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SSSubham Sahasubham59036.hashnode.dev1d ago · 18 min read

Complete Production Grade Event Streaming Setup for Spring Services — A Comprehensive Guide

Introduction Event-driven architecture has become the default choice for distributed systems requiring decoupling, scalability, and real-time processing. Apache Kafka, combined with Spring Boot, provi

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Wwloadctlwloadctl.hashnode.dev2d ago · 7 min read

Designing an Asynchronous Communication Architecture for High-Concurrency Task Scheduling

In high-concurrency distributed systems, communication patterns have a direct impact on throughput and reliability. In this article, we will explore how WLOADCTL uses Message Queue (MQ), Shared Memory

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RMRamon Melendez Juarezcodebymelendez.hashnode.dev3d ago · 2 min read

Kafka in hospitals: real-world event architecture for HIS, LIS and billing in a Venezuelan mid-size hospital

Most Kafka “healthcare interoperability” examples are theoretical or focused on US/EU EHRs. I wanted to share a concrete case from a mid‑size hospital in Venezuela where we used Kafka as the event bac

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PMPatrick McDonaldpatbmcdonald.com4d ago · 10 min read

When Your Application Can’t Explain Its Own State

Some of the hardest production incidents are not full outages. They are the incidents where an operation finished in one place and not another. A payment provider accepts a charge, but the HTTP client

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OWOlivia Watsonoliviawatson.hashnode.dev4d ago · 3 min read

Designing Scalable Retail Microservices for Peak Black Friday Traffic

High-volume shopping events place extreme demands on online retail platforms. When millions of consumers access a digital storefront at the same time, traditional backend infrastructures often experie

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SKSachin Kamathzeliot-official.hashnode.devJul 21 · 31 min read

Kafka Partition Strategy: The Complete Guide to Designing for Scale from Day One

TL;DR Kafka partition strategy is one of the most important architectural decisions when building scalable event-driven applications. It determines how data is distributed across partitions, sets the

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ASAnik Sikderaniksikder.hashnode.devJul 18 · 7 min read

Synchronous vs Asynchronous Workloads: Why Modern Systems Cannot Afford To Wait

The Illusion of Simplicity Most software begins with a simple interaction. A user clicks a button. User ↓ Request ↓ Application ↓ Response The user asks for something. The system performs the w

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ABAniruddha Banerjeeruddhani.hashnode.devJul 17 · 8 min read

The Post-Acquisition Assumption Gap

The Post-Acquisition Assumption Gap Two years after we closed an acquisition, we found out our own pipeline still thought the company hadn't happened. Not the ERP. Not the org chart. The CDC job watch

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MGManjusha Gunturmanjushaguntur.hashnode.devJul 14 · 17 min read

From Requirement to Release: Building an AI Software Engineering Platform for Event-Driven Systems

Why Code Generation Is Not Enough The first generation of AI software engineering tools demonstrated that Large Language Models can generate production-quality code. The next generation will be measur

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MBMadhav Bhasinblog.madhav.devJul 13 · 10 min read

Observability and Scaling: Monitoring Event Lag and Handling Failure

A distributed event-driven pipeline fails differently from a monolith. When a single service goes down, you get an error page. When an event-driven pipeline degrades, it's often invisible at first — m

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#event-driven-architecture

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#event-driven-architecture

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Trending tags this week

Complete Production Grade Event Streaming Setup for Spring Services — A Comprehensive Guide

Designing an Asynchronous Communication Architecture for High-Concurrency Task Scheduling

Kafka in hospitals: real-world event architecture for HIS, LIS and billing in a Venezuelan mid-size hospital

When Your Application Can’t Explain Its Own State

Designing Scalable Retail Microservices for Peak Black Friday Traffic

Kafka Partition Strategy: The Complete Guide to Designing for Scale from Day One

Synchronous vs Asynchronous Workloads: Why Modern Systems Cannot Afford To Wait

The Post-Acquisition Assumption Gap

From Requirement to Release: Building an AI Software Engineering Platform for Event-Driven Systems

Observability and Scaling: Monitoring Event Lag and Handling Failure