82:T517,Can a system be considered truly reliable if it isn't fundamentally secure? Or can it be considered secure if it's unreliable? Security is crucial to the design and operation of scalable systems in production, as it plays an important part in product quality, performance, and availability. In this book, experts from Google share best practices to help your organization design scalable and reliable systems that are fundamentally secure. Two previous O’Reilly books from Google―Site Reliability Engineering and The Site Reliability Workbook―demonstrated how and why a commitment to the entire service lifecycle enables organizations to successfully build, deploy, monitor, and maintain software systems. In this latest guide, the authors offer insights into system design, implementation, and maintenance from practitioners who specialize in security and reliability. They also discuss how building and adopting their recommended best practices requires a culture that’s supportive of such change. You’ll learn about secure and reliable systems through: Design strategies Recommendations for coding, testing, and debugging practices Strategies to prepare for, respond to, and recover from incidents Cultural best practices that help teams across your organization collaborate effectively83:T523,If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place. Analyze data distributions and visualize patterns using Python libraries Improve predictions and insights with regression models Dive into specialized topics like time series analysis and survival analysis Integrate statistical techniques and tools for validation, inference, and more Communicate findings with effective data visualization Troubleshoot common data analysis challenges Boost reproducibility and collaboration in data analysis projects with interactive notebooks84:T5da,Salary surveys worldwide regularly place software architect in the top 10 best jobs, yet no real guide exists to help developers become architects. Until now. This updated edition provides a comprehensive overview of software architecture's many aspects, with five new chapters covering the latest insights from the field. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming architecture, governance, data, generative AI, team topologies, and many other topics. Mark Richards and Neal Ford-hands-on practitioners who have taught software architecture classes professionally for years-focus on architecture principles that apply across all technology stacks. You'll explore software architecture in a modern light, taking into account all the innovations of the past decade. This book examines: Architecture styles and patterns: Microservices, modular monoliths, microkernels, layered architectures, and many more Components: Identification, coupling, cohesion, partitioning, and granularity Soft skills: Effective team management, collaboration, business engagement models, negotiation, presentations, and more Modernity: Engineering practices and operational approaches that have changed radically in the past few years, including cloud considerations and generative AI Architecture as an engineering discipline: Repeatable results, metrics, and concrete valuations that add rigor to software architecture85:T519,

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.

Get a crash course in Python
Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science
Collect, explore, clean, munge, and manipulate data
Dive into the fundamentals of machine learning
Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering
Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

86:T791, Since the last edition of this book appeared three years ago, there has been a major climate change with regard to web standards. Designers are no longer using (X)HTML as a design tool, but as a means of defining the meaning and structure of content. Cascading Style Sheets are no longer just something interesting to tinker with, but rather a reliable method for handling all matters of presentation, from fonts and colors to the layout of the entire page. In fact, following the standards is now a mandate of professional web design. In this update to the popular book, Learning Web Design, author Jennifer Niederst Robbins shares the knowledge she's gained from years of web design experience, both as a designer and a teacher. This book starts from the beginning -- defining the basic components of how the Internet works and what comprises web sites - and builds from there. After reading this book, you'll have a solid foundation in HTML, CSS, graphics, and design principles that you can immediately put to use in creating effective web pages. In the third edition, Jennifer has updated the book to cover CSS, rich media applications, web standards, and much more. She has also added exercises that help you to learn various techniques and short quizzes that make sure you're up to speed with key concepts. The companion CD-ROM contains material for all the exercises in the book, as well as trial versions of popular software for graphics creation and editing, web-page and web-site creation, and audio- and video- integration. Unlike other beginner books, Learning Web Design leaves no holes in your education. It gives you everything you need to create basic web sites and will prepare you for moreadvanced web work. If you are interested in web design, this book is the place to start. After finishing it, you'll be ready for the author's bestselling companion reference, Web Design in a Nutshell. (Bookdata) 87:T517,Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals.

You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library.

