Steve Kendrex

You want to ship AI, but your compliance team won't sign off until the solution meets their regulatory requirements. This session shows how Bedrock protects data from the hardware up, with zero operator access enforced at the chip so no one, not even AWS operators, can access your prompts and completions.

AI coding agents are transforming how developers build and operate modern cloud-native applications. With tools such as Kiro CLI, Kiro IDE, or any MCP-compatible AI coding assistant, developers are embracing AI to move faster and scale smarter.

In the modern digital era, running artificial intelligence (AI) and machine learning (ML) workloads is essential for powering applications like image generation and natural language processing. In this session, learn techniques to maximize the performance and scalability of these workloads to meet dynamic demand.

Customers often ask how can they take an existing application running on their Amazon EC2 instances and migrate it to a containerized workflow or environment. In this chalk talk, take an application that is running on Amazon EC2 and walk through how to break it up into containers.

The Digital Marketing industry generates petabytes of event data per day. In this session, learn how NextRoll, a marketing technology provider and platform, uses AWS Batch to process these petabytes of data in a stable and efficient way.

Learn how Uber uses AWS Batch to run hundreds of thousands of autonomous vehicle simulations across as many vCPUs every day. Hear the story of how the company built a highly performant and scalable simulation pipeline on native AWS services.

This presentation was recorded prior to re:Invent. Flyte is the backbone for large-scale machine learning and data processing pipelines at Lyft and is used across many business-critical applications.

Amazon Lex creates conversational interfaces powered by the same deep learning technologies used in Alexa. AWS Batch dynamically provisions the optimal quantity and type of compute resources based on the volume and specific resource requirements of the batch jobs submitted.