AWS Compute Blog
Python 3.13 runtime now available in AWS Lambda
This post is written by Julian Wood, Principal Developer Advocate, and Leandro Cavalcante Damascena, Senior Solutions Architect Engineer. AWS Lambda now supports Python 3.13 as both a managed runtime and container base image. Python is a popular language for building serverless applications. The Python 3.13 release includes a number of changes to the language, the implementation, and the […]
Reduce your Microsoft licensing costs by upgrading to 4th generation AMD processors
This post is written by Jeremy Girven, Solutions Architect at AWS and Chase Lindeman, Senior Specialist Solutions Architect at AWS. Amazon Web Services (AWS) and AMD have collaborated since 2018 to deliver cost effective performance for a broad variety of Microsoft workloads, such as Microsoft SQL Server, Microsoft Exchange Server, Microsoft SharePoint Server, Microsoft Systems […]
Efficiently monitor your On Demand Capacity Reservations (ODCR) by Grouping on CloudWatch Dimensions
This post is written by Ballu Singh, Principal Solutions Architect at AWS, Ankush Goyal, Enterprise Support Lead in AWS Enterprise Support, Hasan Tariq, Principal Solutions Architect with AWS and Ninad Joshi, Senior Solutions Architect at AWS. The On-Demand Capacity Reservations (ODCR) allows you to reserve compute capacity for your Amazon Elastic Compute Cloud (Amazon EC2) […]
Retaining Optimize CPUs configuration during Amazon EC2 scaling to save on licensing costs
This post is written by Rafet Ducic, Senior Solutions Architect at Amazon Web Services (AWS) Introduction Amazon Elastic Compute Cloud (Amazon EC2) now lets you modify CPU configurations after an instance has launched. With this new feature, users can change instance CPU settings either by directly modifying the CPU configuration, or when changing instance size […]
The attendee’s guide to the AWS re:Invent 2024 Compute track
This post is written by Markus Adhiwiyogo, Senior Product Marketing Manager at Amazon Web Services (AWS) From December 2nd to December 6th, AWS will hold its annual premier learning event: re:Invent. At this event, attendees can become stronger and more proficient in any area of AWS technology through a variety of experiences: large keynotes given […]
Introducing an enhanced local IDE experience for AWS Lambda developers
AWS Lambda is introducing an enhanced local IDE experience to simplify Lambda-based application development. The new features help developers to author, build, debug, test, and deploy Lambda applications more efficiently in their local IDE when using Visual Studio Code (VS Code). Overview The IDE experience is part of the AWS Toolkit for Visual Studio Code. […]
Introducing an enhanced in-console editing experience for AWS Lambda
AWS Lambda is introducing a new code editing experience in the AWS console based on the popular Code-OSS, Visual Studio Code Open Source code editor. This brings the familiar Visual Studio Code interface and many of the features directly into the Lambda console, allowing developers to use their preferred coding environment and tools in the cloud. […]
Simplifying Lambda function development using CloudWatch Logs Live Tail and Metrics Insights
This post is written by Shridhar Pandey, Senior Product Manager, AWS Lambda Today, AWS is announcing two new features which make it easier for developers and operators to build and operate serverless applications using AWS Lambda. First, the Lambda console now natively supports Amazon CloudWatch Logs Live Tail which provides you real-time visibility into Lambda […]
Learn how to deploy Falcon 2 11B on Amazon EC2 c7i instances for model Inference
This post is written by Paul Tran, Senior Specialist SA; Asif Mujawar, Specialist SA Leader; Abdullatif AlRashdan, Specialist SA; and Shivagami Gugan, Enterprise Technologist. Technology Innovation Institute (TII) has developed Falcon 2 11B foundation model (FM), a next-generation AI model that can be now deployed on Amazon Elastic Compute Cloud (Amazon EC2) c7i instances, which support […]
Designing Serverless Integration Patterns for Large Language Models (LLMs)
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 […]