Performance

Introduction Thread pools are a foundational concurrency primitive used to execute units of work (tasks) using a fixed or managed set of threads. They improve performance by amortizing thread lifecycle costs, improve stability by bounding concurrency, and provide operational control via queueing, task rejection, prioritization, and metrics. Despite their ubiquity, thread pools are often misconfigured or misapplied, leading to oversubscription, latency spikes, deadlocks, or underutilization. This comprehensive guide covers how thread pools work, design dimensions and trade-offs, sizing formulas and tuning strategies, scheduling algorithms, instrumentation, and language-specific implementations with code examples. It is aimed at practitioners building high-throughput, low-latency systems, or anyone seeking a deep understanding of thread pool internals and best practices. ...

Introduction The Node.js event loop is the beating heart of every Node application. It powers non-blocking I/O, orchestrates timers, resolves promises, schedules callbacks, and coordinates the thread pool. Understanding it deeply is the difference between apps that feel crisp and resilient under load, and apps that stall, leak resources, or starve I/O. This tutorial takes you from beginner-friendly mental models to advanced, production-grade techniques. You’ll learn what the event loop is, how it’s implemented (libuv), the phases and microtask semantics, how timers work, how to measure and improve event loop health, and how to avoid common pitfalls like starvation and blocking. By the end, you’ll be comfortable reasoning about execution order, building reliable async flows, and tuning performance with confidence. ...

Introduction Memory-mapped files (mmap) let you treat file contents (or anonymous memory) as a region of your process’s virtual memory. Instead of calling read/write in loops, you map a file, then access it as if it were an in-memory buffer. The kernel transparently brings pages into RAM on demand and writes them back when needed. This can reduce system calls, enable zero-copy I/O, and open up powerful patterns like inter-process shared memory. ...

Batching API requests is a proven technique to improve throughput, reduce overhead, and tame the N+1 request problem across web and mobile apps. But batching is more than “combine a few calls into one.” To do it well you need to consider protocol details, error semantics, idempotency, observability, rate limiting, and more. This article explains how batching works, when to use it, and how to design and implement robust batch endpoints with real code examples. ...

Introduction WebAssembly (Wasm) is a portable binary instruction format designed to run high-performance code on the web and beyond. It lets you compile code from languages like C/C++, Rust, Go, and others into a compact, fast, and secure module that executes at near-native speed in browsers, servers, edge environments, and embedded systems. In this in-depth guide, you’ll learn: What WebAssembly is and how it works How to write and run your first Wasm module (step-by-step) Toolchains for C/C++, Rust, Go, and AssemblyScript How to integrate Wasm with JavaScript in the browser and with WASI on servers Performance strategies, memory and interop, threads and SIMD Debugging, testing, packaging, and deployment Advanced topics: Component Model, WASI, reference types, GC, and more Common pitfalls and best practices A curated list of resources to go further Whether you’re a web developer, systems programmer, or platform engineer, this guide will take you from zero to hero with Wasm. ...