A comprehensive guide to architectural patterns and strategies for building scalable applications.
A comprehensive guide to understanding and solving common application scaling challenges.
A deep dive into consensus algorithms, their applications in distributed systems, and how quorums ensure consistency across unreliable networks.
An in-depth exploration of classic distributed system design problems and trade-offs synthesized from foundational system design literature.
Privacy Policy for the Eisenhower Matrix App - How we protect your data and respect your privacy.
Key lessons on storage, transactions, and distributed coordination inspired by Alex Petrov's book.
Exploring pragmatic design patterns for building scalable, data-intensive architectures.
A comprehensive technical deep-dive into the fundamental principles of building robust data systems at scale, inspired by Martin Kleppmann's seminal work.
A deep technical analysis of modern trade-offs in distributed architectures, exploring the fundamental challenges that architects face when designing scalable systems.
