Distributed Systems

Understanding the CAP Theorem

The CAP theorem is fundamental to understanding distributed systems. Learn about the trade-offs between Consistency, Availability, and Partition tolerance, and how they influence system design decisions.

Raft Consensus Algorithm Explained

Dive deep into the Raft consensus algorithm, a cornerstone of modern distributed systems. Understand leader election, log replication, and how Raft ensures consistency across nodes.

Microservices Design Patterns

Explore essential microservices patterns including service discovery, circuit breakers, and event sourcing. Learn when and how to apply these patterns in your distributed architecture.

Distributed Caching Strategies

Master distributed caching with Redis and Memcached. Learn about cache invalidation, consistency models, and how to design cache-friendly architectures.

Eventual Consistency in Practice

Understanding eventual consistency models and their implementation in real-world systems. Learn about conflict resolution, vector clocks, and designing for eventual consistency.

Load Balancing Strategies for Distributed Systems

Explore different load balancing algorithms and their trade-offs. From round-robin to consistent hashing, learn how to distribute traffic effectively across your distributed infrastructure.

Understanding Microservices Architecture

Learn how CAP theorem considerations apply to microservices design and how to handle consistency across service boundaries.

Exploring Zero Trust Architecture

Discover how security considerations intersect with distributed system design and the importance of securing distributed architectures.