Camel in Action, Second Edition is the most complete Camel book on the market. Written by core developers of Camel and the authors of the highly acclaimed first edition, this book distills their experience and practical insights so that you can tackle integration tasks like a pro. About the Technology Apache Camel is a Java framework that implements enterprise integration patterns (EIPs) and comes with over 200 adapters to third-party systems. A concise DSL lets you build integration logic into your app with just a few lines of Java or XML. By using Camel, you benefit from the testing and experience of a large and vibrant open source community. About the Book Camel in Action, Second Edition is the definitive guide to the Camel framework. It starts with core concepts like sending, receiving, routing, and transforming data. It then goes in depth on many topics such as how to develop, debug, test, deal with errors, secure, scale, cluster, deploy, and monitor your Camel applications. The book also discusses how to run Camel with microservices, reactive systems, containers, and in the cloud. What's Inside Coverage of all relevant EIPs Camel microservices with Spring Boot Camel on Docker and Kubernetes Error handling, testing, security, clustering, monitoring, and deployment Hundreds of examples in Java and XML About the Reader Readers should be familiar with Java. This book is accessible to beginners and invaluable to experts. About the Authors Claus Ibsen is a senior principal engineer working for Red Hat specializing in cloud and integration. He has worked on Apache Camel for the last nine years where he heads the project. Claus lives in Denmark. Jonathan Anstey is an engineering manager at Red Hat and a core Camel contributor. He lives in Newfoundland, Canada. Quotes I highly recommend this book to anyone with even a passing interest in Apache Camel. Do take Camel for a ride...and don't get the hump! - From the Foreword by James Strachan, Creator of Apache Camel Claus and Jon are great writers, relying on figures and diagrams where needed and presenting lots of code snippets and worked examples. - From the Foreword by Dr. Mark Little, Technical Director of JBoss The second edition of this all-time classic is an indispensable companion for your Apache Camel rides. - Gregor Zurowski, Apache Camel Committer The absolute best way to learn and use Camel - top to bottom, front to back, and all the way through. Camel is a fantastic tool - every Java coder should have a copy of this book. - Rick Wagner, Red Hat An excellent book and the definite reference for experienced engineers. - Yan Guo, EventBrite

Dive into the essential resource for mastering Apache Kafka with this cookbook of practical recipes. You'll explore the dynamic features of Kafka 1.0, integrate it with enterprise data solutions, and confidently manage messaging and streaming data in real-time. What this Book will help me do Effectively install and configure Apache Kafka in a professional environment. Implement Kafka producers and consumers to manage real-time data streams. Utilize Confluent platforms and Kafka streams for advanced data processing. Monitor Kafka clusters with tools like Graphite and Ganglia for optimal performance. Integrate Kafka seamlessly with tools such as Hadoop, Spark, and Elasticsearch. Author(s) None Estrada and None Zinoviev have extensive experience in enterprise data systems and have been dedicated contributors to the Apache Kafka ecosystem. Their combined expertise encompasses developing robust, real-time distributed systems and delivering insightful technical guidance. Through this book, they share their vast knowledge and practical solutions, tailored for both developers and administrators. Who is it for? This book is tailored for developers and administrators looking to enhance their expertise in Apache Kafka. Developers should be comfortable with Java or Scala to fully utilize examples, while administrators benefit from prior knowledge of Kafka operations. Ideal readers are those seeking actionable techniques to efficiently manage and integrate Kafka into their enterprise systems.

