Amazon Fraud Detector now provides customers with a simple and effective way to align their business use cases with Amazon Fraud Detector data models. Amazon Fraud Detector is a fully managed service enabling customers to identify potentially fraudulent activities and catch more online fraud faster.

You can now deploy Amazon AppStream 2.0 in the AWS South America (São Paulo) Region. Deploying AppStream 2.0 in your local region provides users with a more responsive experience and helps support your local data residency obligations. With this launch, you can deploy General Purpose, Compute Optimized, Memory Optimized, and Graphics G4DN instances to meet the needs of your users.

AWS Copilot now supports Amazon Elastic Container Service (Amazon ECS) Service Connect, a capability that simplifies building and operating resilient distributed applications. Service Connect enables you to have easier network setup and seamless communication between sevices deployed across multiple Amazon ECS clusters and virtual private clouds (VPCs). Service Connect enables you to add a layer of resilience to your Amazon ECS service communication and get traffic insights with no changes to your application code. 

Today, Amazon SageMaker Feature Store is announcing SageMaker Python SDK support for its offline store. Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, update, search, and share machine learning (ML) features. SageMaker Feature Store offline store contains historical ML features, and you can use it to generate training data sets for training and batch inference. Until today, you had to use Athena and Glue and write ad hoc SQL queries to create these training datasets. 

You can now use the newly re-designed Amazon EMR console. Amazon EMR is the cloud big data solution for petabyte-scale data processing, interactive analytics, and machine learning using open-source frameworks such as Apache Spark, Apache Hive, and Presto. The new re-designed console introduces a new simplified experience to launch and manage clusters running big data processing workloads.

We are excited to announce that Amazon Personalize has extended limits to support datasets with up to 100 million users and 3 billion interactions. Amazon Personalize enables developers to improve customer engagement through personalized product and content recommendations – no ML expertise required. Amazon Personalize trains custom models for each customer using their unique data. Previously, these models could consider up to 50 million users in training. By doubling this limit, Amazon Personalize improves model performance for large customers by allowing them to train on a more diverse set of data. For customers with larger user bases that may exceed this limit, Amazon Personalize samples an optimal set of users before training. Previously, models trained by Amazon Personalize would also consider a maximum of 500 million of the latest interactions between users and items. Customers now have the option to increase their training time to consider up to 3 billion interactions. This can improve model performance by capturing more historical data for customers with a large user base or a high velocity of interactions. To increase the number of interactions considered by your model, simply request a service quota increase via the Service Quota console.

AWS Partners and consulting firms can now create an AWS IQ profile for their company and connect with AWS customers. Customers can message the Partner directly and connect to receive immediate help. Partners can choose to respond as a company or as an individual who works for the company when engaging with customers. Any Partner can set up a public profile showcasing their expertise, solutions, employee profiles, ratings, and reviews.

Amazon Elastic Container Service (Amazon ECS) now enables you to configure port ranges for your container as part of the port mapping. Port mappings (specified in the container definition) allow containers to access ports on the host container instance to send or receive traffic. In addition to individual ports, Amazon ECS now allows your application to access an entire range of ports that you select by opening these ports on the container for you, and binding them to ports on the host. This makes it easier for you to run applications such as game servers and real-time streaming which typically require multiple ports to be opened simultaneously on the container.

Starting today, the general-purpose Amazon EC2 M6a instances and compute-optimized Amazon EC2 C6a instances are now available in US West (N. California), Asia Pacific (Singapore, Sydney, Tokyo), and Europe (London) regions. M6a and C6a instances are powered by third-generation AMD EPYC processors with an all-core turbo frequency of up to 3.6 GHz. M6a instances deliver up to 35% better price performance than comparable M5a instances, while C6a instances deliver up to 15% better price performance than comparable C5a instances. Both M6a and C6a instances offer 10% lower cost than comparable x86-based EC2 instances. These instances are built on the AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor that delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security.

We’re excited to announce availability of AWS IoT Core and AWS IoT Device Management in the AWS Middle East (UAE) Region. The AWS Middle East (UAE) Region is the second Region in the Middle East, in addition to the Middle East (Bahrain) Region.