Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.

Provides durable queues that allow the front-end website to accept events and turn them into jobs for the background workers to process.

Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

Used along with Celery, for offloading CPU intensive tasks to separate workers instead of running them on our application server.

We use it as an add-on to heroku and it is an amazing message queue.

We are using Kafka as a message queue to process our widget logs.

Used for communications and triggering jobs across ETL systems

Used as a integration middleware by messaging interchanging.