Introduction Command Query Responsibility Segregation (CQRS) is an architectural pattern that separates reads (queries) from writes (commands). Rather than using a single data model and layer to both modify and read state, CQRS encourages designing optimized models and pathways for each. This separation can improve scalability, performance, and clarity—especially in complex domains—while introducing new challenges around consistency, messaging, and operational complexity. This guide provides a practical, vendor-neutral overview of CQRS: what it is, when it helps, how to implement it (with and without event sourcing), and the pitfalls to avoid. Code examples are provided to illustrate implementation techniques. ...

Introduction Automated Market Makers (AMMs) are the liquidity engines powering most decentralized exchanges (DEXs). Instead of relying on traditional order books and human market makers, AMMs use deterministic formulas—called bonding curves—to continuously quote buy and sell prices for assets. This design unlocks 24/7 liquidity, permissionless market creation, and composability across decentralized finance (DeFi). Yet AMMs also introduce new mechanics and risks: slippage, impermanent loss, MEV (maximal extractable value), and complex design trade-offs. ...

Introduction Distributed systems underpin many critical applications today, from blockchain networks to large-scale cloud services. However, coordinating agreement (consensus) among distributed nodes is challenging, especially when some nodes may behave maliciously or unpredictably. This challenge is famously captured by the Byzantine Generals Problem, which models how independent actors can safely agree on a strategy despite some actors potentially acting against the group’s interest. This blog post will take you from zero to hero on Byzantine consensus in distributed systems. We’ll explore the problem’s origins, why it matters, fundamental solutions like Byzantine Fault Tolerance (BFT), and real-world applications. ...

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 In modern software development, improving application responsiveness and performance is critical. Two fundamental concepts that help achieve this are parallelism and asynchronous programming. Although often used interchangeably, they represent distinct approaches to handling multiple tasks and can be combined for maximum efficiency. This tutorial provides an in-depth exploration of parallelism and asynchronous programming: what they mean, how they differ, how they relate to concurrency, and how to implement them effectively. We will also include practical examples and point to valuable resources for further learning. ...