reinvent2024-svs217

Improve throughput and monitoring of serverless streaming workloads

AWS Lambda event source mappings simplify building the processing layer for streaming workloads. Connect your event source to your Lambda function to use built-in integrations to filter and batch messages and readily handle errors. Join this session to learn how to use newly launched features to improve the throughput and observability of new and existing processing workloads, without changes to your function code. Explore how to meet even the most stringent processing needs when working with Apache Kafka event sources and how new enhanced metrics improve visibility into Amazon SQS, Amazon Kinesis, Kafka, and Amazon DynamoDB event sources

Video (click to watch)

Slides

• Session presentation slides

Useful links

• [Blog] Introducing Provisioned Mode for Kafka Event Source Mappings with AWS Lambda
• [Blog] Scaling improvements when processing Apache Kafka with AWS Lambda
• [Blog] Using Amazon MSK as an event source for AWS Lambda
• [Blog] Offset lag metric for Amazon MSK as an event source for Lambda
• [Blog] AWS Lambda scaling controls for Kinesis and DynamoDB event sources
• [Guide] Serverless streaming processing with AWS Lambda
• [Guide] Serverless Kafka processing with AWS Lambda
• [Resources] Kafka resources at Serverlessland.com
• [Video] Understanding AWS Lambda scaling and throughput
• [Video] AWS re:Invent 2024 - AWS Lambda and Apache Kafka for real-time data processing applications (SVS321)
• [Workshop] Amazon MSK workshop