Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

In this updated edition, the authors show you how zero trust lets you focus on building strong authentication, authorization, and encryption throughout, while providing compartmentalized access and better operational agility. You'll learn the architecture of a zero trust network, including how to build one using currently available technology.

In this comprehensive guide, authors Kelly Shortridge and Aaron Rinehart help you navigate the challenges of sustaining resilience in complex software systems by using the principles and practices of security chaos engineering. By preparing for adverse events, you can ensure they don't disrupt your ability to innovate, move quickly, and achieve your engineering and business goals.

Messy code is a nuisance. "Tidying" code, to make it more readable, requires breaking it up into manageable sections. In this practical guide, author Kent Beck, creator of Extreme Programming and pioneer of software patterns, suggests when and where you might apply tidyings to improve your code while keeping the overall structure of the system in mind. Instead of trying to master tidying all at once, this book lets you try out a few examples that make sense for your problem. If you have a big function containing many lines of code, you'll learn how to logically divide it into smaller chunks.