In this practical book, author Susan Fowler presents a set of microservice standards in depth, drawing from her experience standardizing over a thousand microservices at Uber. You’ll learn how to design microservices that are stable, reliable, scalable, fault tolerant, performant, monitored, documented, and prepared for any catastrophe.

Author Jeff Patton shows you how changeable story maps enable your team to hold better conversations about the project throughout the development process. Your team will learn to come away with a shared understanding of what you’re attempting to build and why.

This book provides developers, enterprise architects, and site reliability engineers with a sound introduction to bleeding-edge Linux-based tools and technologies for both development and production environments. If you already know Linux administration basics, author Sam Alapati will help you explore and evaluate tools for virtualization, cloud and big data, configuration management and continuous delivery, and operations monitoring.

Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive applications. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

OSCON is where the open source community gathers to celebrate achievements, spark new ideas, and map the future of open computing through collaboration, education, and connecting people with technology.