AWS re:Invent 2019: [REPEAT 1] Serverless stream processing pipeline best practices (SVS317-R1)
Published on Dec 07, 2019
Streaming data pipelines are increasingly used to replace batch processing with real-time decision-making for use cases including log processing, real-time monitoring, data lake analytics, and machine learning. Join this session to learn how to leverage Amazon Kinesis and AWS Lambda to solve real-time ingestion, processing, storage, and analytics challenges. We introduce design patterns and best practices as well as share a customer journey in building large-scale real-time serverless analytics capabilities.
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AWS re:Invent 2019: Cloud-native machine learning at Lyft with AWS Batch and Amazon EKS (CON235-P)
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1:00:27
AWS re:Invent 2019: [REPEAT 1] Serverless stream processing pipeline best practices (SVS317-R1)
1:00:27
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AWS re:Invent 2019: Uber builds scalable autonomous vehicle simulations w/ AWS Batch (CMP328-R1)
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