RabbitMQ in Depth is a practical guide to building and maintaining message-based applications. This book provides detailed coverage of RabbitMQ with an emphasis on why it works the way it does. You'll find examples and detailed explanations based in real-world systems ranging from simple networked services to complex distributed designs. You'll also find the insights you need to make core architectural choices and develop procedures for effective operational management. About the Technology At the heart of most modern distributed applications is a queue that buffers, prioritizes, and routes message traffic. RabbitMQ is a high-performance message broker based on the Advanced Message Queueing Protocol. It's battle tested, ultrafast, and powerful enough to handle anything you can throw at it. It requires a few simple setup steps, and you can instantly start using it to manage low-level service communication, application integration, and distributed system message routing. About the Book What's Inside AMQP, the Advanced Message Queueing Protocol Communicating via MQTT, Stomp, and HTTP Valuable troubleshooting techniques Database integration About the Reader Written for programmers with a basic understanding of messaging-oriented systems. About the Author Gavin M. Roy is an active, open source evangelist and advocate who has been working with internet and enterprise technologies since the mid-90s. Technical editor James Titcumb is a freelance developer, trainer, speaker, and active contributor to open source projects. Quotes An excellent resource for beginners and experts alike...shows how to integrate RabbitMQ into a successful enterprise application. - Ian Dallas, Hewlett-Packard The most comprehensive source for everything RabbitMQ. From terms to code to patterns, it's all here! - Andrew Meredith, Quantum Metric A cheat sheet for getting started and troubleshooting the migration process to RabbitMQ. - Nadia Noori, La Salle University Barcelona Filled with pragmatic advice and pearls of wisdom. - Milos Milivojevic, Mozzart Bet

This book provides a comprehensive guide to real-time data processing and analytics using modern frameworks like Apache Spark, Flink, Storm, and Kafka. Through practical examples and in-depth explanations, you will learn how to implement efficient, scalable, real-time processing pipelines. What this Book will help me do Understand real-time data processing essentials and the technology stack Learn integration of components like Apache Spark and Kafka Master the concepts of stream processing with detailed case studies Gain expertise in developing monitoring and alerting solutions for real-time systems Prepare to implement production-grade real-time data solutions Author(s) Shilpi Saxena and Saurabh Gupta, the authors, are experienced professionals in distributed systems and data engineering, focusing on practical applications of real-time computing. They bring their extensive industry experience to this book, helping readers understand the complexities of real-time data solutions in an approachable and hands-on manner. Who is it for? This book is ideal for software engineers and data engineers with a background in Java who seek to develop real-time data solutions. It is suitable for readers familiar with concepts of real-time data processing, and enhances knowledge in frameworks like Spark, Flink, Storm, and Kafka. Target audience includes learners building production data solutions and those designing distributed analytics engines.

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

Learn how to design and build efficient real-time streaming applications using Apache Kafka, a leading distributed streaming platform. This book provides comprehensive guidance on setting up Kafka clusters, developing producers and consumers, and integrating with frameworks like Spark, Storm, and Heron. By the end, you'll master the skills needed to create enterprise-grade data streaming solutions. What this Book will help me do Grasp the core concepts and components of Apache Kafka and its ecosystem. Develop robust Kafka producers and consumers to process real-time data streams. Design and implement streaming applications using Spark, Storm, and Heron. Plan Kafka deployments with a focus on scalability, capacity, and fault tolerance. Ensure secure data streaming with best practices for securing Apache Kafka. Author(s) The authors, None Singh and None Kumar, bring years of expertise in data engineering and distributed systems. Having worked extensively with streaming technologies like Apache Kafka, they aim to share their in-depth knowledge through practical examples and real-world scenarios. Their approach to teaching focuses on making complex concepts easily understandable. Who is it for? This book is ideal for software developers and data engineers who are eager to learn Apache Kafka for building streaming applications. Some experience with programming, particularly Java, will help readers get the most out of the material. If you are working on data-processing systems or looking to enhance your skills in real-time data handling, this book caters to your needs.

Mastering Apache Storm is your step-by-step guide to mastering real-time data streaming with this robust framework. You'll learn how to process big data efficiently and integrate Apache Storm with popular technologies like Kafka, HBase, and Redis to maximize its potential. This book walks you through from basic concepts to advanced implementations of Apache Storm in real-world scenarios. What this Book will help me do Understand the core features and operation of Apache Storm for real-time data streaming. Integrate Apache Storm with other Big Data frameworks like Kafka, HBase, Redis, and Hadoop. Effectively deploy and manage multi-node Apache Storm clusters in real-world environments. Monitor and analyze your data streams and system health effectively using built-in and external tools. Learn to implement fault-tolerant, scalable, and distributed stream processing applications in Apache Storm. Author(s) None Jain is an experienced software developer and technical instructor specializing in distributed systems and real-time data processing. With years of experience working with Apache Storm and related technologies, their teachings focus on practical, hands-on learning to equip readers with actionable skills. Who is it for? This book is ideal for Java developers aspiring to build expertise in real-time data streaming and distributed processing applications using Apache Storm. Beginners can start with the fundamentals provided, while those with prior knowledge can delve into intermediate and advanced implementations.

Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them. About the Book Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details. What's Inside The right way to collect real-time data Architecting a streaming pipeline Analyzing the data Which technologies to use and when About the Reader Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required. About the Author Andrew Psaltis is a software engineer focused on massively scalable real-time analytics. Quotes The definitive book if you want to master the architecture of an enterprise-grade streaming application. - Sergio Fernandez Gonzalez, Accenture A thorough explanation and examination of the different systems, strategies, and tools for streaming data implementations. - Kosmas Chatzimichalis, Mach 7x A well-structured way to learn about streaming data and how to put it into practice in modern real-time systems. - Giuliano Araujo Bertoti, FATEC This book is all you need to understand what streaming is all about! - Carlos Curotto, Globant

Messaging is one of the more poorly understood areas of IT; most developers and architects have only a passing familiarity with how broker-based messaging technologies work. This practical report not only helps you get up to speed on the essentials of messaging, but also compares two of today’s most popular messaging technologies—Apache ActiveMQ and Apache Kafka. Author and consultant Jakub Korab describes use cases and design choices that lead developers to very different approaches for developing message-based systems. You’ll come away with a high-level understanding of both ActiveMQ and Kafka, including how they should and should not be used, how they handle concerns such as throughput and high-availability, and what to look out for when considering other messaging technologies in future. Understand the types of problems that messaging systems address Explore three primary messaging patterns: point-to-point, publish-subscribe, and a hybrid of both Dive into ActiveMQ, a classic broker-centric design implemented through Java libraries that works for a broad range of messaging use cases Examine Kafka, a distributed system that can be scaled to provide massive performance and fault tolerance through replication Learn the mechanical complexities that message-based systems need to address, and some patterns you can apply to deal with those complexities

Dive into the world of MQTT, the preferred protocol for IoT and M2M communication. This book provides a comprehensive guide to understanding, implementing, and securing MQTT-based systems, enabling readers to create efficient and lightweight communication networks for their connected devices. What this Book will help me do Understand the underlying principles and protocol structure of MQTT. Securely configure and deploy an MQTT broker for communication. Develop Python, Java, and JavaScript-based MQTT client applications. Utilize MQTT for real-world IoT use cases such as sensor data interchange. Optimize MQTT usage for low-latency and lightweight communication scenarios. Author(s) Gastón C. Hillar is an experienced IoT developer and author with a deep understanding of IoT protocols and technologies. With years of practical experience in designing and deploying secure IoT systems, Gastón specializes in breaking down complex topics into digestible and actionable insights. Through his books, he aims to empower developers to effectively integrate IoT technologies into their work. Who is it for? The book is tailored for software developers and engineers who are looking to integrate MQTT into their IoT solutions. It's ideal for individuals with pre-existing knowledge in IoT concepts who want to deepen their understanding of MQTT. Readers seeking to secure, optimize, and utilize MQTT for communication and automation tasks will find it especially useful. It's a perfect fit for those working with Python, Java, and web technologies in IoT contexts.

Weathering the Storm explores the factors leading up to the recent global financial and economic crisis, how the crisis unfolded, and the response of European and national authorities. The book describes the rationale behind the measures undertaken to mitigate the consequences of the recession and to ensure that a similar situation does not happen again in the future. In the wake of the crisis, various major changes continue to significantly affect the life and social organization of Europeans. For instance, a new ESM with a size financially comparable to that of the IMF was created; similarly, the reforms in economic governance imply much more intrusive participation of European countries in each other's macroeconomic policies. Moreover, the organization, regulation, and supervision of the financial sector have been drastically revamped. The decisions taken by European and national authorities affect the daily lives of hundreds of millions of European citizens and countless more around the globe. An insightful read for anyone interested in understanding the topic and its effect on their lives, the book primarily addresses undergraduate students in their final year and graduate students in fields such as economics, finance, and political science. The main messages are explained through examples and charts.

