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Showing all articles tagged with "Distributed Systems".
Explore why fixed timeouts fail for AI APIs and how adaptive, speculative, and load-aware fallback strategies can sharply cut tail latency while controlling cost and overload risk. Drawing on Cloudflare AI Gateway patterns, this engineering study shows how to turn fallback from a simple emergency switch into a smart, measurement-driven control layer.
Netflix moved from a monolithic architecture to microservices to fix scalability issues, single points of failure, and slow innovation as streaming demand grew. The original unified codebase faced a major 2008 outage, inefficient scaling, tight coupling, and slow deployments. By migrating to AWS and creating independent services, it enabled targeted scaling, fault isolation, and faster deployments.
When you click a bit.ly link, it feels instantaneous. Behind the simplicity is a battle-tested system that scaled to billions of redirects through Base62 encoding, heavy caching, NSQ async pipelines, and a major MySQL-to-Bigtable migration. This engineering foundation powered Bitly’s growth from a viral URL shortener to a $100M+ ARR Connections Platform. The story showcases how thoughtful architecture turns simple ideas into resilient global infrastructure.
Telegram moves billions of messages a day across a custom-built backend that skips most of the standard cloud playbook – no managed databases, no conventional load balancers, just a purpose-built protocol and a web of data centres designed so no single failure takes the system down. This piece breaks down exactly how that architecture works, from home data centres and message routing to why a famously small engineering team has been enough to keep it all running.