Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale, 2/e (Paperback)
暫譯: Kafka：權威指南：大規模實時數據與流處理，第2版（平裝本）

Shapira, Gwen, Palino, Todd, Sivaram, Rajini

Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale, 2/e (Paperback)
  • 出版商: O'Reilly
  • 出版日期: 2021-12-14
  • 定價: $2,820
  • 售價: 9.5 折 $2,679
  • 語言: 英文
  • 頁數: 455
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1492043087
  • ISBN-13: 9781492043089
  • 相關分類: Message Queue

    • 立即出貨 (庫存 < 3)

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商品描述

Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, 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:

  • Best practices for deploying and configuring Kafka
  • 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

商品描述(中文翻譯)

每個企業應用程式都會產生數據，無論是日誌消息、指標、用戶活動還是發送的消息。移動這些數據與數據本身同樣重要。在這個更新版中，對於新接觸 Kafka 流平台的應用架構師、開發人員和生產工程師，將學習如何處理流動中的數據。附加章節涵蓋了 Kafka 的 AdminClient API、事務、新的安全功能和工具變更。

來自 Confluent 和 LinkedIn 的工程師負責開發 Kafka，解釋如何部署生產環境中的 Kafka 集群、編寫可靠的事件驅動微服務，以及使用此平台構建可擴展的流處理應用程式。通過詳細的範例，您將學習 Kafka 的設計原則、可靠性保證、關鍵 API 和架構細節，包括複製協議、控制器和存儲層。

您將檢視：

- 部署和配置 Kafka 的最佳實踐
- 用於寫入和讀取消息的 Kafka 生產者和消費者
- 確保可靠數據傳遞的模式和用例需求
- 使用 Kafka 構建數據管道和應用程式的最佳實踐
- 如何在生產環境中執行監控、調整和維護任務
- Kafka 操作測量中最關鍵的指標
- Kafka 在流處理系統中的傳遞能力

作者簡介

Gwen Shapira is a system architect at Confluent helping customers achieve success with their Apache Kafka implementation. She has 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. She currently specializes in building real-time reliable data processing pipelines using Apache Kafka. Gwen is an Oracle Ace Director, an author of Hadoop Application Architectures, and a frequent presenter at data driven conferences. Gwen is also a committer on the Apache Kafka and Apache Sqoop projects.

Todd is a Staff Site Reliability Engineer at LinkedIn, tasked with keeping the largest deployment of Apache Kafka, Zookeeper, and Samza fed and watered. He is responsible for architecture, day-to-day operations, and tools development, including the creation of an advanced monitoring and notification system. Todd is the developer of the open source project Burrow, a Kafka consumer monitoring tool, and can be found sharing his experience on Apache Kafka at industry conferences and tech talks. Todd has spent over 20 years in the technology industryrunning infrastructure services, most recently as a Systems Engineer at Verisign, developing service management automation for DNS, networking, and hardware management, as well as managing hardware and software standards across the company.

Rajini Sivaram is a Software Engineer at Confluent designing and developing security features for Kafka. She is an Apache Kafka Committer and member of the Apache Kafka Program Management Committee. Prior to joining Confluent, she was at Pivotal working on a high-performance reactive API for Kafka based on Project Reactor. Earlier, Rajini was a key developer on IBM Message Hub which provides Kafka-as-a-Service on the IBM Bluemix platform. Her experience ranges from parallel and distributed systems to Java virtual machines and messaging systems.

Krit Petty is the Site Reliability Engineering Manager for Kafka at LinkedIn. Before becoming Manager, he worked as an SRE on the team expanding and increasing Kafka to overcome the hurdles associated with scaling Kafka to never before seen heights, including taking the first steps to moving LinkedIn's large-scale Kafka deployments into Microsoft's Azure cloud. Krit has a Master's Degree in Computer Science and previously worked managing Linux systems and as a Software Engineer developing software for high-performance computing projects in the oil and gas industry.

作者簡介(中文翻譯)

Gwen Shapira 是 Confluent 的系統架構師，協助客戶成功實現他們的 Apache Kafka 實作。她擁有 15 年的經驗，與代碼和客戶合作，建立可擴展的數據架構，整合關聯式和大數據技術。她目前專注於使用 Apache Kafka 建立實時可靠的數據處理管道。Gwen 是 Oracle Ace Director、《Hadoop Application Architectures》的作者，並且經常在數據驅動的會議上發表演講。Gwen 也是 Apache Kafka 和 Apache Sqoop 項目的委員。

Todd 是 LinkedIn 的資深網站可靠性工程師，負責維護最大的 Apache Kafka、Zookeeper 和 Samza 部署。他負責架構、日常運營和工具開發，包括創建先進的監控和通知系統。Todd 是開源項目 Burrow 的開發者，這是一個 Kafka 消費者監控工具，他經常在行業會議和技術演講中分享他在 Apache Kafka 的經驗。Todd 在技術行業工作超過 20 年，負責基礎設施服務，最近擔任 Verisign 的系統工程師，開發 DNS、網絡和硬體管理的服務管理自動化，並管理公司內的硬體和軟體標準。

Rajini Sivaram 是 Confluent 的軟體工程師，設計和開發 Kafka 的安全功能。她是 Apache Kafka 的委員，並且是 Apache Kafka 程式管理委員會的成員。在加入 Confluent 之前，她在 Pivotal 工作，為基於 Project Reactor 的 Kafka 開發高性能反應式 API。早些時候，Rajini 是 IBM Message Hub 的主要開發者，該平台在 IBM Bluemix 上提供 Kafka-as-a-Service。她的經驗涵蓋從平行和分散式系統到 Java 虛擬機和消息系統。

Krit Petty 是 LinkedIn 的 Kafka 網站可靠性工程經理。在成為經理之前，他作為 SRE 在團隊中工作，擴展和增強 Kafka，以克服與擴展 Kafka 相關的挑戰，包括邁出將 LinkedIn 大規模 Kafka 部署遷移到 Microsoft Azure 雲的第一步。Krit 擁有計算機科學碩士學位，之前曾管理 Linux 系統，並作為軟體工程師為石油和天然氣行業的高性能計算項目開發軟體。

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