Every distributed system you build is already taking a side in the CAP trade-off. The question is whether you made that choice deliberately or discover it during an incident. CAP states that a distributed system can guarantee at most two of three properties: Consistency, Availability, and Partition Tolerance. The critical insight most teams miss — P is not optional. Networks fail. Pods crash. AZs
Em sistemas distribuídos modernos, garantir que todos os nós tenham exatamente os mesmos dados ao mesmo tempo pode ser caro, lento ou simplesmente inviável. É aí que entra o conceito de consistência eventual, um dos pilares fundamentais de arquiteturas escaláveis. O que é Consistência Eventual? Consistência eventual é um modelo de consistência onde, dado tempo suficiente e ausência de novas atuali
When people start working with high performance computing or parallel systems, “memory” often sounds like a background detail. It’s not. The way memory is structured can completely change how your applications behave, scale, and even fail. Let’s break it down in a practical way. ⸻ What is Shared Memory? In a shared memory system, all processors access the same memory space. Think of it
Introduction Picture two doctors updating the same patient record at the same time - one in São Paulo, the other in London. Both are offline. When connectivity returns, whose changes prevail? This is not a hypothetical. It is the everyday reality of distributed systems: multiple nodes, no shared clock, no guaranteed network. The conventional answer has long been locking - one node waits while an
Most TypeScript teams shopping for an agent framework don't need one. A single generateObject call covers classification, extraction, summarization, tagging — the 80% case for production LLM work in TS right now. But once the model starts deciding what to do next, surviving deploys, or coordinating with other agents, you start shopping. And the moment you do, you discover the TS agent ecosystem is
In August 2025, a user reported that Apache Kafka v3.9.0 dropped consumer throughput by 10x. Other users reproduced it. The culprit was a configuration called min.insync.replicas, and the fix was three lines of code. Sharad Garg opened a ticket titled "Consumer throughput drops by 10 times with Kafka v3.9.0 in ZK mode." Ritvik Gupta ran controlled tests and traced the issue to min.insync.replicas.
All frameworks are eventually replaced. React is probably the first that won’t be. It's not the best language out there, it's not the language developers love the most, it's the language the robots just won't quit. Request ChatGPT to develop a todo app for you. You'll receive React. Request Copilot to generate the basic structure of a component. React. Request Claude to design a prototype for a da
Idempotency Keys: What Most Tutorials Don't Tell You Strategies for external reconciliation Thea Apr 29 #webdev #javascript #backend #api 8 reactions comments 5 min read