10h ago · 2 min read · Kafka's config options cause more production issues than any other part of it. Here's what actually matters. acks and min.insync.replicas — the durability decision # Producer side acks=all # wait for all ISR replicas (strongest) re...
Join discussion4d ago · 8 min read · I was on-call when the P1 hit. Slack lighting up, a downstream team's database rejecting writes. Constraint violations everywhere. I pulled up the logs. The events looked fine. The schema was correct.
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5d ago · 13 min read · TLDR: Kafka is a distributed event store. Unlike a traditional queue (RabbitMQ) where messages disappear after reading, Kafka stores them in a persistent Log. This allows multiple consumers to read the same data at their own pace, replay history, and...
Join discussion5d ago · 9 min read · At 2:14am on a Tuesday, my phone buzzed. The order service was timing out. Which was timing out the inventory service. Which was failing to respond to the notification service. Which caused the analytics pipeline to back up and start throwing 503s. S...
Join discussionMar 3 · 8 min read · Message Queue Tools: RabbitMQ, Redis Streams, NATS, and Kafka Compared Message queues decouple producers from consumers, smooth out traffic spikes, and let you build systems where components can fail independently. But "just add a queue" is deceptive...
Join discussionFeb 18 · 9 min read · Designing systems at scale is not just about writing code. It’s about handling millions of users, ensuring consistency, preventing race conditions, and keeping latency low. In this blog, we’ll design a production-level URL Shortener system using a st...
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Feb 18 · 9 min read · Designing systems at scale is not just about writing code. It’s about handling millions of users, ensuring consistency, preventing race conditions, and keeping latency low. In this blog, we’ll design a production-level URL Shortener system using a st...
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