Books published by O'Reilly Media

Shell scripts are everywhere, especially those written in bash-compatible syntax. But these scripts can be complex and obscure. Complexity is the enemy of security, but it's also the enemy of readability and understanding. With this practical book, you'll learn how to decipher old bash code and write new code that's as clear and readable as possible.Authors Carl Albing and JP Vossen show you how to use the power and flexibility of the shell to your advantage. You may know enough bash to get by, but this book will take your skills from manageable to magnificent. Whether you use Linux, Unix, Windows, or a Mac, you'll learn how to read and write scripts like an expert. Your future you will thank you.You'll explore the clear idioms to use and obscure ones to avoid, so that you can:Write useful, flexible, and readable bash code with styleDecode bash code such as ${MAKEMELC,,} and ${PATHNAME##*/}Save time and ensure consistency when automating tasksDiscover how bash idioms can make your code clean and concise

It takes a week to travel the 8,000 miles overland from Java to Kotlin. If you're an experienced Java developer who has tried the Kotlin language, you were probably productive in about the same time.You'll have found that they do things differently in Kotlin, though. Nullability is important, collections are different, and classes are final by default. Kotlin is more functional, but what does that mean, and how should it change the way that you program? And what about all that Java code that you still have to support?Your tour guides Duncan and Nat first made the trip in 2015, and they've since helped many teams and individuals follow in their footsteps. Travel with them as they break the route down into legs like Optional to Nullable, Beans to Values, and Open to Sealed Classes. Each explains a key concept and then shows how to refactor production Java to idiomatic Kotlin, gradually and safely, while maintaining interoperability.The resulting code is simpler, more expressive, and easier to change. By the end of the journey, you'll be confident in refactoring Java to Kotlin, writing Kotlin from scratch, and managing a mixed language codebase as it evolves over time.

Want to run your Kubernetes workloads safely and securely? This practical book provides a threat-based guide to Kubernetes security. Each chapter examines a particular component's architecture and potential default settings and then reviews existing high-profile attacks and historical Common Vulnerabilities and Exposures (CVEs). Authors Andrew Martin and Michael Hausenblas share best-practice configuration to help you harden clusters from possible angles of attack.This book begins with a vanilla Kubernetes installation with built-in defaults. You'll examine an abstract threat model of a distributed system running arbitrary workloads, and then progress to a detailed assessment of each component of a secure Kubernetes system.Understand where your Kubernetes system is vulnerable with threat modelling techniquesFocus on pods, from configurations to attacks and defensesSecure your cluster and workload trafficDefine and enforce policy with RBAC, OPA, and KyvernoDive deep into sandboxing and isolation techniquesLearn how to detect and mitigate supply chain attacksExplore filesystems, volumes, and sensitive information at restDiscover what can go wrong when running multitenant workloads in a clusterLearn what you can do if someone breaks in despite you having controls in place

Kubernetes has become an essential part of the daily work for most system, network, and cluster administrators today. But to work effectively together on a production-scale Kubernetes system, they must be able to speak the same language. This book provides a clear guide to the layers of complexity and abstraction that come with running a Kubernetes network.Authors James Strong and Vallery Lancey bring you up to speed on the intricacies that Kubernetes has to offer for large container deployments. If you're to be effective in troubleshooting and maintaining a production cluster, you need to be well versed in the abstraction provided at each layer. This practical book shows you how.Learn the Kubernetes networking modelChoose the best interface for your clusters from the CNCF Container Network Interface projectExplore the networking and Linux primitives that power KubernetesQuickly troubleshoot networking issues and prevent downtimeExamine cloud networking and Kubernetes using the three major providers: Amazon Web Services, Google Cloud, and Microsoft AzureLearn the pros and cons of various network tools--and how to select the best ones for your stack

How can you realize MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from setting service-level objectives to designing schemas, indexes, and queries to tuning your server, operating system, and hardware to achieve your platform's full potential. This guide also teaches database administrators safe and practical ways to scale applications through replication, load balancing, high availability, and failover.Updated to reflect recent advances in cloud- and self-hosted MySQL, InnoDB performance, and new features and tools, this revised edition helps you design a relational data platform that will scale with your business. You'll learn best practices for database security along with hard-earned lessons in both performance and database stability.Dive into MySQL's architecture, including key facts about its storage enginesLearn how server configuration works with your hardware and deployment choicesMake query performance part of your software delivery processExamine enhancements to MySQL's replication and high availabilityCompare different MySQL offerings in managed cloud environmentsExplore MySQL's full stack optimization from application-side configuration to server tuningTurn traditional database management tasks into automated processes

Developing applications for the Android mobile operating system can seem daunting, particularly if it requires learning a new programming language: Kotlin, now Android??s officialdevelopment language. With this practical book, Android developers will learn how to make the transition from Java to Kotlin, including how Kotlin provides a true advantage for gaining control over asynchronous computations.Authors Pierre-Olivier Laurence, Amanda Hinchman-Dominguez, G. Blake Meike, and Mike Dunn explore implementations of the most common tasks in native Android development, and show you how Kotlin can help you solve concurrency problems. With a focus on structured concurrency, a new asynchronous programming paradigm, this book will guide you through one of Kotlin's most powerful constructs, coroutines.Learn about Kotlin essentials and the Kotlin Collections FrameworkExplore Android fundamentals: the operating system and the application container and its componentsLearn about thread safety and how to handle concurrencyWrite sequential, asynchronous work at a low costExamine structured concurrency with coroutines, and learn how channels make coroutines communicateLearn how to use flows for asynchronous data processingUnderstand performance considerations using Android profiling toolsUse performance optimizations to trim resource consumption

