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Asynchronous Messaging

Asynchronous Messaging

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Asynchronous Communication is the Future of Work

Enterprises are braces towards multiple application, API and Data usage over the cloud. Modern Multi-tier application requires application to talk in Asynchronous mode. Enterprise having large user pool and work load often require the architecture which supports complex integration scenario.

This back-end system allows to manage API load coming to Enterprise network. Some of the use cases are, aggregation of JASON/XML feeds coming from mobile users or other application to Asynchronous application like Kafka or MQ. Complex algorithm or routing logic including parsing of such feeds can be written with such frameworks.

Asynchronous Communication is the Future of Work

Advantages of Asynchronous Messaging

  • Higher Availability and Flexibility are the main advantages of asynchronous messaging
  • More parallel works allowed in asynchronous message passing
  • One message can be received by many – Local to Global
  • Message can be viewed on receivers own time
  • Message can be archived and looked up again if needed
  • Cost effective

We have experience working on complex architecture connecting multiple application in Enterprise using

  • Kafka
  • RabbitMQ
  • Apache Airflow
  • Celery
  • Redis

Enterprise class architecture allows you to setup, single node with multiple broker or multiple node with multiple broker depending on the load of the incoming message. Apache AirFlow / Celery allows you to write custom workflow and use data amongst the multiple channel simultaneously to be used in Big data, RDBMS or Object storage. Using such Enterprise Asynchronous server with Big Data is classic use case example of summarizing data at entry level.

When it comes to creating the Big Data or Data warehouse from the RDBMS or different data source, such Asynchronous Enterprise Server architecture plays major role. Talk to our expert today with your problem statement.

We help enterprise reduce their integration cost and make it very versatile to implement Data exchange between applications. Such servers can be often be used with API gateway for access management and security.

RabbitMQ is a general purpose message broker that supports protocols including, MQTT, AMQP, and STOMP. It can deal with high-throughput use cases, such as online payment processing. It can handle background jobs or act as a message broker between micro services.

Use Cases

Kafka Use Cases

  • Messaging. Kafka works well as a replacement for a more traditional message broker.
  • Website Activity Tracking.
  • Log Aggregation
  • Stream Processing
  • Event Sourcing
  • Commit Log

Apache Airflow Use Cases

  • Aggregate daily sales from CRM or ERP to send a daily report to executives
  • Use Airflow to organize and kick off machine learning jobs running on external Spark clusters, Hadoop Cluster or interfacing with Couch DB
  • Load website/application analytics data into a data warehouse on scheduled time

Celery Use cases

  • Running something in the background
  • Running something after the web request is completed
  • Making sure something is done, by executing it asynchronously and trying till it get success
  • Scheduling periodic work

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