Название: Building an Event-Driven Data Mesh: Patterns for Designing & Building Event-Driven Architectures (4th Early Release)Автор: Adam Bellemare
Издательство: O’Reilly Media, Inc.
Год: 2023-02-16
Страниц: 300
Язык: английский
Формат: epub (true)
Размер: 10.1 MB
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.
In both the microservice and data mesh world, common infrastructure services (eg: Git, Kubernetes, containers, continuous integration, monitoring, etc) provide self-service tooling that lets you focus on building useful business services, instead of getting lost in the infrastructure and platforms. Data mesh draws a direct parallel to the microservices architecture - but with data sets, instead of services.
The benefits of a well-built data mesh include:
• Discover trustworthy and reliable data, making it cheaper and faster to put it into use.
• Easier to publish new data sources, such that others can make use of them quickly and easily.
• Data is treated as a first-class product, just like any other mission critical product, including dedicated resourcing, well-defined responsibilities, SLAs, and product release cycles.
• Reduction, and eventual elimination, of unreliable, fragile, and expensive data pipelines and ETLs.
• Eliminating data inconsistencies between analytics and operational systems, by using event streams as the single source of truth.
Building an Event-Driven Data Mesh provides:
Practical examples of event and event stream design, including recommendations
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 state, delta, and command type events, including how these choices will impact your data products
Methods for handling events at scale, including multitenancy
Best practices for privacy and regulatory compliance
Advice on handling eventual consistency and building multitenancy solutions and asynchronous communication
Practical tips for iteratively building your own event-driven data mesh, including hurdles you'll encounter, 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
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