Get a gentle overview of big data and Spark
Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples
Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames
Understand how Spark runs on a cluster
Debug, monitor, and tune Spark clusters and applications
Learn the power of Structured Streaming, Spark’s stream-processing engine
Learn how you can apply MLlib to a variety of problems, including classification or recommendation88:T626,Discover how to coach your team to become more Agile. "Agile Coaching" de-mystifies agile practices--it's a practical guide to creating strong agile teams. Packed with useful tips from practicing agile coaches Rachel Davies and Liz Sedley, this book gives you coaching tools that you can apply whether you are a project manager, a technical lead, or working in a software team. To lead change, you need to expand your toolkit, and this book gives you the tools you need to make the transition from agile practitioner to agile coach. "Agile Coaching" is all about working with people to create great agile teams. You'll learn how to build a team that produces great software and has fun doing it. In the process, you'll grow a team that's self-sufficient and skillful. This book provides you with deeper knowledge of how agile practices work and how to inspire your team to improve. Discover how to coach your team through the agile lifecycle, from planning to writing software. Learn the secrets of running effective agile meetings and how to get your team following a consistent approach to creating software. You'll find chapters dedicated to introducing Test-Driven Development, designing Retrospectives, and making progress visible. Find out what works and what to avoid when introducing agile practices to your team. Throughout the book the authors share their personal coaching stories from experience with real teams, giving you insights into what works and what to avoid. Each chapter also covers hurdles that you and your team may face and what to do to clear them.89:T8b0,Some developers thrash around aimlessly looking for a bug without concrete results. Others have the knack of unerringly zeroing in on the root cause of a bug. Are they geniuses? Just lucky? No, they've learned the secrets of professional debugging. This book will equip you with the tools, techniques and approaches-proven in the crucible of professional software development-to ensure that you can tackle any bug with confidence. You'll learn how to handle every stage of the bug life-cycle, from constructing software that makes debugging easy, through detection, reproduction, diagnosis and rolling out your eventual fix. If you develop software, sooner or later you're going to discover that it doesn't always behave as you intended. Working out why it's misbehaving can be hard. Sometimes very hard. "Debug It " is here to help All bugs are different: there is no silver bullet. You've got to rely upon your intellect, intuition, detective skills and yes, even a little luck. But that doesn't mean that you're completely on your own-there is much you can learn from those who have gone before. This book distills decades of hard-won experience gained in the trenches of professional software development, giving you a head-start and arming you with the tools you need to get to the bottom of the problem, whatever you're faced with. Whether you're writing Java or assembly language, targeting servers or embedded micro-controllers, using agile or traditional approaches, the same basic bug-fixing principles apply. From constructing software that is easy to debug (and incidentally less likely to contain bugs in the first place), through handling bug reports to rolling out your ultimate fix, we'll cover the entire life-cycle of a bug. You'll learn about the empirical approach, which leverages your software's unique ability to show you what's really happening, the importance of finding a reliable and convenient means of reproducing a bug, and common pitfalls so you can avoid them. You'll see how to use commonly available tools to automatically detect problems before they're reported by customers and how to construct "transparent software" that provides access to critical information and internal state.8a:T596,Get ready to create distributed sensor systems and intelligent interactive devices using the ZigBee wireless networking protocol and Series 2 XBee radios. By the time you're halfway through this fast-paced, hands-on guide, you'll have built a series of useful projects, including a complete ZigBee wireless network that delivers remotely sensed data.

Radio networking is creating revolutions in volcano monitoring, performance art, clean energy, and consumer electronics. As you follow the examples in each chapter, you'll learn how to tackle inspiring projects of your own. This practical guide is ideal for inventors, hackers, crafters, students, hobbyists, and scientists.

