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If you use Linux in development or operations and need a structured approach to help you dive deeper, this book is for you. Author Michael Hausenblas also provides tips and tricks for improving your workflow with this open source operating system. Whether you're a developer, software architect, or site reliability engineer, this hands-on guide focuses on ways to use Linux for your everyday needs, from development to office-related tasks.Along the way, you'll gain hands-on experience with modern Linux terminals and shells, and learn how to manage your workloads. You'll understand how to run Linux applications by using containers, systemd, modern filesystems, and immutable distros such as Flatcar and Bottlerocket.Use Linux as a modern work environment, rather than just from an admin perspectiveLearn critical components such as the Linux kernel, terminal multiplexer, human-friendly shells, and portable shell scriptingBecome familiar with access control, from file permissions to capabilities, and understand the role of filesystems as a fundamental building blockLearn about application dependency management and containersGain hands-on experience with the Linux networking stack and tooling, including DNSApply modern operating system observability to manage your workloadsBecome familiar with interprocess communication, virtual machines, and selected security topics

Testing is a critical discipline for any organization looking to deliver high-quality software. This practical book provides software developers and QA engineers with a comprehensive one-stop guide to testing skills in 10 different categories. You'll learn appropriate strategies, concepts, and practical implementation knowledge you can apply from both a development and testing perspective for web and mobile applications.Author Gayathri Mohan offers examples of more than 40 tools you can use immediately. You'll acquire the skills to conduct exploratory testing, test automation, cross-functional testing, data testing, mobile testing, and visual testing, as well as tests for performance, security, and accessibility. You'll learn to integrate them in continuous integration pipelines to gain faster feedback. Once you dive into this guide, you'll be able to tackle challenging development workflows with a focus on quality.With this book, you will:Learn how to employ various testing types to yield maximum quality in your projectsExplore new testing methods by following the book's strategies and conceptsLearn how to apply these tools at work by following detailed examplesImprove your skills and job prospects by gaining a broad exposure to testing best practices

Ready to build quantum computing applications using Q# and the Microsoft Quantum Development Kit? This is the book for you. Q# is a domain-specific language for expressing quantum algorithms that combines familiar "e;classical"e; language constructs with quantum-specific ones. Ideal for any developer familiar with (or willing to learn) the basics of quantum computing and looking to get started with quantum programming, this pocket guide quickly helps you find syntax and usage information for unfamiliar aspects of Q#.You'll explore the quantum software development lifecycle from implementing the program to running it on quantum simulators to testing and debugging it. You'll learn to use the tools provided by Microsoft's Quantum Development Kit for each step of the process.You'll explore:Q# language details, including data types, statements, and operatorsGuidelines for organizing Q# code and invoking it from different environmentsInformation on simulators and tools in the Microsoft Quantum Development KitAdvice on testing and debugging tools and techniques for quantum programs

With the rise of the cloud, every aspect of IT has been shaken to its core. The fundamentals for building systems are changing, and although many of the principles that underpin security still ring true, their implementation has become unrecognizable. This practical book provides recipes for AWS, Azure, and GCP to help you enhance the security of your own cloud native systems.Based on his hard-earned experience working with some of the world's biggest enterprises and rapidly iterating startups, consultant Josh Armitage covers the trade-offs that security professionals, developers, and infrastructure gurus need to make when working with different cloud providers. Each recipe discusses these inherent compromises, as well as where clouds have similarities and where they're fundamentally different.Learn how the cloud provides security superior to what was achievable in an on-premises worldUnderstand the principles and mental models that enable you to make optimal trade-offs as part of your solutionLearn how to implement existing solutions that are robust and secure, and devise design solutions to new and interesting problemsDeal with security challenges and solutions both horizontally and vertically within your business

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world.Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI.This book examines:Differences between and limitations of automated, autonomous, and human decision-makingUnique advantages of autonomous AI for real-time decision-making, with use casesHow to design an autonomous AI from modular components and document your designs

Making Simple Robots is based on the idea that anybody can build a robot! That includes kids, educators, parents, and anyone who didn't make it to engineering school. If you can cut, fold, and tape a piece of paper to make a tube or a box, you can build a no-tech robotic part. In fact, many of the models in this book are based upon real-life prototypes -- working models created in research labs and companies. What's more, if you can use the apps on your smartphone, you can quickly learn to tell robots what to do using free, online, beginner-level software like MIT's Scratch and Microsoft MakeCode. The projects in this book which teach you about electric circuits by making jumping origami frogs with eyes that light up when you get them ready to hop. You'll practice designing all-terrain robot wheel-legs with free, online Tinkercad software, and you'll create files ready for 3D printing. You'll also learn to sew -- and code -- a cyborg rag doll with a blinking electronic "eye." Each project includes step-by-step directions and clear illustrations and photographs. Along the way, you'll learn about the real research behind the DIY version, find shortcuts for making projects easier when needed, and get suggestions for adding to the challenge as your skill set grows.

