Our team attended the AWS re:Invent in Las Vegas.

Here is a list of the main announcements that were made during the event:


  1. General availability of AWS Well-Architected Custom Lenses, a new feature of the AWS Well-Architected Tool that lets us bring our own best practices to complement the existing framework based on customer's industry, operational plans, and internal processes.


  1. Announced preview for AWS Migration Hub Refactor Spaces. A new capability of AWS Migration Hub to ease refactoring existing applications into distributed applications, typically based on microservices.


  1. A new pillar for the Well-Architected Framework. The Sustainability Pillar contains questions aimed at evaluating the design, architecture, and implementation of your workloads to reduce their energy consumption and improve their efficiency.


  1. Three new SDKs were launched in public preview for Swift, Kotlin, and Rust programming languages.


  1. New EC2 instance types including Graviton3, Trainium, and M1 Mac compute. The most interesting one of these was the C7g, a new EC2 instance powered by Graviton3, the latest of the custom ARM-based silicon processor.


  1. Announced preview for AWS IoT RoboRunner for Building Robot Fleet Management Applications. AWS IoT RoboRunner is a new robotics service that makes it easier for enterprises to build and deploy applications that help fleets of robots work seamlessly together.


  1. Introduced Amazon Braket Hybrid Jobs. Set up, monitor, and efficiently run hybrid quantum-classical workloads to confidently execute your algorithms quickly and predictably, with on-demand priority access to QPUs.


  1. New AWS Scholarship Program. This program helps Underrepresented and Underserved Students Prep for Careers in AI and ML. The AWS AI & ML Scholarship program is launching as part of the all-new AWS DeepRacer Student service and Student League.


  1. Now in Preview – Amazon SageMaker Studio Lab, a Free Service to Learn and Experiment with ML. AWS launched a free service that enables anyone to learn and experiment with ML without needing an AWS account, credit card, or cloud configuration knowledge.


  1. Introduced Karpenter, an Open-Source High-Performance Kubernetes Cluster Autoscaler. New open-source project helps improve your application availability and cluster efficiency by rapidly launching right-sized compute resources in response to changing application loads.


Sebastian Ganame (CEO) and Damian Galletini (Chief of Engineering)


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