This course covers core concepts of concurrency control—threads, locks, transactions, and crash recovery—in the first half, then shifts to distributed systems topics like network models, clocks, replication, consensus, and fault tolerance. It lists lecture topics, objectives, prerequisites, and recommended readings for a Part IB CST Michaelmas module led by Dr. Martin Kleppmann.

• Kleppmann's 16-lecture Part IB course splits evenly: 8 lectures on concurrency control, 8 on distributed systems.
• The concurrency half moves from basic threads/locks through bakery algorithm, semaphores, monitors, and message-passing (actors, CSP) to ACID transactions, 2PL, optimistic concurrency, and crash recovery.
• The distributed half covers network/failure models, physical and logical clocks, replication and consensus (Raft, FLP impossibility, 2PC, CAP), ending with case studies on CRDTs and Google Spanner's TrueTime.
• Core texts backing the course are Tanenbaum's Modern Operating Systems, Goetz's Java Concurrency in Practice, and Kleppmann's own Designing Data-Intensive Applications.

Martin Kleppmann discusses his journey from startups to academia, and the new edition of his book Designing Data-Intensive Applications. They cover trade-offs in modern infrastructure, cloud scalability, distributed system challenges, and emerging topics like formal verification and local-first software.

• Kleppmann rewrote and reorganized Designing Data-Intensive Applications' second edition to add consensus algorithm case studies and deeper cloud failure-handling coverage
• Cloud infrastructure has shifted the core scaling trade-offs from raw hardware capacity to network behavior and API guarantees
• Kleppmann is now researching local-first software algorithms for offline-first collaboration and cryptographic methods for supply-chain transparency that preserve pricing/manufacturing secrecy
• He predicts formal verification will become more important as AI-assisted coding introduces subtle bugs that are hard to catch otherwise

In this Pragmatic Engineer episode, Martin Kleppmann walks through updates in the second edition of Designing Data-Intensive Applications and shares how his LinkedIn experience shaped the book’s core concepts. He breaks down trade-offs in multi-region and cloud architectures, explains why replication still matters more than sharding, and predicts a rise in formal verification and local-first software.

• Second edition of DDIA cuts MapReduce coverage in favor of Spark and Flink, reflecting how the field has moved on
• Manual sharding has become rare thanks to bigger hardware and managed services, making replication the fault-tolerance skill every team now needs
• Kleppmann predicts LLMs will make formal verification mainstream by automating proof generation, shifting the bottleneck to human review
• Architecture decisions like multi-region or multi-cloud are business trade-offs between risk and cost, not universal best practices