AWS News Blog

Companies are increasingly building their applications as microservices (many separate services that each do a single job). Microservices often allow companies to iterate and deploy more quickly. Many of these microservice-based modern applications are built using various types of cloud resources and deployed on dynamically changing infrastructure. Previously you had to use configuration files to […]

As you know, you can easily build highly scalable AWS applications that launch fresh EC2 instances on an as-needed basis. While the instances can be up and running in a matter of seconds, booting the operating system and the application can take considerable time. Also, caches and other memory-centric application components can take some time […]

When you make use of commercial, licensed software in the AWS Cloud using a BYOL (Bring Your Own License) strategy, you need to make sure that you stay within the provisions of the license, while also avoiding expensive over-provisioning. This can be a challenge when it is so easy to launch instances on demand whenever […]

As promised in Welcome to AWS re:Invent 2018, here’s a summary of the launches, previews, and pre-announcements from Andy Jassy’s keynote. I have included links to allow you to sign up for previews, as appropriate. (photo from AWS Community Hero Eric Hammond) Launches Here are the blog posts that we wrote for today’s launches: Amazon […]

Machine learning (ML) is split in two distinct phases: training and inference. Training deals with building the model, i.e. running a ML algorithm on a dataset in order to identify meaningful patterns. This often requires large amounts of storage and computing power, making the cloud a natural place to train ML jobs with services such […]

The capacity to foresee the future would be an incredible superpower. At AWS, we can’t give you that, but we can help you use machine learning to forecast time series in a few steps. The goal of time series forecasting is to predict future values of time-dependent data such as weekly sales, daily inventory levels, […]

Machine learning definitely offers a wide range of exciting topics to work on, but there’s nothing quite like personalization and recommendation. At first glance, matching users to items that they may like sounds like a simple problem. However, the task of developing an efficient recommender system is challenging. Years ago, Netflix even ran a movie […]

Reinforcement Learning is a type of machine learning that works when an “agent” is allowed to act on a trial-and-error basis within an interactive environment, using feedback from those actions to learn over time in order to reach a predetermined goal or to maximize some type of score or reward. This stands in contrast to […]