Data at Scale

Every engineer has a scar story about a distributed system failure—a replication lag that caused double payments, a misconfigured load balancer, or a cascading outage. Most of these problems are self-inflicted wounds from adopting complex patterns before they were needed.

This book is a practical field guide to distributed systems. It cuts through the hype and shows you how to build systems that are fast, safe, and simple. You will learn when to use distributed architecture and, more importantly, when to avoid it entirely.

Inside, you'll discover:
• The scale myth and why you might not need a distributed system
• Designing for reliability with idempotency and circuit breakers
• Choosing the right data model and database
• Replication, partitioning, and the consistency tradeoffs
• Event-driven architecture: when to use it and when to avoid it
• Batch processing vs. streaming: the practical choice
• Cost-aware architecture and the human side of distributed systems

Stop over-engineering your systems. Build a boring, reliable system that just works.