Managing continuous applications Track

Building Flink As a Service platform at Uber

Stream processing plays an important role in Uber’s real-time business. It has been widely used to support many use cases in Uber, like surge pricing and restaurant manager. To support all the stream processing use cases at Uber, the stream processing platform team has built the Flink As a Service platform. In this talk, we will present the design and architecture of the Flink As a Service platform. Specifically, we will discuss how we manage the deployment, how we make the platform highly available to support critical real-time business, how we scale the platform to support the entire company, and our experience running the platform in production.

Authors

Shuyi Chen
Shuyi Chen
Senior Software Engineer Uber
Shuyi Chen

Shuyi Chen is a senior software engineer at Uber. He built Uber’s real-time complex event processing platform for the marketplace, which powers 100+ production real-time use cases. Currently, he is the tech lead of the stream processing team in Uber data infrastructure. Shuyi has years of experience in storage infrastructure, data infrastructure, and Android and iOS development at both Google and Uber.

Rong Rong
Rong Rong
Software Engineer Uber
Rong Rong

Rong Rong is a software engineer at Uber’s streaming processing team. He worked on Uber’s SQL-based stream analytics engine AthenaX which is currently powering over 500+ production real-time data analytics and ML pipelines. Previously Rong held a software and machine learning engineer position in Qualcomm computer vision team.

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