Sid Anand on Building Agari’s Cloud-native Data Pipelines with AWS Kinesis and Serverless
Published June 9, 2017
25 min
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    Wesley Reisz talks to Sid Anand, a data architect at cybersecurity company Agari, about building cloud-native data pipelines. The focus of their discussion is around a solution Agari uses that is built from Amazon Kinesis Streams, serverless functions, and auto scaling groups. Sid Anand is an architect at Agari, and a former technical architect at eBay, Netflix, and LinkedIn. He has 15 years of data infrastructure experience at scale, is a PMC for Apache Airflow, and is also a program committee chair for QCon San Francisco and QCon London. Why listen to this podcast - Real-time data pipeline processing is very latency sensitive - Micro-batching allows much smaller amounts of data to be processed - Use the appropriate data store (or stores) to support the use of the dataIngesting data quickly into a clean database with minimal indexes can be fast - Communicate using a messaging system that supports schema evolution More on this: Quick scan our curated show notes on InfoQ You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. Subscribe: Like InfoQ on Facebook: Follow on Twitter: Follow on LinkedIn: Want to see extented shownotes? Check the landing page on InfoQ:
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