Get started with Selenium WebDriver, the open source library for automating tests to ensure your web application performs as expected. In this practical hands-on book, author Boni Garcia takes Java developers through Selenium's main features for automating web navigation, browser manipulation, web element interaction, and more, with ready-to-be-executed test examples.You'll start by learning the core features of Selenium (composed of WebDriver, Grid, and IDE) and its ecosystem. Discover why Selenium WebDriver is the de facto library for developing end-to-end tests on your web application. You'll explore ways to use advanced Selenium WebDriver features, including using web browsers in Docker containers or the DevTools protocol. Selenium WebDriver examples in this book are available on GitHub.With this book, you'll learn how to:Set up a Java project containing end-to-end tests that use Selenium WebDriverConduct automated interaction with web applicationsUse strategies for managing browser-specific capabilities and cross-browser testingInteract with web forms, manage pop-up messages, and execute JavaScriptControl remote browsers and use advanced browser infrastructure for Selenium WebDriver tests in the cloudModel web pages using object-oriented classes to ease test maintenance and reduce code duplication

Securing, observing, and troubleshooting containerized workloads on Kubernetes can be daunting. It requires a range of considerations, from infrastructure choices and cluster configuration to deployment controls and runtime and network security. With this practical book, you'll learn how to adopt a holistic security and observability strategy for building and securing cloud native applications running on Kubernetes.Whether you're already working on cloud native applications or are in the process of migrating to its architecture, this guide introduces key security and observability concepts and best practices to help you unleash the power of cloud native applications. Authors Brendan Creane and Amit Gupta from Tigera take you through the full breadth of new cloud native approaches for establishing security and observability for applications running on Kubernetes.Learn why you need a security and observability strategy for cloud native applications and determine your scope of coverageUnderstand key concepts behind the book's security and observability approachExplore the technology choices available to support this strategyDiscover how to share security responsibilities across multiple teams or rolesLearn how to architect Kubernetes security and observability for multicloud and hybrid environments

AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android.Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today.Explore the options for implementing ML and AI on mobile devicesCreate ML models for iOS and AndroidWrite ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOSChoose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIsLearn privacy and ethics best practices for ML on devices

Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.Author Carl Allchin shows anyone how to find data sources and develop data analytics, and teaches those with more data expertise how to visualize data to convey findings to key business leaders more effectively. Once both your business and data experts possess the skills to work with data and interpret its significance, you can deal with questions and challenges in departments across your organization.Learn the fundamental data skills required to work with dataUse data visualization to influence change in your organizationLearn how to apply data techniques to effectively work with data end to endUnderstand how to communicate data points clearly and persuasivelyAppreciate why different stakeholders often have divergent needs and viewsCreate a playbook for using data with different departments

Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance.Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other.Draw upon mathematics to learn the foundations of financial theory and Python programmingLearn about financial theory, financial data modeling, and the use of Python for computational financeLeverage simple economic models to better understand basic notions of finance and Python programming conceptsUse both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocationLearn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy

Your code is a testament to your skills as a developer. No matter what language you use, code should be clean, elegant, and uncluttered. By using test-driven development (TDD), you'll write code that's easy to understand, retains its elegance, and works for months, even years, to come. With this indispensable guide, you'll learn how to use TDD with three different languages: Go, JavaScript, and Python.Author Saleem Siddiqui shows you how to tackle domain complexity using a unit test-driven approach. TDD partitions requirements into small, implementable features, enabling you to solve problems irrespective of the languages and frameworks you use. With Learning Test-Driven Development at your side, you'll learn how to incorporate TDD into your regular coding practice.This book helps you:Use TDD's divide-and-conquer approach to tame domain complexityUnderstand how TDD works across languages, testing frameworks, and domain conceptsLearn how TDD enables continuous integrationSupport refactoring and redesign with TDDLearn how to write a simple and effective unit test harness in JavaScriptSet up a continuous integration environment with the unit tests produced during TDDWrite clean, uncluttered code using TDD in Go, JavaScript, and Python

Ready to build cloud native applications? Get a hands-on introduction to daily life as a developer crafting code on OpenShift, the open source container application platform from Red Hat. Creating and packaging your apps for deployment on modern distributed systems can be daunting. Too often, adding infrastructure value can complicate development. With this practical guide, you'll learn how to build, deploy, and manage a multitiered application on OpenShift.Authors Joshua Wood and Brian Tannous, principal developer advocates at Red Hat, demonstrate how OpenShift speeds application development. With the Kubernetes container orchestrator at its core, OpenShift simplifies and automates the way you build, ship, and run code. You'll learn how to use OpenShift and the Quarkus Java framework to develop and deploy apps using proven enterprise technologies and practices that you can apply to code in any language.Learn the development cycles for building and deploying on OpenShift, and the tools that drive themUse OpenShift to build, deploy, and manage the ongoing lifecycle of an n-tier applicationCreate a continuous integration and deployment pipeline to build and deploy application source code on OpenShiftAutomate scaling decisions with metrics and trigger lifecycle events with webhooks

Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware

Whether you're searching for new or additional opportunities, information security can be vast and overwhelming. In this practical guide, author Christina Morillo introduces technical knowledge from a diverse range of experts in the infosec field. Through 97 concise and useful tips, you'll learn how to expand your skills and solve common issues by working through everyday security problems.You'll also receive valuable guidance from professionals on how to navigate your career within this industry. How do you get buy-in from the C-suite for your security program? How do you establish an incident and disaster response plan? This practical book takes you through actionable advice on a wide variety of infosec topics, including thought-provoking questions that drive the direction of the field.Continuously Learn to Protect Tomorrow's Technology - Alyssa ColumbusFight in Cyber Like the Military Fights in the Physical - Andrew HarrisKeep People at the Center of Your Work - Camille StewartInfosec Professionals Need to Know Operational Resilience - Ann JohnsonTaking Control of Your Own Journey - Antoine MiddletonSecurity, Privacy, and Messy Data Webs: Taking Back Control in Third-Party Environments - Ben BrookEvery Information Security Problem Boils Down to One Thing - Ben SmithFocus on the WHAT and the Why First, Not the Tool - Christina Morillo

Observability is critical for building, changing, and understanding the software that powers complex modern systems. Teams that adopt observability are much better equipped to ship code swiftly and confidently, identify outliers and aberrant behaviors, and understand the experience of each and every user. This practical book explains the value of observable systems and shows you how to practice observability-driven development.Authors Charity Majors, Liz Fong-Jones, and George Miranda from Honeycomb explain what constitutes good observability, show you how to improve upon what you??re doing today, and provide practical dos and don'ts for migrating from legacy tooling, such as metrics monitoring and log management. You??ll also learn the impact observability has on organizational culture (and vice versa).You'll explore:How the concept of observability applies to managing software systemsThe value of practicing observability when delivering and managing complex cloud native applications and systemsThe impact observability has across the entire software development lifecycleHow and why different functional teams use observability with service-level objectives (SLOs)How to instrument your code to help future engineers understand the code you wrote todayHow to produce quality code for context-aware system debugging and maintenanceHow data-rich analytics can help you debug elusive issues quickly

Over the past two decades, the booming ecommerce and fintech industries have become a breeding ground for fraud. Organizations that conduct business online are constantly engaged in a cat-and-mouse game with these invaders. In this practical book, Gilit Saporta and Shoshana Maraney draw on their fraud-fighting experience to provide best practices, methodologies, and tools to help you detect and prevent fraud and other malicious activities.Data scientists, data analysts, and fraud analysts will learn how to identify and quickly respond to attacks. You'll get a comprehensive view of typical incursions as well as recommended detection methods. Online fraud is constantly evolving. This book helps experienced researchers safely guide and protect their organizations in this ever-changing fraud landscape.With this book, you will:Examine current fraud attacks and learn how to mitigate themFind the right balance between preventing fraud and providing a smooth customer experienceShare insights across multiple business areas, including ecommerce, banking, cryptocurrency, anti-money laundering, and ad techEvaluate potential risks for a new vertical, market, or productTrain and mentor teams by boosting collaboration and kickstarting brainstorming sessionsGet a framework of fraud methods, fraud-fighting analytics, and data science methodologies

With the rise of DevOps, low-cost cloud computing, and container technologies, the way Java developers approach development today has changed dramatically. This practical guide helps you take advantage of microservices, serverless, and cloud native technologies using the latest DevOps techniques to simplify your build process and create hyperproductive teams.Stephen Chin, Melissa McKay, Ixchel Ruiz, and Baruch Sadogursky from JFrog help you evaluate an array of options. The list includes source control with Git, build declaration with Maven and Gradle, CI/CD with CircleCI, package management with Artifactory, containerization with Docker and Kubernetes, and much more. Whether you're building applications with Jakarta EE, Spring Boot, Dropwizard, MicroProfile, Micronaut, or Quarkus, this comprehensive guide has you covered.Explore software lifecycle best practicesUse DevSecOps methodologies to facilitate software development and deliveryUnderstand the business value of DevSecOps best practicesManage and secure software dependenciesDevelop and deploy applications using containers and cloud native technologiesManage and administrate source control repositories and development processesUse automation to set up and administer build pipelinesIdentify common deployment patterns and antipatternsMaintain and monitor software after deployment

Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark.In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script.With this book, you will:Learn how to select Spark transformations for optimized solutionsExplore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions()Understand data partitioning for optimized queriesBuild and apply a model using PySpark design patternsApply motif-finding algorithms to graph dataAnalyze graph data by using the GraphFrames APIApply PySpark algorithms to clinical and genomics dataLearn how to use and apply feature engineering in ML algorithmsUnderstand and use practical and pragmatic data design patterns