Adam Wagner

In this code talk, see live coding of a serverless application for producing meeting summaries with generative AI. Learn how to orchestrate transcription using Amazon Transcribe and summarization with Amazon Bedrock, orchestrated with AWS Step Functions.

In this chalk talk, explore the convergence of event-driven architectures (EDAs) and real-time event streaming to meet modern business needs. Learn about Amazon EventBridge, Apache Kafka, and their roles in facilitating real-time decision-making, business velocity, and operational autonomy.

Learn how to use AWS serverless technologies and generative AI models in Amazon Bedrock to quickly build, deploy, and manage intelligent chatbots. In this code talk, learn how to use AWS Lambda to handle and process natural language, and use generative AI models to generate dynamic, natural responses.

Scaling data processing workloads is a significant challenge for many organizations. However, it can be simplified with AWS Step Functions Distributed Map state.

Data drives many businesses, but the way it is ingested and processed is changing. Serverless data processing with AWS Lambda and AWS Step Functions offers new ways to process data quickly and efficiently.

Parallel processing is a common computing approach to help solve large problems in a shorter period of time. By running the components of a problem concurrently, the total duration is greatly reduced.

Many enterprises that try to accelerate development times for their digital native applications default to serverless architectures, and for good reasons. Self-serve provisioning, elastic scaling, lower TCO, and industry-standard security features make it easy for developers to spend more time building and less time managing.

In this chalk talk, dive deep into serverless streaming use cases—one with Apache Kafka and AWS Lambda and another with Amazon Kinesis and Lambda. Learn how to address reliability, scalability, and cost considerations as you design serverless streaming applications.

Dive into the details of using Amazon Kinesis Data Streams and Amazon DynamoDB Streams as event sources for AWS Lambda. This session walks you through how AWS Lambda scales along with these two event sources.

In this session, we dive into the details of consuming Amazon DynamoDB Streams and Amazon Kinesis Data Streams with Lambda. We walk through common architecture patterns, and we discuss the different scaling options for DynamoDB and how they affect the stream.