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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (76 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Every enterprise application creates data, whether it consists of log messages, metrics, user activity, outgoing messages, or something else. Moving all of this data is just as important as the data itself. This book's updated second edition shows application architects, developers, and production engineers new to the Kafka open source streaming platform how to handle real-time data feeds. Additional chapters cover Kafka's AdminClient API, new security features, and tooling changes. Engineers from Confluent and LinkedIn 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. You'll examine: How publish-subscribe messaging fits in the big data ecosystem Kafka producers and consumers for writing and reading messages Patterns and use-case requirements to ensure reliable data delivery Best practices for building data pipelines and applications with Kafka How to perform monitoring, tuning, and maintenance tasks with Kafka in production The most critical metrics among Kafka's operational measurements Kafka's delivery capabilities for stream processing systems
    Note: Online resource; Title from title page (viewed October 25, 2021) , Mode of access: World Wide Web.
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  • 2
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Parallel Title: Erscheint auch als
    Keywords: Apache Kafka (Computer program) ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: 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
    Note: Includes index. - Description based on print version record
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  • 3
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Posts & Telecom Press | Boston, MA : Safari
    ISBN: 9787115473271
    Language: English , Chinese
    Pages: 1 online resource (234 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: 每个应用程序都会产生数据,包括日志消息、度量指标、用户活动记录、响应消息等。如何移动数据,几乎变得与数据本身一样重要。如果你是架构师、开发者或者产品工程师,同时也是Apache Kafka新手,那么这本实践指南将会帮助你成为流式平台上处理实时数据的专家。 本书由出身于LinkedIn的Kafka核心作者和一线技术人员共同执笔,详细介绍了如何部署Kafka集群、开发可靠的基于事件驱动的微服务,以及基于Kafka平台构建可伸缩的流式应用程序。通过详尽示例,你将会了解到Kafka的设计原则、可靠性保证、关键API,以及复制协议、控制器和存储层等架构细节。 了解发布和订阅消息模型以及该模型如何被应用在大数据生态系统中 学习使用Kafka生产者和消费者来生成消息和读取消息 了解Kafka保证可靠性数据传递的模式和场景需求 使用Kafka构建数据管道和应用程序的最佳实践 在生产环境中管理Kafka,包括监控、调优和维护 了解Kafka的关键度量指标 探索Kafka如何成为流式处理利器
    Note: Online resource; Title from title page (viewed January 1, 2018) , Mode of access: World Wide Web.
    Library Location Call Number Volume/Issue/Year Availability
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