Weathering the Storm explores the factors leading up to the recent global financial and economic crisis, how the crisis unfolded, and the response of European and national authorities. The book describes the rationale behind the measures undertaken to mitigate the consequences of the recession and to ensure that a similar situation does not happen again in the future. In the wake of the crisis, various major changes continue to significantly affect the life and social organization of Europeans. For instance, a new ESM with a size financially comparable to that of the IMF was created; similarly, the reforms in economic governance imply much more intrusive participation of European countries in each other's macroeconomic policies. Moreover, the organization, regulation, and supervision of the financial sector have been drastically revamped. The decisions taken by European and national authorities affect the daily lives of hundreds of millions of European citizens and countless more around the globe. An insightful read for anyone interested in understanding the topic and its effect on their lives, the book primarily addresses undergraduate students in their final year and graduate students in fields such as economics, finance, and political science. The main messages are explained through examples and charts.

There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do well—until now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities.

Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? In this report, author Dean Wampler examines the rise of streaming systems for handling time-sensitive problems—such as detecting fraudulent financial activity as it happens. You’ll explore the characteristics of fast data architectures, along with several open source tools for implementing them. Batch-mode processing isn’t going away, but exclusive use of these systems is now a competitive disadvantage. You’ll learn that, while fast data architectures are much harder to build, they represent the state of the art for dealing with mountains of data that require immediate attention. Learn step-by-step how a basic fast data architecture works Understand why event logs are the core abstraction for streaming architectures, while message queues are the core integration tool Use methods for analyzing infinite data sets, where you don’t have all the data and never will Take a tour of open source streaming engines, and discover which ones work best for different use cases Get recommendations for making real-world streaming systems responsive, resilient, elastic, and message driven Explore an example streaming application for the IoT: telemetry ingestion and anomaly detection for home automation systems

More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm. Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer. To illustrate the effectiveness of these technologies, this book also includes specific use cases. Ideal for developers and non-technical people alike, this book describes: Key elements in good design for streaming analytics, focusing on the essential characteristics of the messaging layer New messaging technologies, including Apache Kafka and MapR Streams, with links to sample code Technology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache Apex How stream-based architectures are helpful to support microservices Specific use cases such as fraud detection and geo-distributed data streams Ted Dunning is Chief Applications Architect at MapR Technologies, and active in the open source community. He currently serves as VP for Incubator at the Apache Foundation, as a champion and mentor for a large number of projects, and as committer and PMC member of the Apache ZooKeeper and Drill projects. Ted is on Twitter as @ted_dunning. Ellen Friedman, a committer for the Apache Drill and Apache Mahout projects, is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. With a PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics. Ellen is on Twitter as @Ellen_Friedman.

How can event streams help make your application more scalable, reliable, and maintainable? In this report, O’Reilly author Martin Kleppmann shows you how stream processing can make your data storage and processing systems more flexible and less complex. Structuring data as a stream of events isn’t new, but with the advent of open source projects such as Apache Kafka and Apache Samza, stream processing is finally coming of age. Using several case studies, Kleppmann explains how these projects can help you reorient your database architecture around streams and materialized views. The benefits of this approach include better data quality, faster queries through precomputed caches, and real-time user interfaces. Learn how to open up your data for richer analysis and make your applications more scalable and robust in the face of failures. Understand stream processing fundamentals and their similarities to event sourcing, CQRS, and complex event processing Learn how logs can make search indexes and caches easier to maintain Explore the integration of databases with event streams, using the new Bottled Water open source tool Turn your database architecture inside out by orienting it around streams and materialized views

