I Heart Logs


Book Description

Why a book about logs? That’s easy: the humble log is an abstraction that lies at the heart of many systems, from NoSQL databases to cryptocurrencies. Even though most engineers don’t think much about them, this short book shows you why logs are worthy of your attention. Based on his popular blog posts, LinkedIn principal engineer Jay Kreps shows you how logs work in distributed systems, and then delivers practical applications of these concepts in a variety of common uses—data integration, enterprise architecture, real-time stream processing, data system design, and abstract computing models. Go ahead and take the plunge with logs; you’re going love them. Learn how logs are used for programmatic access in databases and distributed systems Discover solutions to the huge data integration problem when more data of more varieties meet more systems Understand why logs are at the heart of real-time stream processing Learn the role of a log in the internals of online data systems Explore how Jay Kreps applies these ideas to his own work on data infrastructure systems at LinkedIn




Managing Data in Motion


Book Description

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. - Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types - Explains, in non-technical terms, the architecture and components required to perform data integration - Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"




Flow Architectures


Book Description

Software development today is embracing events and streaming data, which optimizes not only how technology interacts but also how businesses integrate with one another to meet customer needs. This phenomenon, called flow, consists of patterns and standards that determine which activity and related data is communicated between parties over the internet. This book explores critical implications of that evolution: What happens when events and data streams help you discover new activity sources to enhance existing businesses or drive new markets? What technologies and architectural patterns can position your company for opportunities enabled by flow? James Urquhart, global field CTO at VMware, guides enterprise architects, software developers, and product managers through the process. Learn the benefits of flow dynamics when businesses, governments, and other institutions integrate via events and data streams Understand the value chain for flow integration through Wardley mapping visualization and promise theory modeling Walk through basic concepts behind today's event-driven systems marketplace Learn how today's integration patterns will influence the real-time events flow in the future Explore why companies should architect and build software today to take advantage of flow in coming years




A Complete Guide to Wireless Sensor Networks


Book Description

This book provides comprehensive coverage of the major aspects in designing, implementing, and deploying wireless sensor networks by discussing present research on WSNs and their applications in various disciplines. It familiarizes readers with the current state of WSNs and how such networks can be improved to achieve effectiveness and efficiency. It starts with a detailed introduction of wireless sensor networks and their applications and proceeds with layered architecture of WSNs. It also addresses prominent issues such as mobility, heterogeneity, fault-tolerance, intermittent connectivity, and cross layer optimization along with a number of existing solutions to stimulate future research.




Spark: The Definitive Guide


Book Description

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. Youâ??ll explore the basic operations and common functions of Sparkâ??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, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??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, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation




Lean Integration


Book Description

Use Lean Techniques to Integrate Enterprise Systems Faster, with Far Less Cost and Risk By some estimates, 40 percent of IT budgets are devoted to integration. However, most organizations still attack integration on a project-by-project basis, causing unnecessary expense, waste, risk, and delay. They struggle with integration “hairballs”: complex point-to-point information exchanges that are expensive to maintain, difficult to change, and unpredictable in operation. The solution is Lean Integration. This book demonstrates how to use proven “lean” techniques to take control over the entire integration process. John Schmidt and David Lyle show how to establish “integration factories” that leverage the powerful benefits of repeatability and continuous improvement across every integration project you undertake. Drawing on their immense experience, Schmidt and Lyle bring together best practices; solid management principles; and specific, measurable actions for streamlining integration development and maintenance. Whether you’re an IT manager, project leader, architect, analyst, or developer, this book will help you systematically improve the way you integrate—adding value that is both substantial and sustainable. Coverage includes Treating integration as a business strategy and implementing management disciplines that systematically address its people, process, policy, and technology dimensions Providing maximum business flexibility and supporting rapid change without compromising stability, quality, control, or efficiency Applying improvements incrementally without “Boiling the Ocean” Automating processes so you can deliver IT solutions faster–while avoiding the pitfalls of automation Building in both data and integration quality up front, rather than inspecting quality in later More than a dozen in-depth case studies that show how real organizations are applying Lean Integration practices and the lessons they’ve learned Visit integrationfactory.com for additional resources, including more case studies, best practices, templates, software demos, and reference links, plus a direct connection to lean integration practitioners worldwide.




Stream Processing with Apache Spark


Book Description

Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams




Introduction to Windows Server 2019


Book Description

The Windows Server 2019 operating system is an improvement from its predecessor, Windows Server 2016. It offers various features that cater to the modern needs of businesses. One of the most significant changes in the server interface is its traditional Windows desktop that has been replaced with the Windows Admin Center. This change makes it more organized and faster to access critical features. Windows Server 2019 also features a new Storage Migration Service, which enables smooth transfers of data from previous Windows Server versions to the latest releases. The new server operating system offers a range of enhancements for security purposes, such as the Shielded Virtual Machines, powered by virtual TPMs and Advanced Threat Protection. Such features make it increasingly challenging for hackers to penetrate the system. Other critical enhancements include network performance improvements, PowerShell features, and Quick Create options. Overall, Windows Server 2019 provides businesses with various tools to meet the evolving needs for seamless integration, security, performance enhancements, flexibility, and accessibility. In conclusion, Windows Server 2019 is a robust and scalable operating system designed to cater to the needs of the current business landscape. From the insights in this introduction, it is evident that the enhanced features provided by Windows Server 2019 can improve the management and deployment of critical applications. It is an ideal upgrade for businesses looking to modernize their IT infrastructure and maintain a secure, productive, and efficient work environment.




Kafka: The Definitive Guide


Book Description

Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems