Building Event-Driven Microservices: Leveraging Distributed Large-Scale Data [Minkštas viršelis]

  • Formatas: Paperback / softback, 275 pages, aukštis x plotis: 233x178 mm
  • Išleidimo metai: 31-Jul-2020
  • Leidėjas: O'Reilly Media, Inc, USA
  • ISBN-10: 1492057894
  • ISBN-13: 9781492057895
  • Formatas: Paperback / softback, 275 pages, aukštis x plotis: 233x178 mm
  • Išleidimo metai: 31-Jul-2020
  • Leidėjas: O'Reilly Media, Inc, USA
  • ISBN-10: 1492057894
  • ISBN-13: 9781492057895

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
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).