Exactly-Once Delivery: The Elusive Guarantee
Explore exactly-once semantics in distributed messaging - why it's hard, how Kafka and SQS approach it, and practical patterns for deduplication.
Explore exactly-once semantics in distributed messaging - why it's hard, how Kafka and SQS approach it, and practical patterns for deduplication.
Explore the classic assumptions developers make about networked systems that lead to failures. Learn how to avoid these pitfalls in distributed architecture.
The FLP impossibility theorem proves that no consensus algorithm can guarantee termination in an asynchronous system with even one faulty process. Understanding FLP is essential for distributed systems designers.
Explore Google Chubby's architecture, lock-based coordination, Paxos integration, cell hierarchy, and its influence on distributed systems design.
Google Spanner architecture combining relational model with horizontal scalability, TrueTime API for global consistency, and F1 database implementation.
Learn how gossip protocols enable scalable state sharing in distributed systems. Covers epidemic broadcast, anti-entropy, SWIM failure detection, and real-world applications like Cassandra and Consul.
Design systems that maintain core functionality when components fail through fallback strategies, degradation modes, and progressive service levels.
Explore advanced health check patterns for distributed systems including deep checks, aggregation, distributed health tracking, and health protocols.
Leader election is the process of designating a single node as the coordinator among a set of distributed nodes, critical for consensus protocols.
Understand Lamport timestamps and logical clocks for ordering distributed events without synchronized physical clocks. Learn how to determine what happened before what.