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.

Durable, high throughput data streaming

as a log aggregator

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

Used as a integration middleware by messaging interchanging.

realtime distributed broker

Distributed system messaging.

消息队列

消息队列，主要用于处理各个微服务之间的通信以及异步处理相关逻辑

Event bus

Used for communications and triggering jobs across ETL systems

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

Internal, distributed message queue. Main communication happens via port 4730 and consists of simple json messages. Completely independent of the main website back-end.