Revolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. Data Mesh in Action teaches you to establish a data mesh in organizations of any size. The book avoids a dogmatic one-size-fits-all approach and utilizes flexible "sliders" to adjust a data mesh to your company's specific needs. You'll learn processes and facilitative leadership techniques that will help change the way your colleagues think about data. Data Mesh in Action reveals how this groundbreaking architecture looks for both small startups and large enterprises. You'll see a data mesh in action as you explore both an extended case study and multiple real-world examples. As you go, you'll be expertly guided through discussions around Socio-Technical Architecture and Domain- Driven Design with the goal of building a sleek data-as-a-product system. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Revolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. In Data Mesh in Action you will learn how to: Implement a data mesh in your organization Turn data into a data product Move from your current data architecture to a data mesh Identify data domains, and decompose an organization into smaller, manageable domains Set up the central governance and local governance levels over data Balance responsibilities between the two levels of governance Establish a platform that allows efficient connection of distributed data products and automated governance Data Mesh in Action reveals how this groundbreaking architecture looks for both small startups and large enterprises. You won’t need any new technology—this book shows you how to start implementing a data mesh with flexible processes and organizational change. You’ll explore both an extended case study and multiple real-world examples. As you go, you’ll be expertly guided through discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-product system. Plus, dozens of workshop techniques for both in-person and remote meetings help you onboard colleagues and drive a successful transition. About the technology Business increasingly relies on efficiently storing and accessing large volumes of data. The data mesh is a new way to decentralize data management that radically improves security and discoverability. A well-designed data mesh simplifies self-service data consumption and reduces the bottlenecks created by monolithic data architectures. About the book Data Mesh in Action teaches you pragmatic ways to decentralize your data and organize it into an effective data mesh. You’ll start by building a minimum viable data product, which you’ll expand into a self-service data platform, chapter-by-chapter. You’ll love the book’s unique “sliders” that adjust the mesh to meet your specific needs. You’ll also learn processes and leadership techniques that will change the way you and your colleagues think about data. What's inside Decompose an organization into manageable domains Turn data into a data product Set up central and local governance levels Build a fit-for-purpose data platform Improve management, initiation, and support techniques About the reader For data professionals. Requires no specific programming stack or data platform. About the author Jacek Majchrzak is a hands-on lead data architect. Dr. Sven Balnojan manages data products and teams. Dr. Marian Siwiak is a data scientist and a management consultant for IT, scientific, and technical projects. Table of Contents PART 1 FOUNDATIONS 1 The what and why of the data mesh 2 Is a data mesh right for you? 3 Kickstart your data mesh MVP in a month PART 2 THE FOUR PRINCIPLES IN PRACTICE 4 Domain ownership 5 Data as a product 6 Federated computational governance 7 The self-serve data platform PART 3 INFRASTRUCTURE AND TECHNICAL ARCHITECTURE 8 Comparing self-serve data platforms 9 Solution architecture design

Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.

Solve difficult service-to-service communication challenges around security, observability, routing, and resilience with an Istio-based service mesh. Istio allows you to define these traffic policies as configuration and enforce them consistently without needing any service-code changes. In Istio in Action you will learn: Why and when to use a service mesh Envoy's role in Istio's service mesh Allowing "North-South" traffic into a mesh Fine-grained traffic routing Make your services robust to network failures Gain observability over your system with telemetry "golden signals" How Istio makes your services secure by default Integrate cloud-native applications with legacy workloads such as in VMs Reduce the operational complexity of your microservices with an Istio-powered service mesh! Istio in Action shows you how to implement this powerful new architecture and move your application-networking concerns to a dedicated infrastructure layer. Non-functional concerns stay separate from your application, so your code is easier to understand, maintain, and adapt regardless of programming language. In this practical guide, you'll go hands-on with the full-featured Istio service mesh to manage microservices communication. Helpful diagrams, example configuration, and examples make it easy to understand how to control routing, secure container applications, and monitor network traffic. Foreword by Eric Brewer. About the technology Offload complex microservice communication layer challenges to Istio! The industry-standard Istio service mesh radically simplifies security, routing, observability, and other service-to-service communication challenges. With Istio, you use a straightforward declarative configuration style to establish application-level network policies. By separating communication from business logic, your services are easier to write, maintain, and modify. About the book Istio in Action teaches you how to implement an Istio-based service mesh that can handle complex routing scenarios, traffic encryption, authorization, and other common network-related tasks. You'll start by defining a basic service mesh and exploring the data plane with Istio’s service proxy, Envoy. Then, you'll dive into core topics like traffic routing and visualization and service-to-service authentication, as you expand your service mesh to workloads on multiple clusters and legacy VMs. What's inside Comprehensive coverage of Istio resources Practical examples to showcase service mesh capabilities Implementation of multi-cluster service meshes How to extend Istio with WebAssembly Traffic routing and observability VM integration into the mesh About the reader For developers, architects, and operations engineers. About the author Christian Posta is a well-known architect, speaker, and contributor. Rinor Maloku is an engineer at Solo.io working on application networking solutions. ToC PART 1 UNDERSTANDING ISTIO 1 Introducing the Istio service mesh 2 First steps with Istio 3 Istio's data plane: The Envoy proxy PART 2 SECURING, OBSERVING, AND CONTROLLING YOUR SERVICE’S NETWORK TRAFFIC 4 Istio gateways: Getting traffic into a cluster 5 Traffic control: Fine-grained traffic routing 6 Resilience: Solving application networking challenges 7 Observability: Understanding the behavior of your services 8 Observability: Visualizing network behavior with Grafana, Jaeger, and Kiali 9 Securing microservice communication PART 3 ISTIO DAY-2 OPERATIONS 10 Troubleshooting the data plane 11 Performance-tuning the control plane PART 4 ISTIO IN YOUR ORGANIZATION 12 Scaling Istio in your organization 13 Incorporating virtual machine workloads into the mesh 14 Extending Istio on the request path

