
Monolith vs Microservices: The Encyclopedia of System Architecture
A strategic guide for Architects. Covers Conway's Law, Distributed Patterns (Saga, CQRS), Modular Monolith, Migration Strategies, Glossary, and FAQ.

A strategic guide for Architects. Covers Conway's Law, Distributed Patterns (Saga, CQRS), Modular Monolith, Migration Strategies, Glossary, and FAQ.
Once you ship a public API, you can't change it freely. Compare four versioning strategies for evolving APIs without breaking clients, plus analysis of real-world choices by GitHub, Stripe, and Twilio.

Why is the CPU fast but the computer slow? I explore the revolutionary idea of the 80-year-old Von Neumann architecture and the fatal bottleneck it left behind.

Pringles can (Stack) vs Restaurant line (Queue). The most basic data structures, but without them, you can't understand recursion or message queues.

ChatGPT answers questions. AI Agents plan, use tools, and complete tasks autonomously. Understanding this difference changes how you build with AI.

After going through the docs, case studies, and tradeoffs, here's the takeaway:
1. Start Monolithic: Always start with one. Add MSA after problems emerge, not before.
2. Split only when it hurts: Split when deployment queues get too long or teams get too large. Don't split early.
3. Observability First: Don't split without log aggregation (ELK), monitoring (Prometheus), and distributed tracing (Jaeger). You'll be blind.
4. Database Separation: Won't split databases? Don't do MSA. Distributed monolith is the worst outcome.
5. Conway's Law: Check organization structure first. 5 people? Monolith. 100 people? MSA.
6. Modular Monolith: This is the answer for most cases.
I'm convinced now. Monolith isn't bad. Using it wrong is bad.