Engineering Blogs

Systematic Debugging of Distributed Systems: A Practical Guide

SystemExperts·2025

Debugging distributed systems is hard because failures happen across many machines, networks are unreliable, and timing matters. This guide teaches you a scientific approach to debugging: gather facts, form hypotheses, test them, and narrow down the cause step by step. Stop guessing randomly. Start debugging systematically.

Building Data-Intensive Systems

This guide teaches you how to pick the right database and scale your system. Think of data like water - you need the right container for the right job. A bucket works for a garden, but you need pipes and tanks for a city. Similarly, a simple database works for small apps, but big systems need special techniques like splitting data across machines (sharding) or keeping copies everywhere (replication). The hardest part is not the technology - it is knowing WHEN to use WHAT. This guide gives you a simple framework: start simple, measure problems, then pick the right tool for that specific problem.

The Universal System Design Framework

This framework works for ANY system design question. The secret? Every system is just: take data in, store it, give it back. The hard part is doing this fast, reliably, and at scale. Follow these 8 steps in order: (1) Clarify what to build - MVP features only, (2) Design the API - what endpoints do users call?, (3) Quick math - how big is this system?, (4) Decide compute model - real-time or pre-compute?, (5) Pick your database - SQL unless you have a good reason, (6) Draw the basic architecture - load balancer, servers, database, (7) Handle scale - caching, sharding, hot spots, (8) Add reliability - what happens when things break? Master this framework and you can design anything.