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We Added Redis to Make Things Faster. It Made Things Worse.

A product endpoint is taking around 800ms under load. The request isn't doing anything unusual: fetch a product from PostgreSQL, serialize it, return JSON. The data changes infrequently, but the same

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ZZyVOPblog.zyvop.comSep 24 · 8 min read

Consistent Hashing: Why Adding One Server Shouldn't Move Everything

Add a fifth server to a four-server cache cluster. With the obvious approach, hash(key) % number_of_servers, something like 80% of your keys suddenly belong to a different server than they did a minut

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JMJoselo Martinezdesignednotmagic.hashnode.devSep 16 · 4 min read

Agentic AI Beyond the Hype: Why the Boundaries Are Key in Deterministic and Non-Deterministic Behavior for Agents

Let’s imagine we are implementing deterministic behavior for agent systems using control techniques (harnessing). Suddenly, we observe that the agent's actions and responses begin to become clumsy, an

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JSJayesh Sojitrajayesh-sojitra.hashnode.devSep 14 · 4 min read

3 Ways to Share State Across Microfrontends

Once independently-deployed microfrontends can share components via Module Federation, the next question shows up fast: if the checkout microfrontend needs to know the cart microfrontend's current sta

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DSDoogal Simpsondoogal.devSep 1 · 5 min read

Handling Partial Failures in Distributed Systems

Quick Answer: To handle partial failures in distributed systems, avoid complex distributed transactions. Instead, design for the "unhappy path" using an orchestration pattern (like the Saga pattern).

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ZZyVOPblog.zyvop.comAug 31 · 15 min read

How Netflix's Architecture Works in 2026: A Developer's Guide

Netflix isn't running the architecture most developers remember. The company that became famous for Eureka, Hystrix, Ribbon, Zuul and Titus has spent years replacing, reshaping, or moving responsibili

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DSDoogal Simpsondoogal.devAug 31 · 5 min read

How to Build a Scale-Proof Distributed Counter

To build a scale-proof like counter, you must decouple user actions from database writes. Start with optimistic UI updates for instant feedback, log the event to a user-specific store, and process cou

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MTMuhammad Tahirmtdeveloper.hashnode.devAug 26 · 13 min read

Orchestrating Distributed AI Agents: Ensuring Data Consistency with Event Sourcing & Kafka

This article was originally published on Muhammad Tahir's Portfolio. Introduction & Industry Context The rapid proliferation of AI agents has ushered in a new era of autonomous workflows, transforming

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NSNilay Shahanecuriousnilay.hashnode.devAug 15 · 8 min read

I Tried Designing a Distributed Rate Limiter. Here’s Every Place It Broke.

Somewhere out there is a client with a bug — a while (true) loop with a missing break condition, hammering /api/order/create as fast as the network allows. while (true) { await fetch('/api/order/cre

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DPDevesh Parmarbackend-bytes.hashnode.devAug 7 · 6 min read

Why Every Microservice Eventually Needs a Queue

Imagine you're the engineer at a UPI payments app. The Transaction Service debits the sender's account and calls the Settlement Service directly over HTTP to credit the receiver and mark the transacti

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#distributedsystems

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#distributedsystems

Explore Hashnode

Trending tags this week

We Added Redis to Make Things Faster. It Made Things Worse.

Consistent Hashing: Why Adding One Server Shouldn't Move Everything

Agentic AI Beyond the Hype: Why the Boundaries Are Key in Deterministic and Non-Deterministic Behavior for Agents

3 Ways to Share State Across Microfrontends

Handling Partial Failures in Distributed Systems

How Netflix's Architecture Works in 2026: A Developer's Guide

How to Build a Scale-Proof Distributed Counter

Orchestrating Distributed AI Agents: Ensuring Data Consistency with Event Sourcing & Kafka

I Tried Designing a Distributed Rate Limiter. Here’s Every Place It Broke.

Why Every Microservice Eventually Needs a Queue