Latency

Practical techniques for delivering low latency software. From first principles to production-ready code, Latency teaches you how to make your software faster at every layer of the stack. You’ll learn what latency really is, how it differs from bandwidth, and why it matters for user experience. Then, guided by practical examples, you’ll apply Little’s Law, lock-free algorithms, and architect caching systems that scale. You’ll discover how your code runs differently on distributed systems, databases, and operating systems, and understand the common latency-causing issues in each situation. In Latency you’ll learn how to: Define latency, distinguish it from bandwidth, and understand its impact on user experience Model performance with Little’s Law and Amdahl’s Law, then measure and visualize delays Optimize data access with colocation, replication, partitioning, and caching Accelerate logic with algorithmic improvements, memory tuning, and lock-free concurrency Minimize delays with asynchronous processing, predictive techniques, and speculative execution Put simply, latency is the delay between a cause and effect. In practice, too much latency can create problems throughout a software system, ranging from inaccurate calculations and timeouts to impatient users simply abandoning your applications. Latency issues can be challenging to avoid and troubleshoot. This book balances theory with practical implementations, turning academic research into useful techniques you can apply to your projects. About the technology From lost microseconds routing server messages to page loads that keep users waiting, latency can kill good software. This one-of-a-kind book shows you how to spot, understand, and fix unwanted latency in your applications and infrastructure. About the book Latency: Reduce delay in software systems shows you how to troubleshoot latency in existing applications and create low latency systems from the ground up. In it, you’ll discover high-impact fixes for measuring latency and advanced optimizations in memory management, concurrency models, and predictive execution. The tips and tricks, hands-on projects, and personal insights make this book as enjoyable as it is practical. What‘s inside How to model and measure latency Organizing application data for low latency Accelerating your code Hiding latency About the reader For software engineers with a working knowledge of backends. Examples in Rust. About the author Pekka Enberg has experience in operating systems, databases, and distributed systems, having worked on the Linux kernel and the Scylla and Turso databases. Table of Contents Part 1 1 Introduction 2 Modeling and measuring latency Part 2 3 Colocation 4 Replication 5 Partitioning 6 Caching Part 3 7 Eliminating work 8 Wait-free synchronization 9 Exploiting concurrency Part 4 10 Asynchronous processing 11 Predictive techniques A Further reading