Tag Archives: event sourcing

DATA PERSISTENCE IN LAGOM


Are you finding it difficult to understand lagom persistence? Don’t worry because help is right here. In this blog, we will learn about lagom’s persistence with the help of a simple application and also discuss its theoretical aspects. Before we … Continue reading

Posted in Cassandra, database, Microservices, NoSql, Scala | Tagged , , , , , , , , | 5 Comments

Lagom Framework: The Legacy WordCount Example


What is Lagom? Lagom is an open source micro-service framework, built with Akka message-driven runtime and Play web framework and finally light bend service orchestration. Mixing all these technologies abstracts away the complexities of building, running, and managing microservice architectures. … Continue reading

Posted in big data, Microservices, Scala | Tagged , , , , | 2 Comments

Building Microservices Based Enterprise Applications in Java Using Lagom – Part I


As we know, now days, most of the enterprise applications design as a “Microservices Architecture” because of scalability, sharding, loosely-coupling and many others reasons are there. On the other hand  JavaEE help us for building an Enterprise Applications. As we … Continue reading

Posted in Akka, Java, Microservices, Scala | Tagged , , , , , , , , , , | 2 Comments

Event Sourcing with Eventuate


Hi all, Knoldus had organized an hours session on 3rd February 2017 at 4:00 PM. Topic was Event Sourcing with Eventuate. Many enthusiasts  joined and learned from the session. I am  sharing the slides of the session here. Please let me know … Continue reading

Posted in akka-http, Cassandra, Scala | Tagged , | 2 Comments

Scala-IOT : Introduction to Internet Of Things.


Recently this word IOT is gaining lot of popularity. And we see a lot of news on it like the world is moving towards IOT , and its the next big thing and smart cities are no longer a fiction  … Continue reading

Posted in IOT, Scala | Tagged , , , , , , , , , , , | 12 Comments

CQRS in a jiffy!


Segregate operations that read data from operations that update data by using separate interfaces. This pattern can maximize performance, scalability, and security; support evolution of the system over time through higher flexibility; and prevent update commands from causing merge conflicts … Continue reading

Posted in Scala | Tagged , , | 1 Comment