Summary The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you’ll learn to take advantage of Spark’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark’s powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Foreword by Rob Thomas. About the technology Analyzing enterprise data starts by reading, filtering, and merging files and streams from many sources. The Spark data processing engine handles this varied volume like a champ, delivering speeds 100 times faster than Hadoop systems. Thanks to SQL support, an intuitive interface, and a straightforward multilanguage API, you can use Spark without learning a complex new ecosystem. About the book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. In this entirely new book, you’ll learn from interesting Java-based examples, including a complete data pipeline for processing NASA satellite data. And you’ll discover Java, Python, and Scala code samples hosted on GitHub that you can explore and adapt, plus appendixes that give you a cheat sheet for installing tools and understanding Spark-specific terms. What's inside Writing Spark applications in Java Spark application architecture Ingestion through files, databases, streaming, and Elasticsearch Querying distributed datasets with Spark SQL About the reader This book does not assume previous experience with Spark, Scala, or Hadoop. About the author Jean-Georges Perrin is an experienced data and software architect. He is France’s first IBM Champion and has been honored for 12 consecutive years. Table of Contents PART 1 - THE THEORY CRIPPLED BY AWESOME EXAMPLES 1 So, what is Spark, anyway? 2 Architecture and flow 3 The majestic role of the dataframe 4 Fundamentally lazy 5 Building a simple app for deployment 6 Deploying your simple app PART 2 - INGESTION 7 Ingestion from files 8 Ingestion from databases 9 Advanced ingestion: finding data sources and building your own 10 Ingestion through structured streaming PART 3 - TRANSFORMING YOUR DATA 11 Working with SQL 12 Transforming your data 13 Transforming entire documents 14 Extending transformations with user-defined functions 15 Aggregating your data PART 4 - GOING FURTHER 16 Cache and checkpoint: Enhancing Spark’s performances 17 Exporting data and building full data pipelines 18 Exploring deployment

Propose a new scalable data architecture paradigm, Data Lakehouse, that addresses the limitations of current data architecture patterns Key FeaturesUnderstand how data is ingested, stored, served, governed, and secured for enabling data analyticsExplore a practical way to implement Data Lakehouse using cloud computing platforms like AzureCombine multiple architectural patterns based on an organization's needs and maturity levelBook Description The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success. The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application. By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner. What you will learnUnderstand the evolution of the Data Architecture patterns for analyticsBecome well versed in the Data Lakehouse pattern and how it enables data analyticsFocus on methods to ingest, process, store, and govern data in a Data Lakehouse architectureLearn techniques to serve data and perform analytics in a Data Lakehouse architectureCover methods to secure the data in a Data Lakehouse architectureImplement Data Lakehouse in a cloud computing platform such as AzureCombine Data Lakehouse in a macro-architecture pattern such as Data MeshWho this book is for This book is for data architects, big data engineers, data strategists and practitioners, data stewards, and cloud computing practitioners looking to become well-versed with modern data architecture patterns to enable large-scale analytics. Basic knowledge of data architecture and familiarity with data warehousing concepts are required.

