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Microservices

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vanmathi b edited this page Sep 21, 2019 · 6 revisions

Introduction to Microservices

Microservices are a form of service-oriented architecture style wherein applications are built as a collection of different smaller services rather than one whole app. Instead of a monolithic app, you have several independent applications that can run on their own and may be created using different coding or programming languages. Big and complicated applications can be made up of simpler and independent programs that are executable by themselves. These smaller programs are grouped together to deliver all the functionalities of the big, monolithic app.

Keyingredients to Microservice Architecture

  • The microservice architecture plans we develop for our customers emphasize the speed of new feature development, of ongoing maintenance, and of the day-to-day work of deployment and testing.
  • Faster development and iteration.
  • Microservices are all about autonomy, decentralization, and real-time computing. Operate peer-to-peer using APIs. Graph data, polyglot, real-time event-driven use cases.
  • Provide the ability to decouple and deliver application functionality faster with greater stability, agile development and teamS.

Microservices in Web-Knowledge-Generator

  1. Upstream Microservice
  2. Data-cleaning Microservice
  3. Sentimental Analysis Microservice
  4. Login-Authentication Microservice
  5. Feed-service Microservice
  6. Notify-service Microservice
  7. ibm-domain Microservice
  8. political-domain Microservice
  9. Downstream-Microservice

Upstream-Microservice

It takes the streaming data from twitter adapter.

Data-cleaning Microservice

Receives data from upstream filters unnecessary properties and non-english texts from tweet entities and implements spell check on filtered tweet entity.

Sentimental Analysis Microservice

Takes the object from data-cleaning service and calculates the sentiment type and score using standford core NLP.

Login-Authentication Microservice

Takes username and password and logs in to respective domain dashboard

Feed-service Microservice

Takes tweet object from kafka topic and gives it to the front end respective dashboards

Notify-service Microservice

It notifies stakeholders with the mail.

ibm-domain Microservice

It takes the analysed tweet entity from sentimental Analysis and classifies various domains into respective subDomains.

political-domain Microservice

It takes the analysed tweet entity from sentimental Analysis and classifies various domains into respective subDomains.

Downstream-Microservice

It will get the raw data from upstream and gets data from organisation domain and political domain and store it in cassandra.

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