Enhancing AWS CloudTrail Observability Using Event-Driven Ansible

AWS CloudTrail is a useful tool that records everything happening in AWS account, such as who did what, when, and from where. It helps with tracking changes, spotting unusual behavior, and meeting security and audit requirements. By combining CloudTrail with Event-Driven Ansible, we can take automatic action as soon as something important happens without needing someone to step in manually. In this talk, I will demonstrate how to set up this integration using the ansible.eda.aws_cloudtrail module. In this demo, I will give a demo on how to monitor events like starting or stopping an EC2 instance, and automatically trigger a response. This setup can be customized to handle many other events, helping teams manage their cloud systems more easily, securely, and efficiently.

Building Production Applications with Generative AI.

Generative AI is helping developers to code faster with coding assistants, and future tools promise to do much more of the software development lifecycle. Developers don't need to wait to take advantage of these advanced LLM capabilities. By using existing software development knowledge and prompting techniques, developers can build production grade Micro-SaaS applications using existing chatbots from providers like Anthropic. In this talk we will walk through a case study which delivered a custom Micro-SaaS app to solve a customer's business problem.

Visualize and design your serverless applications

Discover how to start building serverless web applications that can solve common problems. In this session, learn how to get started with AWS Application Composer, a low-code, visual interface for designing and building serverless applications. Application Composer helps builders understand their application architecture, collaborate, and manage application configuration. Also, learn how to prototype a serverless generative AI application leveraging Amazon Bedrock from concept to a fully featured application using Application Composer and Amazon Q Developer in your IDE.

Unleashing the Power of AWS Network Firewall: Securing Your Egress Traffic with Centralized Control

Firewalls are crucial for infrastructure security as they help protect outgoing data from an organization's network, known as egress traffic. This session will cover the importance of securing egress traffic and explore how AWS Network Firewall can provide a centralized solution for managing and monitoring outbound traffic from your AWS environment.

CI/CD: GitHub Actions to ECS

Peter will walk through how he has set up a CI/CD pipeline using GitHub Actions deploying to ECS. If you have ever been curious about setting up continuous deployment, this talk will give you the foundation to get started.

The Bedrock of RAG

Retrieval Augmented Generation (RAG) is one of the hottest topics for making data more accessible and valuable. And it's easy to get started with it on AWS, especially when using Bedrock as the foundation for the Large Language Model (LLM). This talk shows how to get started with RAG on AWS, using a playground to go from custom data to an interactive application in minutes. The second part of the demo then dives into more advanced topics around Bedrock and how to tune your RAG's generation part: * How does the chosen LLM influence quality and performance? * Can you tune the prompt? * Can the LLM also help with the retrieval step? At the end of this session, you will better understand of how to get started and how to get the most out of Bedrock with your AWS-powered RAG.

Leverage ML Inference for Generative AI Models on AWS

LLM is becoming essential for many companies - either as a core product, an internal tool, or as a service for improving operations. One challenge when deploying the LLM to production is navigating through different hardware, service, and orchestration options. This presentation is focused on providing a comprehensive understanding of different LLM deployment options in AWS Cloud. We will explore different ways of deploying pretrained models to the AWS cloud from SageMaker Real-time inference to Elastic Container Service and AWS Lambda. We will also cover different ways of deploying ML infrastructure - from SageMaker JumpStart and SageMaker SDK to AWS Copilot and AWS SAM and options like Amazon Bedrock. There will be a live demo that shows how the deployment process would look like for the generative AI model using SageMaker JumpStart, ECS/Fargate + AWS Copilot and for AWS Lambda.