”A complete guide to the challenges and solutions in securing microservices architectures.” —Massimo Siani, FinDynamic Key Features Secure microservices infrastructure and code Monitoring, access control, and microservice-to-microservice communications Deploy securely using Kubernetes, Docker, and the Istio service mesh. Hands-on examples and exercises using Java and Spring Boot Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Microservices Security in Action teaches you how to address microservices-specific security challenges throughout the system. This practical guide includes plentiful hands-on exercises using industry-leading open-source tools and examples using Java and Spring Boot. About The Book Design and implement security into your microservices from the start. Microservices Security in Action teaches you to assess and address security challenges at every level of a Microservices application, from APIs to infrastructure. You’ll find effective solutions to common security problems, including throttling and monitoring, access control at the API gateway, and microservice-to-microservice communication. Detailed Java code samples, exercises, and real-world business use cases ensure you can put what you’ve learned into action immediately. What You Will Learn Microservice security concepts Edge services with an API gateway Deployments with Docker, Kubernetes, and Istio Security testing at the code level Communications with HTTP, gRPC, and Kafka This Book Is Written For For experienced microservices developers with intermediate Java skills. About The Author Prabath Siriwardena is the vice president of security architecture at WSO2. Nuwan Dias is the director of API architecture at WSO2. They have designed secure systems for many Fortune 500 companies. Table of Contents PART 1 OVERVIEW 1 Microservices security landscape 2 First steps in securing microservices PART 2 EDGE SECURITY 3 Securing north/south traffic with an API gateway 4 Accessing a secured microservice via a single-page application 5 Engaging throttling, monitoring, and access control PART 3 SERVICE-TO-SERVICE COMMUNICATIONS 6 Securing east/west traffic with certificates 7 Securing east/west traffic with JWT 8 Securing east/west traffic over gRPC 9 Securing reactive microservices PART 4 SECURE DEPLOYMENT 10 Conquering container security with Docker 11 Securing microservices on Kubernetes 12 Securing microservices with Istio service mesh PART 5 SECURE DEVELOPMENT 13 Secure coding practices and automation

This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment. The book is divided into three parts: Part I provides an introduction to the topic from fundamental principles to key success factors, and an overview of operational use cases. As a holistic description of process mining in a business environment, this part is particularly useful for readers not yet familiar with the topic. Part II presents detailed use cases written by contributors from a variety of functions and industries. Lastly, Part III provides a brief overview of the future of process mining, both from academic and operational perspectives. Based on a solid academic foundation, process mining has received increasing interest from operational businesses, with many companies already reaping the benefits. As the first book to present an overview of successful industrial applications, it is of particular interest to professionals who want to learn more about the possibilities and opportunities this new technology offers. It is also a valuable resource for researchers looking for empirical results when considering requirements for enhancements and further developments.

On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data. This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow. Understand the relationship between data, business, and design Get a firm grounding in data, data types, and components of A/B testing Use an experimentation framework to define opportunities, formulate hypotheses, and test different options Create hypotheses that connect to key metrics and business goals Design proposed solutions for hypotheses that are most promising Interpret the results of an A/B test and determine your next move

Summary Kafka Streams in Action teaches you everything you need to know to implement stream processing on data flowing into your Kafka platform, allowing you to focus on getting more from your data without sacrificing time or effort. Foreword by Neha Narkhede, Cocreator of Apache Kafka Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Not all stream-based applications require a dedicated processing cluster. The lightweight Kafka Streams library provides exactly the power and simplicity you need for message handling in microservices and real-time event processing. With the Kafka Streams API, you filter and transform data streams with just Kafka and your application. About the Book Kafka Streams in Action teaches you to implement stream processing within the Kafka platform. In this easy-to-follow book, you'll explore real-world examples to collect, transform, and aggregate data, work with multiple processors, and handle real-time events. You'll even dive into streaming SQL with KSQL! Practical to the very end, it finishes with testing and operational aspects, such as monitoring and debugging. What's inside Using the KStreams API Filtering, transforming, and splitting data Working with the Processor API Integrating with external systems About the Reader Assumes some experience with distributed systems. No knowledge of Kafka or streaming applications required. About the Author Bill Bejeck is a Kafka Streams contributor and Confluent engineer with over 15 years of software development experience. Table of Contents PART 1 - GETTING STARTED WITH KAFKA STREAMS Welcome to Kafka Streams Kafka quicklyPART 2 - KAFKA STREAMS DEVELOPMENT Developing Kafka Streams Streams and state The KTable API The Processor APIPART 3 - ADMINISTERING KAFKA STREAMS Monitoring and performance Testing a Kafka Streams applicationPART 4 - ADVANCED CONCEPTS WITH KAFKA STREAMS Advanced applications with Kafka StreamsAPPENDIXES Appendix A - Additional configuration information Appendix B - Exactly once semantics