This book delves into the techniques and tools essential for designing, processing, and analyzing complex datasets in real-time using advanced frameworks like Apache Spark, Storm, and Amazon Kinesis. By engaging with this thorough guide, you'll build proficiency in creating robust, efficient, and scalable real-time data processing architectures tailored to real-world scenarios. What this Book will help me do Learn the fundamentals of real-time data processing and how it differs from batch processing. Gain hands-on experience with Apache Storm for creating robust data-driven solutions. Develop real-world applications using Amazon Kinesis for cloud-based analytics. Perform complex data queries and transformations with Spark SQL and understand Spark RDDs. Master the Lambda Architecture to combine batch and real-time analytics effectively. Author(s) Shilpi Saxena is a renowned expert in big data technologies, holding extensive experience in real-time data analytics. With a career spanning years in the industry, Shilpi has provided innovative solutions for big data challenges in top-tier organizations. Her teaching approach emphasizes practical applicability, making her writings accessible and impactful for developers and architects alike. Who is it for? This book is for software professionals such as Big Data architects, developers, or programmers looking to enhance their skills in real-time big data analytics. If you are familiar with basic programming principles and seek to build solutions for processing large data streams in real-time environments, this book caters to your needs. It is also suitable for those seeking to familiarize themselves with using state-of-the-art tools like Spark SQL, Apache Storm, and Amazon Kinesis. Whether you're extending current expertise or transitioning into this field, this resource helps you achieve your objectives.

Mastering RabbitMQ provides a comprehensive guide to developing and scaling message-driven applications using RabbitMQ. From installation and configuration to advanced concepts like cluster management and high availability, this book equips you with the knowledge and practical skills to ensure robust and efficient messaging solutions. What this Book will help me do Effectively set up and configure RabbitMQ for scalable applications. Implement robust messaging solutions using RabbitMQ's administrative tools. Leverage clustering and high availability for fault-tolerant systems. Create custom RabbitMQ plugins using Erlang for extended capabilities. Monitor and secure RabbitMQ environments leveraging popular tools and practices. Author(s) Yusuf Aytas and the co-authors bring a wealth of technical knowledge and practical experience in messaging systems and RabbitMQ. With years of expertise in software engineering and hands-on implementations in enterprise environments, they provide insights that combine theory with real-world application. Who is it for? This book is ideal for developers and IT professionals with basic knowledge of RabbitMQ seeking to master advanced usage and best practices. It caters to those looking to design, develop, and maintain robust messaging systems efficiently. Perfect for those with a background in message queuing, it provides an in-depth understanding to take your expertise to the next level.

Learning RabbitMQ offers developers and system administrators a clear and practical guide to mastering RabbitMQ, the popular message-broker solution. By going through concrete scenarios and examples, this book equips you with the skills to configure, manage, and optimize RabbitMQ instances effectively. What this Book will help me do Understand and apply common messaging patterns using RabbitMQ. Set up and manage RabbitMQ clusters with high availability. Integrate RabbitMQ with popular tools like Spring, MuleESB, and Docker. Optimize RabbitMQ performance and ensure secure messaging. Troubleshoot and extend RabbitMQ for different use cases. Author(s) None Toshev, the author of Learning RabbitMQ, is an expert in middleware and distributed systems, with extensive hands-on experience working with message brokers. Toshev's practical approach and clear explanations make complex topics easy to understand, helping readers effectively apply best practices when using RabbitMQ. Who is it for? This book is for developers and system administrators who aim to incorporate RabbitMQ as part of their applications. Beginners with a basic understanding of messaging will find it foundational, while experienced users will appreciate the advanced insights on integration, performance tuning, and troubleshooting.

Gain a competitive edge with IBM Streams Turn data-in-motion into solid business opportunities with IBM Streams and let Streaming Analytics with IBM Streams show you how. This comprehensive guide starts out with a brief overview of different technologies used for big data processing and explanations on how data-in-motion can be utilized for business advantages. You will learn how to apply big data analytics and how they benefit from data-in-motion. Discover all about Streams starting with the main components then dive further with Stream instillation, and upgrade and management capabilities including tools used for production. Through a solid understanding of big in motion, detailed illustrations, Endnotes that provide additional learning resources, and end of chapter summaries with helpful insight, data analysists and professionals looking to get more from their data will benefit from expert insight on: Data-in-motion processing and how it can be applied to generate new business opportunities The three approaches to processing data in motion and pros and cons of each The main components of Streams from runtime to installation and administration Multiple purposes of the Text Analytics toolkit The evolving Streams ecosystem A detailed roadmap for programmers to quickly become fluent with Streams Data-in-motion is rapidly becoming a business tool used to discover more about customers and opportunities, however it is only valuable if have the tools and knowledge to analyze and apply. This is an expert guide to IBM Streams and how you can harness this powerful tool to gain a competitive business edge.