Category: Amazon Bedrock

This post is written by Uma Ramadoss, Principal Specialist SA, Serverless and Dhiraj Mahapatro, Principal Specialist SA, Amazon Bedrock AWS Step Functions is introducing variables and JSONata data transformations. Variables allow developers to assign data in one state and reference it in any subsequent steps, simplifying state payload management without the need to pass data […]

AWS re:Invent 2024 offers an extensive selection of serverless and application integration content. AWS re:Invent Banner For detailed descriptions and schedule, visit the AWS re:Invent Session Catalog. Join AWS serverless experts and community members at the AWS Modern Apps and Open Source Zone in the AWS Expo Village. This serves as a hub for serverless […]

This post is written by Josh Hart, Principal Solutions Architect and Thomas Moore, Senior Solutions Architect This post explores best practice integration patterns for using large language models (LLMs) in serverless applications. These approaches optimize performance, resource utilization, and resilience when incorporating generative AI capabilities into your serverless architecture. Overview of serverless, LLMs and example […]

Welcome to the 26th edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. Every quarter, we share all the most recent product launches, feature enhancements, blog posts, webinars, live streams, and other interesting things that you might have missed! In case you missed our last ICYMI, check out what happened last […]

Welcome to the 25th edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. Every quarter, we share all the most recent product launches, feature enhancements, blog posts, webinars, live streams, and other interesting things that you might have missed! In case you missed our last ICYMI, check out what happened last […]

This post is written by Pascal Vogel, Solutions Architect, and Martin Sakowski, Senior Solutions Architect. Large language models (LLMs) are proving to be highly effective at solving general-purpose tasks such as text generation, analysis and summarization, translation, and much more. Because they are trained on large datasets, they can use a broad generalist knowledge base. […]