Investigate an assortment of practical and intriguing project ideas
Prep your ZigBee toolbox with an extensive shopping list of parts and programs
Create a simple, working ZigBee network with XBee radios in less than two hours -- for under $100
Use the Arduino open source electronics prototyping platform to build a series of increasingly complex projects
Get familiar with XBee's API mode for creating sensor networks
Build fully scalable sensing and actuation systems with inexpensive components
Learn about power management, source routing, and other XBee technical nuances
Make gateways that connect with neighboring networks, including the Internet

8b:T6ae,

The freeware Apache web server runs on about half of the world's existing web sites, and it is rapidly increasing in popularity.Apache: The Definitive Guide, written and reviewed by key members of the Apache Group, is the only complete guide on the market today that describes how to obtain, set up, and secure the Apache software.

Apache was originally based on code and ideas found in the most popular HTTP server of the time: NCSA httpd 1.3 (early 1995). It has since evolved into a far superior system that can rival (and probably surpass) almost any other Unix-based HTTP server in terms of functionality, efficiency, and speed. The new version now includes support for Win32 systems. This new second edition ofApache: The Definitive Guidefully describes Windows support and all the other Apache 1.3 features. Contents include:

The history of the Apache Group
Obtaining and compiling the server
Configuring and running Apache on Unix and Windows, including such topics as directory structures, virtual hosts, and CGI programming
The Apache 1.3 Module API
Apache security
A complete list of configuration directives

WithApache: The Definitive Guide, web administrators new to Apache can get up to speed more quickly than ever before by working through the tutorial demo. Experienced administrators and CGI programmers, and web administrators moving from Unix to Windows, will find the reference sections indispensable.Apache: The Definitive Guideis the definitive documentation for the world's most popular web server. Includes CD-ROM with Apache manuals and demo sites discussed in the book.

8c:T469,As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are taking an interest in high-level software design patterns such as hexagonal/clean architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn't always straightforward. With this hands-on guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity-and get the most value out of their test suites. Each pattern is illustrated with concrete examples in beautiful, idiomatic Python, avoiding some of the verbosity of Java and C# syntax. Patterns include: Dependency inversion and its links to ports and adapters (hexagonal/clean architecture) Domain-driven design's distinction between Entities, Value Objects, and Aggregates Repository and Unit of Work patterns for persistent storage Events, commands, and the message bus Command-query responsibility segregation (CQRS) Event-driven architecture and reactive microservices8d:T533,Docker is rapidly changing the way organizations deploy software at scale. However, understanding how Linux containers fit into your workflow-and getting the integration details right-is not a trivial task. With the updated edition of this practical guide, you'll learn how to use Docker to package your applications with all of their dependencies and then test, ship, scale, and support your containers in production. This edition includes significant updates to the examples and explanations that reflect the substantial changes that have occurred over the past couple of years. Sean Kane and Karl Matthias have added a complete chapter on Docker Compose, deeper coverage of Docker Swarm mode, introductions to both Kubernetes and AWS Fargate, examples on how to optimize your Docker images, and much more. Learn how Docker simplifies dependency management and deployment workflow for your applications Start working with Docker images, containers, and command line tools Use practical techniques to deploy and test Docker containers in production Debug containers by understanding their composition and internal processes Deploy production containers at scale inside your data center or cloud environment Explore advanced Docker topics, including deployment tools, networking, orchestration, security, and configuration8e:T52e,If you're a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering-data structures and algorithms-in a way that's clearer, more concise, and more engaging than other materials. By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You'll explore the important classes in the Java collections framework (JCF), how they're implemented, and how they're expected to perform. Each chapter presents hands-on exercises supported by test code online. Use data structures such as lists and maps, and understand how they work Build an application that reads Wikipedia pages, parses the contents, and navigates the resulting data tree Analyze code to predict how fast it will run and how much memory it will require Write classes that implement the Map interface, using a hash table and binary search tree Build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results Other books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.8f:T558,Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks-scikit-learn and TensorFlow-author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details90:T510,What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company, from analysts and management to the C-Suite and the board. Through interviews and examples from data scientists and analytics leaders in a variety of industries, author Carl Anderson explains the analytics value chain you need to adopt when building predictive business models-from data collection and analysis to the insights and leadership that drive concrete actions. You'll learn what works and what doesn't, and why creating a data-driven culture throughout your organization is essential.Start from the bottom up: learn how to collect the right data the right way Hire analysts with the right skills, and organize them into teams Examine statistical and visualization tools, and fact-based story-telling methods Collect and analyze data while respecting privacy and ethics Understand how analysts and their managers can help spur a data-driven culture Learn the importance of data leadership and C-level positions such as chief data officer and chief analytics officer91:T55e,Today's synthetic biologists are in the early stages of engineering living cells to help treat diseases, sense toxic compounds in the environment, and produce valuable drugs. With this manual, you can be part of it. Based on the BioBuilder curriculum, this valuable book provides open-access, modular, hands-on lessons in synthetic biology for secondary and post-secondary classrooms and laboratories. It also serves as an introduction to the field for science and engineering enthusiasts. Developed at MIT in collaboration with award-winning high school teachers, BioBuilder teaches the foundational ideas of the emerging synthetic biology field, as well as key aspects of biological engineering that researchers are exploring in labs throughout the world. These lessons will empower teachers and students to explore and be part of solving persistent real-world challenges.Learn the fundamentals of biodesign and DNA engineering Explore important ethical issues raised by examples of synthetic biology Investigate the BioBuilder labs that probe the design-build-test cycle Test synthetic living systems designed and built by engineers Measure several variants of an enzyme-generating genetic circuit Model "bacterial photography" that changes a strain's light sensitivity Build living systems to produce purple or green pigment Optimize baker's yeast to produce ? -carotene92:T7f9,HTML has been on a wild ride. Sure, HTML started as a mere markup language, but more recently HTMLs put on some major muscle. Now weve got a language tuned for building web applications with Web storage, 2D drawing, offline support, sockets and threads, and more. And to speak this language youve got to go beyond HTML5 markup and into the world of the DOM, events, and JavaScript APIs.

