15 docs tagged with "distributed-systems"

Crash-fault vs Byzantine-fault consensus, when BFT is needed, and the operational tradeoffs of protocols such as PBFT and HotStuff.

Core principles of distributed systems architecture including CAP theorem, consistency models, availability, partition tolerance, and key trade-offs every engineer must understand.

A comprehensive guide to the CAP theorem in distributed systems, covering network partitions, consistency models, microservice-level trade-offs, interview questions, and real-world implementations.

A comprehensive deep dive into consistent hashing, addressing modulo scaling bottlenecks, hash rings, virtual nodes, data replication, interview questions, and real-world implementations.

A complete guide to horizontal scaling — sharding strategies, consistent hashing, cross-shard complexities, rebalancing, distributed ID generation, and real-world database comparisons.

Core distributed systems concepts including consensus algorithms, leader election, vector clocks, distributed transactions, fault tolerance, and the fallacies of distributed computing.

A complete guide to Kafka brokers — what they are, how storage works, partition leadership, replication, ISR, KRaft vs ZooKeeper, log compaction, performance internals, and production monitoring. Beginner through senior depth.

A complete guide to Kafka exactly-once semantics — delivery guarantees, idempotent producer, transactions, read_committed consumers, Kafka Streams EOS, zombie producer fencing, two-phase commit internals, and production patterns. Beginner through senior depth.

A comprehensive guide comparing Apache Kafka's legacy ZooKeeper architecture with the modern KRaft (Kafka Raft) metadata mode — covering internal mechanics, failure scenarios, migration strategies, and production deep dives for senior engineers.

A comprehensive guide to the Raft Consensus Algorithm — covering leader election, log replication, safety guarantees, and how it is implemented in Apache Kafka's KRaft metadata mode.

Senior-level Redis interview questions covering data structures, persistence, clustering, cache patterns, distributed systems, and production failure scenarios.

A complete guide to the Saga Pattern — from real-world analogies for beginners to choreography vs orchestration internals, compensating transactions, idempotency, state machine design, and failure recovery for senior engineers.

Deep-dive into high write throughput techniques — sharding, partitioning, WAL internals, LSM trees, async pipelines, batching, backpressure, idempotency, and distributed transactions — with production Java/Spring code and failure mode analysis.

A complete guide to the Transactional Outbox Pattern — from the Dual-Write problem for beginners to CDC vs polling internals, at-least-once guarantees, ordering semantics, and production monitoring for senior engineers.

A comprehensive guide to Two-Phase Commit (2PC) and Three-Phase Commit (3PC) — from real-world analogies for beginners to WAL internals, failure modes, and XA implementation for senior engineers.