A practical look at using tower as the middleware layer for Rust AWS Lambda functions, with examples that build up to a DynamoDB-backed per-IP rate limiter. It covers Service, Layer, stack ordering, short-circuiting, boxed async futures, and testing middleware without deploying a Lambda. Comments
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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
A hands-on dev review focused on i18n, date/number formatting, and non-ASCII edge cases. Why I Tested TestSprite for Locale Handling Specifically Most AI testing tools get reviewed for their core functionality — does it find bugs, does it write good test code, does it integrate with CI/CD. Those reviews exist. What I couldn't find was a focused review on how TestSprite handles locale-specific edge
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