Artificial Intelligence
Author: Ebbey Thomas
Ebbey Thomas is a Senior Cloud Architect at AWS, with a strong focus on leveraging generative AI to enhance cloud infrastructure automation and accelerate migrations. In his role at AWS Professional Services, Ebbey designs and implements solutions that improve cloud adoption speed and efficiency while ensuring secure and scalable operations for AWS users. He is known for solving complex cloud challenges and driving tangible results for clients. Ebbey holds a BS in Computer Engineering and an MS in Information Systems from Syracuse University.
Enhance generative AI solutions using Amazon Q index with Model Context Protocol – Part 1
In this post, we explore best practices and integration patterns for combining Amazon Q index and MCP, enabling enterprises to build secure, scalable, and actionable AI search-and-retrieval architectures.
Accelerate migration portfolio assessment using Amazon Bedrock
In this blog post, we will harness the power of generative AI and Amazon Bedrock to help organizations simplify, accelerate, and scale migration assessments.
Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock
As you navigate the complexities of cloud migration, the need for a structured, secure, and compliant environment is paramount. AWS Landing Zone addresses this need by offering a standardized approach to deploying AWS resources. This makes sure your cloud foundation is built according to AWS best practices from the start. With AWS Landing Zone, you eliminate the guesswork in security configurations, resource provisioning, and account management. It’s particularly beneficial for organizations looking to scale without compromising on governance or control, providing a clear path to a robust and efficient cloud setup. In this post, we show you how to generate customized, compliant IaC scripts for AWS Landing Zone using Amazon Bedrock.