Amazon Personalize is a machine learning service which enables you to personalize your website, app, ads, emails, and more, with custom machine learning models which can be created in Amazon Personalize, with no prior machine learning experience. AWS is pleased to announce that Amazon Personalize now supports ten times more item attributes. Previously, you could use up to five item attributes while building an ML model in Amazon Personalize. This limit is now 50 attributes. You can now use more information about your items, for example, category, brand, price, duration, size, author, year of release etc., to increase the relevance of recommendations.

This Quick Start automatically deploys the Poly-integrated Amazon Connect Contact Control Panel (CCP) in the Amazon Web Services (AWS) Cloud in about 30 minutes. This Quick Start is for users who have already configured an Amazon Connect instance in their AWS account and want to enable support for Poly, which provides headset button call control. 

AWS RoboMaker, a service that makes it easy to develop, simulate, and deploy robotics applications, now supports creating simulation jobs in batch with a single API call. The new support for batch simulations allows developers to easily create multiple simulation jobs for use cases like automated regression testing and reinforcement learning model training. The batch API also provides a queueing capability so that a developer can now submit more simulation jobs than is possible with the existing concurrent job execution limit. The batch API will queue up all the submitted jobs and execute them in batches based on the concurrent execution limit.

You can now enable AWS X-Ray for your APIs in AWS AppSync, making it easier to trace and analyze user requests as they travel through the APIs to the backend data sources.

You can now use Amazon Elastic Filesystem (EFS) in AWS CodeBuild build jobs. This can be achieved by specifying the EFS file system Id in your CodeBuild Project . 

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads.  

Use the new Amazon CloudWatch metrics for Amazon DynamoDB Accelerator (DAX) to better understand your DAX clusters’ performance. Determine more easily whether you need to scale up your cluster because you’re reaching peak utilization, or if you can scale down because your cache is underutilized. 

Updates to your containers orchestrated by Amazon Elastic Container Service (Amazon ECS) can now be performed using canary or linear deployment strategies by using AWS CodeDeploy.

This Quick Start automatically deploys Provectus Streaming Data Platform in the Amazon Web Services (AWS) Cloud in about 20 minutes. This Quick Start is for users who are interested in enabling real-time analytics and want to explore capabilities of a streaming-first data platform.

You can now use the DescribeImages  API to determine the billing product information associated with an Amazon Machine Image (AMI). By making it easier to obtain the platform details and billing information of AMIs, this release reduces the chances of erroneously launching instances from incorrect AMIs, and assists with inventory planning and reporting. Starting today, this capability is available in all AWS commercial Regions and AWS GovCloud (US) Regions from API and CLI. Visit our documentation page to learn more.