This article dives into the hidden failures that crop up when your database leaves the ideal “happy path.” It covers contention, slow queries, race conditions, stale reads, retries and live migrations, and shows how production realities can break simple transactional code.

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.

The removal of Python's Global Interpreter Lock (GIL) marks a significant shift in the language's ability to handle multithreading and concurrency. With the introduction of PEP 703, developers can now compile Python with or without the GIL, enabling true parallelism and reshaping how systems are designed, particularly in data science and AI. This change presents both opportunities and challenges, requiring developers to adapt to new concurrency patterns.