Practical notes on building reliable software by Arunkumar Ganesan

CAP Theorem: The Practical Meaning

A practical explanation of CAP theorem through the choice a system makes during a network partition.

Byzantine Faults Without the Mystery

A plain explanation of Byzantine faults, where a participant may lie, corrupt data, or send conflicting answers.

Availability in Distributed Systems

A practical explanation of availability, graceful degradation, and what users should still be able to do when part of a system is unhealthy.

Distributed Computing Jargon: An A to Z Glossary

A plain language glossary of distributed systems terms, from availability and CAP to Lamport time, consensus, ordering, serialized transactions, and ZooKeeper.

Finding Performance Bottlenecks in a Serverless Microservice Chain

A practical guide to tracing, profiling, fixing, and proving performance issues across API Gateway, ALB, ECS Fargate, PostgreSQL, and DynamoDB.

JVM OOM: When the Leak Is in a Library

A data rich JVM memory troubleshooting case study using JFR, heap dumps, Eclipse Memory Analyzer, and a real Netty classloader leak.

Protect the Time That Builds Software

A practical article about protecting the time of strong engineers, reducing low value meetings, and keeping builders focused on meaningful software impact.

Real Time APIs or Events: Choose by the Shape of the Work

A practical guide to choosing real time APIs or event based architecture, including pros, cons, and a checkout example.

Linear Data Structures: How to Choose the Right One

A practical guide to arrays, linked lists, stacks, queues, and deques with operation complexity, code examples, memory hooks, and when to use each one.