Simulation and synthesis are core parts of the future of AI and machine learning. Consider: programmers, data scientists, and machine learning engineers can create the brain of a self-driving car without the car. Rather than use information from the real world, you can synthesize artificial data using simulations to train traditional machine learning models.Thats just the beginning.With this practical book, youll explore the possibilities of simulation- and synthesis-based machine learning and AI, concentrating on deep reinforcement learning and imitation learning techniques. AI and ML are increasingly data driven, and simulations are a powerful, engaging way to unlock their full potential.You'll learn how to:Design an approach for solving ML and AI problems using simulations with the Unity engineUse a game engine to synthesize images for use as training dataCreate simulation environments designed for training deep reinforcement learning and imitation learning modelsUse and apply efficient general-purpose algorithms for simulation-based ML, such as proximal policy optimizationTrain a variety of ML models using different approachesEnable ML tools to work with industry-standard game development tools, using PyTorch, and the Unity ML-Agents and Perception Toolkits

Kubernetes is the operating system of the cloud-native world, providing a reliable and scalable platform for running containerized workloads. This book shows developers and operations staff how to apply industry-standard DevOps practices to Kubernetes in a cloud-native context.

Even as spending on digital transformation continues to skyrocket, mainframes nevertheless have major advantages for global enterprises. These systems still process huge amounts of information and allow for highly secure processing. In this practical book, author Tom Taulli shows software developers how to pursue a hybrid approach by integrating traditional mainframes and applications with modern digital systems.By the end of the book, you'll have a solid understanding of the mainframe architecture and ecosystem, including core concepts and technologies such as COBOL, JCL, DB2, VSAM, and CICS. You'll learn how to blend in newer technologies such as the cloud, AI and machine learning, and the use of microservices. This handbook is indispensable for enterprises looking to thrive in the new digital world.Learn strategies and approaches for mainframe DevOpsUpdate and maintain existing mainframe code, and analyze and resolve common errorsApply modern approaches to the mainframe, including microservices, APIs, cloud, and AI and machine learningWork with datasets and databases and put together effective reportsUnderstand how to work with modern cloud systems, like AWS, for pursuing data migration

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

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

The amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming.Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection, to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing.If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis.Familiarize yourself with Spark's programming model and ecosystemLearn general approaches in data scienceExamine complete implementations that analyze large public datasetsDiscover which machine learning tools make sense for particular problemsExplore code that can be adapted to many uses

Move into iOS development by getting a firm grasp of its fundamentals, including the Xcode 13 IDE, Cocoa Touch, and Swift 5.5, the latest version of Apple's acclaimed programming language. With this thoroughly updated guide, you'll learn the Swift language, understand Apple's Xcode development tools, and discover the Cocoa framework.

You'll find several books on basic or advanced MySQL performance, but nothing in between. That's because explaining MySQL performance without addressing its complexity is difficult. This practical book bridges the gap by teaching software engineers mid-level MySQL knowledge beyond the fundamentals, but well shy of deep-level internals required by database administrators (DBAs).Daniel Nichter shows you how to apply the best practices and techniques that directly affect MySQL performance. You'll learn how to improve performance by analyzing query execution, indexing for common SQL clauses and table joins, optimizing data access, and understanding the most important MySQL metrics. You'll also discover how replication, transactions, row locking, and the cloud influenceMySQL performance.Understand why query response time is the North Star of MySQL performanceLearn query metrics in detail, including aggregation, reporting, and analysisSee how to index effectively for common SQL clauses and table joinsExplore the most important server metrics and what they reveal about performanceDive into transactions and row locking to gain deep, actionable insightAchieve remarkable MySQL performance at any scale

Get the lowdown on CockroachDB, the elastic SQL database built to handle the demands of today's data-driven world. With this practical guide, software developers, architects, and DevOps teams will discover the advantages of building on a distributed SQL database. You'll learn how to create applications that scale elastically and provide seamless delivery for end users while remaining exceptionally resilient and indestructible.Written from scratch for the cloud and architected to scale elastically to handle the demands of cloud native and open source, CockroachDB makes it easier to build and scale modern applications. If you're familiar with distributed systems, you'll quickly discover the benefits of strong data correctness and consistency guarantees as well as optimizations for delivering ultralow latencies to globally distributed end users.With this thorough guide, you'll learn how to:Plan and build applications for distributed infrastructure, including data modeling and schema designMigrate data into CockroachDBRead and write data and run ACID transactions across distributed infrastructureOptimize queries for performance across geographically distributed replicasPlan a CockroachDB deployment for resiliency across single-region and multiregion clustersSecure, monitor, and optimize your CockroachDB deployment

Zero to Genetic Engineering Hero is made to provide you with a first glimpse of the inner-workings of a cell. It further focuses on skill-building for genetic engineering and the Biology-as-a-Technology mindset (BAAT).

