When Less Is More: Designing & Decoding Complex Distributed Systems
summary
A pair of Bloomberg engineers explain concrete moves for reducing accidental complexity: a year‑old pipeline 2.0 for computing ESG scores that must process 18 billion data points, a legacy→new‑stack migration serving ~900 clients, and a RabbitMQ I'm ready signal that creates two sources of truth until a supplementary readiness calculation is added. They use behavior‑driven development, C4 diagrams to reveal the “butterfly effect,” and RFCs to lock decisions; lessons center on narrowing scope, measuring collective cost of change, and iterating deployments.
AI-written summary · about
chapters (7)
- 0:00Complexity in distributed systems
- 10:19System expectations and behaviors
- 23:17Trade-offs in system design
- 37:54Stakeholder compromises
- 55:33Iterating system solutions
- 1:05:39Coupling vs cohesion
- 1:16:07Q&A
related talks
42mLarge-Scale Architecture: The Unreasonable Effectiveness of Simplicity
26mThe Power of Simplicity: Crafting Durable Software Systems
29mDeprecating Simplicity
33mFrom Enterprise Architecture to Software Design - Critical Thinking
38mAdding Simplicity to Complexity
01h 02mTools for simplified large scale systems
22mSimplicity: The Key to Software Success
36mIt's Simple...