prometheus and learn to instrument your code for meaningful observability. We'll cover custom metrics, histograms, and performance-tracking patterns used in production environments.

OpenTelemetry Integration - Setup distributed tracing with OpenTelemetry to track requests across microservices. Learn to integrate with distributed systems while maintaining performance and gaining deep insights into your application's behavior through standardized telemetry collection.

By the end of this workshop, you'll have the tools and knowledge to build Node.js applications that perform well under pressure, scale horizontally, and provide the observability needed for production operations.

Prerequisites: Solid understanding of JavaScript, Node.js fundamentals, and basic async/await patterns.

We built a real-time system for Postgres→React sync using a `LISTEN/NOTIFY` Postgres trigger, GraphQL `@live` queries, a React hook and a custom ORM-inspired GraphQL query builder. Starting from ESP32 microcontroller devices sending MQTT messages and a Node/Postgres backend, we moved from polling to a stand-alone PoC with Yoga, Prisma triggers, and a custom `useLiveQuery` hook. After proving that the PoC was working we integrated with all our existing full-stack apps. So now we have low-latency UI updates, reusable cross-app logic, and easier extension for new sensor values. Great UX and excellent DX.

How we transformed a React monolith into multiple apps inside one codebase.

You always start small: one product, one team, one stakeholder. But once you succeed and need to scale, your original frontend architecture might not be ready for what comes next. As our Sales Process Orchestration Platform expanded to support multiple products and sales channels, our original monolithic application became a bottleneck.
In this talk, I'll share how we transitioned to a domain‑driven, multi‑app architecture while deliberately keeping a single React codebase. You'll see how we applied Domain‑Driven Design concepts on the frontend, structured clear boundaries between sales channels, and used Nx to orchestrate builds, enforce architecture rules, and keep teams moving independently without losing shared foundations.

Remember when profiling Node.js meant wrestling with perf, sed scripts, and mysterious V8 internals? Traditional flame graph generation has been like performing surgery with a rusty spoon, requiring kernel-level tools and arcane command-line incantations. The barrier to entry is sky high. The time to insight is glacial.
We've completely reimagined this at Platformatic with @platformatic/flame - a zero-config profiling tool that works instantly. Just run flame run server.js and get production-grade flame graphs. Combined with our WebGL-accelerated React component library (react-pprof), we handle massive datasets with buttery-smooth 60fps interactions. This isn't just another tool - it's about democratizing performance analysis.
When your Auth Service hits 96% Event Loop Utilization, you need answers NOW. I'll show you our ecosystem-compatible architecture, how we profile microservices in-memory with Watt, and real production cases where this saved millions in infrastructure costs. Performance is everybody's responsibility, but the tools have been nobody's friend until now.