The cloud is becoming the de facto home for companies ranging from enterprises to startups. Moving to the cloud means moving your applications from monolith to microservices. But once you do, running and maintaining these services brings its own level of complexity. The answer? Modularity, deployability, observability, and self-healing capacity through cloud native development.With this practical book, Nishant Singh and Michael Kehoe show you how to build a true cloud native infrastructure using Microsoft Azure or another cloud computing solution by following guidelines from the Cloud Native Computing Foundation (CNCF). DevOps and site reliability engineers will learn how adapting applications to cloud native early in the design phase helps you fully utilize the elasticity and distributed nature of the cloud.This book helps you explore:Why go cloud native?How to use infrastructure as codeWhat it takes to containerize an applicationWhy and how Kubernetes is the "e;grand orchestrator"e;How to create a Kubernetes cluster on AzureHow observability complements monitoringHow to use service discovery and a service mesh to find new territoriesHow networking and policy management serve as gatekeepersHow distributed databases and storage work

The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations.Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data.Use Python 3.8+ to read, write, and transform data from a variety of sourcesUnderstand and use programming basics in Python to wrangle data at scaleOrganize, document, and structure your code using best practicesCollect data from structured data files, web pages, and APIsPerform basic statistical analyses to make meaning from datasetsVisualize and present data in clear and compelling ways

Documents various SQL commands according to ANSI standard, and details how those commands are implemented in Microsoft SQL Server 2008, Oracle 11g, and the MySQL 5.1 and PostgreSQL 8.3 open source database products. This book presents fundamental concepts that are necessary for understanding relational databases and SQL commands.

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

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

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

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

Get quick hands-on experience with Google Cloud. This cookbook provides a variety of self-contained recipes that show you how to use Google Cloud services for your enterprise application. Whether you're looking for practical ways to apply microservices, AI, analytics, security, or networking solutions, these recipes take you step-by-step through the process and provide discussions that explain how and why the recipes work.Ideal for system engineers and administrators, developers, network and database administrators, and data analysts, this cookbook helps you get started with Google Cloud regardless of your level of experience. Google veterans Rui Costa and Drew Hodun also cover advanced-level Google Cloud services for those who have appreciable experience with the platform.Learn how to get started with Google CloudUnderstand the depth of services Google Cloud providesGain hands-on experience using practical examples and labsExplore topics that include BigQuery, Cloud Run, and KubernetesBuild and run mobile and web applications on Google CloudExamine ways to build your cloud applications for scaleBuild a minimum viable product (MVP) app to use in productionLearn data platform and pipeline skills

With this unique hands-on guide, you'll learn valuable ways to use Git in many different situations. Raju Gandhi peels back the layers to reveal the simple yet powerful engine that powers Git, with activities that help you truly understand this crucial tool as you get it up and running.

This practical guide provides over 70 self-contained recipes to help you creatively solve common AWS challenges you'll encounter on your cloud journey. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook provides what you need to address foundational tasks and create high-level capabilities.Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described. From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further.Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you:Redact personal identifiable information (PII) from text using Amazon ComprehendAutomate password rotation for Amazon RDS databasesUse VPC Reachability Analyzer to verify and troubleshoot network pathsLock down Amazon Simple Storage Service (S3) bucketsAnalyze AWS Identity and Access Management policiesAutoscale a containerized service

Reactive systems and event-driven architecture are becoming indispensable to application design, and companies are taking note. Reactive systems ensure that applications are responsive, resilient, and elastic no matter what failures or errors may be occurring, while event-driven architecture offers a flexible and composable option for distributed systems. This practical book helps Java developers bring these approaches together using Quarkus 2.x, the Kubernetes-native Java framework.Clement Escoffier and Ken Finnigan show you how to take advantage of event-driven and reactive principles to build robust distributed systems, reducing latency and increasing throughput, particularly in microservices and serverless applications. You'll also get a foundation in Quarkus to help you create true Kubernetes-native applications for the cloud.Understand the fundamentals of reactive systems and event-driven architectureLearn how to use Quarkus to build reactive applicationsCombine Quarkus with Apache Kafka or AMQP to build reactive systemsDevelop microservices that utilize messages with Quarkus for use in event-driven architecturesLearn how to integrate external messaging systems, such as Apache Kafka, with QuarkusBuild applications with Quarkus using reactive systems and reactive programming concepts

Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models.Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will:Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningImprove market risk models (VaR and ES) using ML techniques and including liquidity dimensionDevelop a credit risk analysis using clustering and Bayesian approachesCapture different aspects of liquidity risk with a Gaussian mixture model and Copula modelUse machine learning models for fraud detectionPredict stock price crash and identify its determinants using machine learning models

Every enterprise application creates data, including log messages, metrics, user activity, and outgoing messages. Learning how to move these items is almost as important as the data itself. If you're an application architect, developer, or production engineer new to Apache Pulsar, this practical guide shows you how to use this open source event streaming platform to handle real-time data feeds.Jowanza Joseph, staff software engineer at Finicity, explains how to deploy production Pulsar clusters, write reliable event streaming applications, and build scalable real-time data pipelines with this platform. Through detailed examples, you'll learn Pulsar's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the load manager, and the storage layer.This book helps you:Understand how event streaming fits in the big data ecosystemExplore Pulsar producers, consumers, and readers for writing and reading eventsBuild scalable data pipelines by connecting Pulsar with external systemsSimplify event-streaming application building with Pulsar FunctionsManage Pulsar to perform monitoring, tuning, and maintenance tasksUse Pulsar's operational measurements to secure a production clusterProcess event streams using Flink and query event streams using Presto

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