Now you probably already know all about HTML markup (otherwise known as structure) and you know all aboutCSS style (presentation), but what youve been missing is JavaScript (behavior). If all you know about are structure and presentation, you can create some great looking pages, but theyre still just pages. When you add behavior with JavaScript, you can create an interactive experience; even better, you can create full blown web applications.

Head First HTML5 Programming is your ultimate tour guide to creating web applications with HTML5 and JavaScript, and we give you everything you need to know to build them, including: how to add interactivity to your pages, how to communicate with the world of Web services, and how to use the great new APIs being developed for HTML5.

Here are just some of the things youll learn in Head First HTML5 Programing:

Learn how to make your pages truly interactive by using the power of the DOM.
Finally understand how JavaScript works and take yourself from novice to well-informed in just a few chapters.
Learn how JavaScript APIs fit into the HTML5 ecosystem, and how to use any API in your web pages.
Use the Geolocation API to know where your users are.
Bring out your inner artist with Canvas, HTML5s new 2D drawing surface.
Go beyond just plugging a video into your pages, and create custom video experiences.
Learn the secret to grabbing five megabytes of storage in every users browser.
Improve your pages responsiveness and performance with Web workers.
And much more.

93:T51e,Want to understand a certain PHP programming technique? Or learn how to accomplish a particular task? This cookbook is the first place to look. With more than 350 code-rich recipes revised for PHP 5.4 and 5.5, this third edition provides updated solutions for generating dynamic web content - everything from using basic data types to querying databases, and from calling RESTful APIs to testing and securing your site. Each recipe includes code solutions that you can freely use, along with a discussion of how and why they work. Whether you're an experienced PHP programmer or coming to PHP from another language, this book is an ideal on-the-job resource. You'll find recipes to help you with: Basic data types: strings, numbers, arrays, and dates and times Program building blocks: variables, functions, classes, and objects Web programming: cookies, forms, sessions, and authentication Database access using PDO, SQLite, and other extensions RESTful API clients and servers, including HTTP, XML, and OAuth Key concepts: email, regular expressions, and graphics creation Designing robust applications: security and encryption, error handling, debugging and testing, and performance tuning Files, directories, and PHP's Command Line Interface Libraries and package managers such as Composer and PECL94:T4c9,JSON is becoming the backbone for meaningful data interchange over the internet. This format is now supported by an entire ecosystem of standards, tools, and technologies for building truly elegant, useful, and efficient applications. With this hands-on guide, author and architect Tom Marrs shows you how to build enterprise-class applications and services by leveraging JSON tooling and message/document design. JSON at Work provides application architects and developers with guidelines, best practices, and use cases, along with lots of real-world examples and code samples. You’ll start with a comprehensive JSON overview, explore the JSON ecosystem, and then dive into JSON’s use in the enterprise. Get acquainted with JSON basics and learn how to model JSON data Learn how to use JSON with Node.js, Ruby on Rails, and Java Structure JSON documents with JSON Schema to design and test APIs Search the contents of JSON documents with JSON Search tools Convert JSON documents to other data formats with JSON Transform tools Compare JSON-based hypermedia formats, including HAL and jsonapi Leverage MongoDB to store and access JSON documents Use Apache Kafka to exchange JSON-based messages between services95:T5a9,Get thoroughly up to speed on Android programming, and learn how to create up-to-date user experiences for both handsets and tablets. With this books extensively revised second edition, youll focus on Android tools and programming essentials, including best practices for using Android 4 APIs. If youre experienced with Java or Objective-C, youll gain the knowledge necessary for building well-engineered applications.

