Applying Federated Learning for ML at the Edge

By Dustin Ward

AWS FeedApplying Federated Learning for ML at the Edge Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the…

Amazon Location Service adds metadata help customers reduce costs

By Dustin Ward

AWS FeedAmazon Location Service adds metadata help customers reduce costs Today, Amazon Location Service added metadata for tracking position updates to help developers reduce cost, improve accuracy, and simplify the development of tracking applications. Amazon Location Service Trackers already make it easy for developers to build highly scalable device-tracking applications by enabling them to retrieve the…

Automate Amazon EKS upgrades with infrastructure as code

By Dustin Ward

AWS FeedAutomate Amazon EKS upgrades with infrastructure as code In this post, we explain how to use managed node groups to upgrade Amazon Elastic Kubernetes Service (Amazon EKS) cluster nodes in parallel from 1.19 to 1.20. Users can use the AWS Service Catalog to support an automated workflow with granular controls. This capability provides the…

Optimize your IoT Services for Scale with IoT Device Simulator

By Dustin Ward

AWS FeedOptimize your IoT Services for Scale with IoT Device Simulator The IoT (Internet of Things) has accelerated digital transformation for many industries. Companies can now offer smarter home devices, remote patient monitoring, connected and autonomous vehicles, smart consumer devices, and many more products. The enormous volume of data emitted from IoT devices can be…