Kubernetes Patterns, 2nd Edition
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and principles for designing and implementing cloud native applications on Kubernetes. Each pattern includes a description of the problem and a Kubernetes-specific solution. All patterns are backed by and demonstrated with concrete code examples. This updated edition is ideal for developers and architects familiar with basic Kubernetes concepts who want to learn how to solve common cloud native challenges with proven design patterns. You'll explore: Foundational patterns covering core principles and practices for building and running container-based cloud native applications; Behavioral patterns that ...
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and principles for designing and implementing cloud native applications on Kubernetes. Each pattern includes a description of the problem and a Kubernetes-specific solution. All patterns are backed by and demonstrated with concrete code examples. This updated edition is ideal for developers and architects familiar with basic Kubernetes concepts who want to learn how to solve common cloud native challenges with proven design patterns. You'll explore: Foundational patterns covering core principles and practices for building and running container-based cloud native applications; Behavioral patterns that ...
Machine Learning for High-Risk Applications
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI - a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security; Lea ...
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI - a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security; Lea ...
Practical Linux System Administration
This essential guide covers all aspects of Linux system administration, from user maintenance, backups, filesystem housekeeping, storage management, and network setup to hardware and software troubleshooting and some application management. It's both a practical daily reference manual for sysadmins and IT pros and a handy study guide for those taking Linux certification exams. You'll turn to it frequently, not only because of the sheer volume of valuable information it provides but because of the real-world examples within and the clear, useful way the information is presented. With this book at your side, you'll be able to: Install Linux and perform initial setup duties, such as connecting to a network; Navigate the Linux filesystem via the command line; Install software from repositories and source and satisfy dependencies; Set permissions on files and directories; Create, modify, and remove user accounts; Set up networking; Format and mount filesystems; Perform basic troubleshoot ...
This essential guide covers all aspects of Linux system administration, from user maintenance, backups, filesystem housekeeping, storage management, and network setup to hardware and software troubleshooting and some application management. It's both a practical daily reference manual for sysadmins and IT pros and a handy study guide for those taking Linux certification exams. You'll turn to it frequently, not only because of the sheer volume of valuable information it provides but because of the real-world examples within and the clear, useful way the information is presented. With this book at your side, you'll be able to: Install Linux and perform initial setup duties, such as connecting to a network; Navigate the Linux filesystem via the command line; Install software from repositories and source and satisfy dependencies; Set permissions on files and directories; Create, modify, and remove user accounts; Set up networking; Format and mount filesystems; Perform basic troubleshoot ...
Design for Learning
Our purpose in this book is twofold. First, we introduce the basic skill set and knowledge base used by practicing instructional designers. We do this through chapters contributed by experts in the field who have either academic, research-based backgrounds, or practical, on-the-job experience (or both). Our goal is that students in introductory instructional design courses will be able to use this book as a guide for completing a basic instructional design project. We also hope the book is useful as a ready resource for more advanced students or others seeking to develop their instructional design knowledge and skills. Our second purpose complements the first: to introduce instructional designers to some of the most current views on how the practices of design thinking contribute towards the development of effective and engaging learning environments. While some previous books have incorporated elements of design thinking (for example, processes like prototyping), to date no instruc ...
Our purpose in this book is twofold. First, we introduce the basic skill set and knowledge base used by practicing instructional designers. We do this through chapters contributed by experts in the field who have either academic, research-based backgrounds, or practical, on-the-job experience (or both). Our goal is that students in introductory instructional design courses will be able to use this book as a guide for completing a basic instructional design project. We also hope the book is useful as a ready resource for more advanced students or others seeking to develop their instructional design knowledge and skills. Our second purpose complements the first: to introduce instructional designers to some of the most current views on how the practices of design thinking contribute towards the development of effective and engaging learning environments. While some previous books have incorporated elements of design thinking (for example, processes like prototyping), to date no instruc ...
Managing Cloud Native Data on Kubernetes
Is Kubernetes ready for stateful workloads? This open source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll learn open source technologies that are designed and built for the cloud. Authors Jeff Carpenter and Patrick McFadin provide case studies to help you explore new use cases and avoid the pitfalls others have faced. You'll get an insider's view of what's coming from innovators who are creating next-generation architectures and infrastructure. - Learn how to use basic Kubernetes resources to compose data infrastructure - Automate the deployment and operations of data infrastructure on Kubernetes using tools like Helm and o ...
Is Kubernetes ready for stateful workloads? This open source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll learn open source technologies that are designed and built for the cloud. Authors Jeff Carpenter and Patrick McFadin provide case studies to help you explore new use cases and avoid the pitfalls others have faced. You'll get an insider's view of what's coming from innovators who are creating next-generation architectures and infrastructure. - Learn how to use basic Kubernetes resources to compose data infrastructure - Automate the deployment and operations of data infrastructure on Kubernetes using tools like Helm and o ...
Beginner's Guide to Streamlit with Python
This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural l ...
This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural l ...
Quantitative User Experience Research
This book is your definitive guide to the rapidly growing role of Quantitative User Experience (Quant UX) Research in product development. The book provides an overview of the skills you need on the job, presents hands-on projects with reusable code, and shares advice on starting and developing a career. The book goes beyond basic skills to focus on what is unique to Quant UX. The authors are two of the most widely recognized practitioners in Quant UX research, and this book shares insights from their combined decades of experience. Organizations today have more data about user needs and behaviors than ever before. With this large-scale data, Quant UX researchers work to understand usage patterns, measure the impact of design changes, and inform strategic decisions. In the Quant UX role, interdisciplinary researchers apply analytical skills to uncover user needs, inform engineering and design, answer strategic business questions, and optimize software and hardware products for human ...
This book is your definitive guide to the rapidly growing role of Quantitative User Experience (Quant UX) Research in product development. The book provides an overview of the skills you need on the job, presents hands-on projects with reusable code, and shares advice on starting and developing a career. The book goes beyond basic skills to focus on what is unique to Quant UX. The authors are two of the most widely recognized practitioners in Quant UX research, and this book shares insights from their combined decades of experience. Organizations today have more data about user needs and behaviors than ever before. With this large-scale data, Quant UX researchers work to understand usage patterns, measure the impact of design changes, and inform strategic decisions. In the Quant UX role, interdisciplinary researchers apply analytical skills to uncover user needs, inform engineering and design, answer strategic business questions, and optimize software and hardware products for human ...