Building Event-Driven Microservices: Leveraging Organizational Data at Scale
Bellemare, Adam
- 出版商: O'Reilly
- 出版日期: 2020-08-11
- 定價: $2,280
- 售價: 9.5 折 $2,166
- 貴賓價: 9.0 折 $2,052
- 語言: 英文
- 頁數: 316
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1492057894
- ISBN-13: 9781492057895
-
相關分類:
Microservices 微服務、SOA
-
相關翻譯:
微服務與事件驅動架構 (簡中版)
立即出貨 (庫存 < 3)
買這商品的人也買了...
-
$580$458 -
$1,935Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems (Paperback)
-
$320$250 -
$580$493 -
$2,502Building Microservices: Designing Fine-Grained Systems, 2/e (Paperback)
-
$1,733Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith (Paperback)
-
$474$450 -
$1,710$1,620 -
$980$774 -
$714$678 -
$534$507 -
$439數據中台架構 — 企業數據化最佳實踐
-
$1,000$780 -
$500$390 -
$708$673 -
$1,578Data Management at Scale: Best Practices for Enterprise Architecture
-
$414$393 -
$1,500$1,425 -
$550$429 -
$500$390 -
$1,764Flow Architectures: The Future of Streaming and Event-Driven Integration
-
$2,025Practical Process Automation: Orchestration and Integration in Microservices and Cloud Native Architectures
-
$2,660$2,520 -
$1,760Design Patterns for Cloud Native Applications: Patterns in Practice Using APIs, Data, Events, and Streams
-
$2,080$1,976
相關主題
商品描述
Organizations today often struggle to balance business requirements with ever-increasing volumes of data. Additionally, the demand for leveraging large-scale, real-time data is growing rapidly among the most competitive digital industries. Conventional system architectures may not be up to the task. With this practical guide, you'll learn how to leverage large-scale data usage across the business units in your organization using the principles of event-driven microservices.
Author Adam Bellemare takes you through the process of building an event-driven microservice-powered organization. You'll reconsider how data is produced, accessed, and propagated across your organization. Learn powerful yet simple patterns for unlocking the value of this data. Incorporate event-driven design and architectural principles into your own systems. And completely rethink how your organization delivers value by unlocking near-real-time access to data at scale.
You'll learn:
- How to leverage event-driven architectures to deliver exceptional business value
- The role of microservices in supporting event-driven designs
- Architectural patterns to ensure success both within and between teams in your organization
- Application patterns for developing powerful event-driven microservices
- Components and tooling required to get your microservice ecosystem off the ground
商品描述(中文翻譯)
現今的組織常常在商業需求和不斷增加的數據量之間難以平衡。此外,在最具競爭力的數位產業中,對於利用大規模、即時數據的需求正在迅速增長。傳統的系統架構可能無法勝任這項任務。透過這本實用指南,您將學習如何運用事件驅動的微服務原則,在組織的各個業務單位之間充分利用大規模數據。
作者Adam Bellemare將帶領您進入建立以事件驅動的微服務為核心的組織的過程。您將重新思考數據在組織中的產生、存取和傳播方式。學習強大而簡單的模式,以開發出這些數據的價值。將事件驅動的設計和架構原則融入到您自己的系統中。並徹底重新思考您的組織如何通過大規模數據的幾乎即時存取來提供價值。
您將學到以下內容:
- 如何運用事件驅動架構提供卓越的商業價值
- 微服務在支援事件驅動設計中的角色
- 在組織內部和團隊之間確保成功的架構模式
- 開發強大的事件驅動微服務的應用模式
- 啟動您的微服務生態系統所需的組件和工具
作者簡介
Adam Bellemare is a Staff Engineer, Data Platform at Flipp. He's held this position since 2017. He joined Flipp in 2014 as a senior developer at Flipp. Prior to that, he held positions in embedded software development and quality assurance. His expertise includes: Devops (Kafka, Spark, Mesos, Zookeeper Clusters. Programmatic Building, scaling, destroying); Technical Leadership (Bringing Avro formatting to our data end-to-end, championing Kafka as the event-driven microservice bus, prototyping JRuby, Scala and Java Kafka clients and focusing on removing technical impediments to allow for product delivery); Software Development (Building microservices in Java and Scala using Spark and Kafka libraries); and Data Engineering (Reshaping the way that behavioral data is collected from user devices and shared with our Machine Learning, Billing and Analytics teams).
作者簡介(中文翻譯)
Adam Bellemare是Flipp的數據平台高級工程師。他自2017年起擔任這個職位。他於2014年加入Flipp,當時是一名高級開發人員。在此之前,他曾在嵌入式軟件開發和質量保證方面擔任職位。他的專業知識包括:Devops(Kafka、Spark、Mesos、Zookeeper Clusters. Programmatic Building, scaling, destroying);技術領導(將Avro格式引入我們的數據端到端,推廣Kafka作為事件驅動的微服務總線,原型化JRuby、Scala和Java Kafka客戶端,並致力於消除技術障礙以實現產品交付);軟件開發(使用Java和Scala構建微服務,使用Spark和Kafka庫);以及數據工程(重塑從用戶設備收集行為數據並與我們的機器學習、計費和分析團隊共享的方式)。