Programming Android is organized into four parts:

Part One helps programmers with some Java or iOS experience get off to a fast start with the Android SDK and Android programming basics.
Part Two delves into the Android framework, focusing on user interface and graphics class hierarchies, concurrency, and databases. Its a solid foundation for understanding of how the most important parts of an Android application work.
Part Three features code skeletons and patterns for accelerating the development of apps that use web data and Android 4 user interface conventions and APIs.
Part Four delivers practical coverage of Androids multimedia, search, location, sensor, and account APIs, plus the Native Development Kit, enabling developers to add advanced capabilities.

This updated edition of Programming Android focuses on the knowledge and developer priorities that are essential for successful Android development projects.96:T49c,If you want to learn how to build efficient React applications, this is your book. Ideal for web developers and software engineers who understand how JavaScript, CSS, and HTML work in the browser, this updated edition provides best practices and patterns for writing modern React code. No prior knowledge of React or functional programming is necessary. Authors Alex Banks and Eve Porcello show you how to create UIs that can deftly display changes without page reloads on large-scale data-driven websites. You'll also discover how to work with functional programming and the latest ECMAScript features. Once you learn how to build React components with this hands-on guide, you'll understand just how useful React can be in your organization. Understand key functional programming concepts with JavaScript Look under the hood to learn how React runs in the browser Create application presentation layers with React components Manage data and reduce the time you spend debugging applications Explore React's component lifecycle to improve UI performance Use a routing solution for single-page application features Learn how to structure React applications with servers in mind97:T915,Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models. The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach. AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications. Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the process for developing an AI application, the challenges at each step, and approaches to address them Explore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they work Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them Choose the right model, dataset, evaluation benchmarks, and metrics for your needs Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI. AI Engineering builds upon and is complementary to Designing Machine Learning Systems (O'Reilly).3c:["$","$L7d",null,{"state":{"mutations":[],"queries":[{"dehydratedAt":1793549227793,"state":{"data":{"pages":[{"requestId":"507da2a6-f1dd-4c28-bb50-28a064693af2","total":{"value":3518,"relation":"eq"},"rows":[{"entityType":"book","isbn":"9781492083122","id":974198,"score":2,"position":168,"book":{"id":974198,"isbn":"9781492083122","created":"2025-07-22T07:41:20.000Z","title":"Building Secure and Reliable Systems","description":"$82","htmlDescription":null,"pages":400,"language":"eng","depth":30,"height":176,"width":226,"weight":863,"edition":null,"publishDate":"2020-03-31","authorNames":"Ana Oprea, Betsy Beyer, Paul Blankinship, Heather Adkins, Piotr Lewandowski","publisherName":"O'Reilly 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