Predictive Analytics With Microservices > Predictive Analytics With Microservices

Predictive Analytics With Microservices

At JPyramid we are constantly looking for the coolest way for humans to interact with advanced technology.  In particular, we are very excited by the use of Machine Learning to predict different events that are important for the operation of a business.

There are different ways to build software systems and more recently Microservices have become a more efficient way of doing it.   This approach reduces the overall cost of the project through re-use of services across multiple projects, reduces time to test, build and deploy the new applications and improves the project management process.

If we look at the core properties of the Microservices we can see how this is achieved through following properties:

  • All the things are decentralised
  • Independent deployment of components
  • Failures in the components are isolated
  • Internal details are hidden
  • Everything is automated

During the implementation phase you would create each service in a separate source code repository and create individual deployment artifacts for each service in an automated fashion.
This will reduce time to delivery and improve overall quality of the deployed software system.

On the left-hand side is a potential structure of a Prediction Application with automated builds.





Machine Learning

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