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Unlock near-real-time access to data at scale by leveraging event-driven microservices
| Publisher | O'Reilly Media |
| Publication date | August 11, 2020 |
| Edition | 1st |
| Language | English |
| Print length | 324 pages |
| ISBN-10 | 1492057894 |
| ISBN-13 | 978-1492057895 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 0.75 x 9 inches (17.8 x 1.9 x 22.9 cm) |
Developers looking to implement microservices architecture and leverage organizational data for scalable applications will benefit significantly.
Data architects aiming to design systems that efficiently utilize organizational data in a microservices framework will find valuable insights.
Tech leaders managing teams that require understanding of event-driven microservices to improve system responsiveness and agility.
Individuals with no prior knowledge of microservices or event-driven architecture may struggle with the complex concepts presented.
Building Event-Driven Microservices: Leveraging Organizational Data at Scale 1st Edition
"Building Event-Driven Microservices: Leveraging Organizational Data at Scale" is an introductory book that provides a good overview of event-driven microservices. However, it falls short in addressing key pain points and fails to provide detailed guidance on important topics such as correct sequencing of events and error handling strategies. The book does offer valuable insights into the mindset shift required for successful implementation of event-driven architectures and provides some practical examples of communication flows. It is also praised for being more advanced and less abstract than similar books by Sam Newman. One critique of the book is that the writing style can be confusing, requiring readers to re-read sentences multiple times to understand them. Additionally, the book includes references to technologies like Kafka streams, which may be difficult for readers unfamiliar with these technologies to grasp. Another point to note is that the book assumes familiarity with domain-driven design (DDD), and it is recommended to read books by Eric Evans and Vernon Vaughn on DDD before diving into this book. The author also takes a Kafka-centric approach, which may not make sense for those using different technologies to implement event-driven services. Overall, while the book provides a high-level overview of event-driven microservices and is beneficial for decision-makers and architects, it lacks the depth and practical guidance needed for practitioners in the field.
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