AWS News Blog

Aurora Serverless MySQL Generally Available

You may have heard of Amazon Aurora, a custom built MySQL and PostgreSQL compatible database born and built in the cloud. You may have also heard of serverless, which allows you to build and run applications and services without thinking about instances. These are two pieces of the growing AWS technology story that we’re really excited to be working on. Last year, at AWS re:Invent we announced a preview of a new capability for Aurora called Aurora Serverless. Today, I’m pleased to announce that Aurora Serverless for Aurora MySQL is generally available. Aurora Serverless is on-demand, auto-scaling, serverless Aurora. You don’t have to think about instances or scaling and you pay only for what you use.

AWS Online Tech Talks – August 2018

AWS Online Tech Talks are live, online presentations that cover a broad range of topics at varying technical levels. Join us this month to learn about AWS services and solutions. We’ll have experts online to help answer any questions you may have. We’ve also launched our first-ever office hours style tech talk, where you have the […]

New – Provisioned Throughput for Amazon Elastic File System (EFS)

Amazon Elastic File System (Amazon EFS) lets you create petabyte-scale file systems that can be accessed in massively parallel fashion from hundreds or thousands of Amazon Elastic Compute Cloud (Amazon EC2) servers and on-premises resources, scaling on demand without disrupting applications. Behind the scenes, storage is distributed across multiple Availability Zones and redundant storage servers […]

Thoughts On Machine Learning Accuracy

This blog shares some brief thoughts on machine learning accuracy and bias. Let’s start with some comments about a recent ACLU blog in which they ran a facial recognition trial. Using Rekognition, the ACLU built a face database using 25,000 publicly available arrest photos and then performed facial similarity searches on that database using public […]

Amazon SageMaker Adds Batch Transform Feature and Pipe Input Mode for TensorFlow Containers

At the New York Summit a few days ago we launched two new Amazon SageMaker features: a new batch inference feature called Batch Transform that allows customers to make predictions in non-real time scenarios across petabytes of data and Pipe Input Mode support for TensorFlow containers. SageMaker remains one of my favorite services and we’ve […]