AWS News Blog

Category: News

New for AWS Lambda – Use Any Programming Language and Share Common Components

I remember the excitement when AWS Lambda was announced in 2014! Four years on, customers are using Lambda functions for many different use cases. For example, iRobot is using AWS Lambda to provide compute services for their Roomba robotic vacuum cleaners, Fannie Mae to run Monte Carlo simulations for millions of mortgages, Bustle to serve billions of requests for their digital content. Today, […]

New – Compute, Database, Messaging, Analytics, and Machine Learning Integration for AWS Step Functions

AWS Step Functions is a fully managed workflow service for application developers. You can think & work at a high level, connecting and coordinating activities in a reliable and repeatable way, while keeping your business logic separate from your workflow logic. After you design and test your workflows (which we call state machines), you can […]

New – AWS Toolkits for PyCharm, IntelliJ (Preview), and Visual Studio Code (Preview)

Software developers have their own preferred tools. Some use powerful editors, others Integrated Development Environments (IDEs) that are tailored for specific languages and platforms. In 2014 I created my first AWS Lambda function using the editor in the Lambda console. Now, you can choose from a rich set of tools to build and deploy serverless applications. […]

New – Hibernate Your EC2 Instances

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 […]

AWS Launches, Previews, and Pre-Announcements at re:Invent 2018 – Andy Jassy Keynote

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 […]

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Amazon SageMaker Neo – Train Your Machine Learning Models Once, Run Them Anywhere

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 […]