Systems Engineering

In the years following her role as the lead author of the international best seller, Limits to Growth - the first book to show the consequences of unchecked growth on a finite planet - Donella Meadows remained a pioneer of environmental and social analysis until her untimely death in 2001. Thinking in Systems is a concise and crucial book offering insight for problem-solving on scales ranging from the personal to the global. Edited by the Sustainability Institute's Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world....

"Understanding Systems Engineering: A Practical Guide to Today’s Technology" explores modern systems engineering with a focus on integrating disciplines to manage complex systems throughout their lifecycle. Informed by the author’s diverse experience, the book addresses challenges professionals face and offers insights into the evolving field.

Getting to the good solutions of complex management challenges can make the difference between fulfillment and frustration for teams, and, ultimately, the success or failure of companies. Will Larson's An Elegant Puzzle orients around the particular challenges of engineering management - from sizing teams to technical debt to succession planning - and provides a path to the good solutions.

AI makes headlines, but many organizations face stalled projects, fragile infrastructure, and costly deployments. The AI Engineering Bible fills this gap. For engineers, leads, architects, and product owners, it offers a systematic approach to production-ready AI—grounded in best practices, scalable infrastructure, and real-world use. Covering the full AI lifecycle—from problem definition and data acquisition to deployment, optimization, and maintenance—it provides the depth needed to lead AI at scale.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient - lessons directly applicable to your organization.

Author Brendan Burns demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. This fully updated second edition includes new chapters on AI inference, AI training, and building robust systems for the real world.

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.

Futurologist Luna Lee presents possibilities for the future of space travel in the next 100 years.

Permaculture makes the most use of what nature provides for us by using specific design strategies to maximize nature’s gifts, such as food, energy, and shelter. A counter to heavy industrial farming, permaculture is all about conscious planning that caters to the human needs while also respecting and healing the natural environment. At its core, it involves drawing inspiration from nature to build an ecosystem that thrives just like any other. If you want to start practicing permaculture and reap all its benefits, then you need to listen to this audiobook today!

As organizations shift from monolithic applications to smaller, self-contained microservices, distributed systems have become more fine-grained. But developing these new systems brings its own host of problems. This expanded second edition takes a holistic view of topics that you need to consider when building, managing, and scaling microservices architectures. Through clear examples and practical advice, author Sam Newman gives everyone from architects and developers to testers and IT operators a firm grounding in the concepts.

This audiobook teaches you how to build an intelligent system from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems.

There are no easy decisions in software architecture. Instead, there are many hard parts—difficult problems or issues with no best practices—that force you to choose among various compromises. With this book, you'll learn how to think critically about the trade-offs involved with distributed architectures. Architecture veterans and practicing consultants Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani discuss strategies for choosing an appropriate architecture.

Technology has gradually transitioned from wired to wireless over the years with tons of benefits. From the internet of things to wireless communication, we are all witnesses of the huge benefits of wireless technologies. This audiobook covers various subjects and highlights both the benefits and challenges of wireless technologies.

Written by an expert who has created systems ranging from DNA scanners to children's toys, this book is ideal for intermediate and experienced programmers, no matter what platform you use. This expanded second edition includes new chapters on IoT and networked sensors, motors and movement, debugging, data handling strategies, and more.

The search for success - oh, how daunting it often is. We all want it, but we do not all know how to attain it. Every day, we are bombarded with standards of success we believe apply to us. However, success is not a one-size-fits-all garment. Success is not something we can simply shop and wear. No, success is scalable, completely variable depending on the person pursuing it. Most importantly, success is something we must keenly focus on attaining in alignment with our own personal goals and genuine interests in life.

Estimating the cost of a project is critical to your business success. Done correctly, your company is profitable. Done wrong, you lose money. Michael Stone, a successful construction business consultant and trainer, shares his years of experience estimating residential projects in this manual. Estimating isn't difficult when you have a system. The purpose of this book is to help you create that system. It's an approach that helps you estimate without having to think about the process. An orderly approach makes estimating easier and more accurate.

After an unfortunate accident, Handry is forced to wander a world he doesn't understand, searching for meaning. He soon discovers that the life he thought he knew is far stranger than he could even possibly imagine. Can an unlikely savior provide the answers to the questions he barely comprehends?

Dans cet ouvrage de synthèse, fruit de toute une vie de recherche aux confins de la psychologie et de l'économie, le prix Nobel Daniel Kahneman nous emmène à la rencontre des deux "personnages" qui se partagent notre esprit, régissant notre façon de penser et de prendre des décisions.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.