An event-driven data mesh can power real-time operational and analytical workloads, all from a single set of data product streams. With practical real-world examples, this book shows you how to successfully design and build an event-driven data mesh.
An event-driven data mesh can power real-time operational and analytical workloads, all from a single set of data product streams. With practical real-world examples, this book shows you how to successfully design and build an event-driven data mesh.
Adam Bellemare is a Staff Technologist, Office of the CTO at Confluent. Previously, staff Engineer, Data Platform at Shopify and he was at Flipp from 2014, first as a Senior Developer, followed by a role as Staff. He has also 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). He is the author of Building Event-Driven Microservices (2020) with O'Reilly
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