The exponential growth of data combined with the need to derive real-time business value is a critical issue today. 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. Building an Event-Driven Data Mesh provides: Practical tips for iteratively building your own event-driven data mesh, including hurdles you'll experience, possible solutions, and how to obtain real value as soon as possible Solutions to pitfalls you may encounter when moving your organization from monoliths to event-driven architectures A clear understanding of how events relate to systems and other events in the same stream and across streams A realistic look at event modeling options, such as fact, delta, and command type events, including how these choices will impact your data products Best practices for handling events at scale, privacy, and regulatory compliance Advice on asynchronous communication and handling eventual consistency.
About the author
Adam is a Staff Technologist, Office of the CTO at Confluent. He has worked on a wide range of projects, including event-driven data mesh theory and proof of concepts, event-driven microservice strategies, and event and event stream design principles.
Before Confluent Adam worked in multiple e-commerce companies as a big data platform engineer, focusing on building batch solutions using Apache Spark and HDFS, before turning his attention to event-driven architectures. Since then he has been largely focused on building micro (and regular) services with Apache Kafka, and evangelizing the benefits of publishing useful business facts as a general-purpose data access layer.
Adam is the author of O'Reilly's Building Event-Driven Microservices (2020) and Building an Event-Driven Data Mesh (2023).
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