Amazon Personalize Optimizer Using Amazon Pinpoint Events is a solution that enables customers to create integrations between Amazon Personalize campaigns and Amazon Pinpoint projects. Customers can connect an Amazon Personalize campaign with an Amazon Pinpoint project directly from the Amazon Pinpoint console , then use this solution to build and maintain an automated data pipeline between Amazon Pinpoint and Amazon Personalize. The solution automatically provisions and configures the necessary AWS services to train and publish models quickly by defining the frequency and the type of data used to retrain the models. The result, more personalized recommendations are delivered over time.

AWS Batch now supports FSx for Lustre’s new options, a persistent storage and a second-generation scratch storage, both announced on Februrary 24 .  

AWS Security Hub today released updates and additions to AWS Security Finding Format (ASFF) that enable integrated Security Hub partners to send richer, more detailed findings to Security Hub. We have added a new Severity.Label field that is intended to replace the Severity.Normalized field. Severity.Label allows for informational, low, medium, high, and critical values, and each finding provider will select the appropriate value for their finding. If a finding is missing the Severity.Label field, Security Hub will automatically populate it based on the existing Severity.Normalized field. We are also updating how we track the status of the investigation into a finding. The existing WorkflowState field is deprecated. We have added a new Workflow object to contain information about the investigation workflow. It currently contains a single field, Status, which replaces the deprecated WorkflowState. Next, we have added new fields to the AwsS3Bucket resource details and added a new AwsS3Object resource type and corresponding details object. Finally, we added the following new resource types. These resource types do not yet have a corresponding details objects: AwsApiGatewayMethod, AwsApiGatewayRestApi, AwsAppStreamFleet, AwsCertificateManagerCertificate, AwsCloudFormationStack, AwsCloudWatchAlarm, AwsCodeCommitRepository, AwsCodeDeployApplication, AwsCodeDeployDeploymentGroup, AwsCodePipelinePipeline, AwsCognitoIdentityPool, AwsCognitoUserPool, AwsEcsService, AwsEcsTaskDefinition, AwsEfsFileSystem, AwsEksCluster, AwsElastiCacheCacheCluster, AwsElbLoadBalancer, AwsEmrCluster, AwsKinesisStream, and AwsLogsLogGroup.

AWS AppConfig now supports Amazon S3 as a source to store and retrieve application configurations. This option enables AWS customers who use S3 to store application configurations to on-board seamlessly with AWS AppConfig by specifying the URI of the configuration stored in their S3 bucket.

You can now use AWS Resource Access Manager (RAM) in the Middle East (Bahrain) Region.

Amazon Elasticsearch Service now supports open source Elasticsearch 7.4 and its corresponding version of Kibana. This minor release includes bug fixes and enhancements. 

You can now run your container applications on AWS Elastic Beanstalk using Docker on Amazon Linux 2 beta platform. The Docker on Amazon Linux 2 beta platform comes with several enhancements in the compiler tool chain, and the Amazon Linux 2 operating system.  

Amazon API Gateway announced the general availability of HTTP APIs, enabling customers to easily build high performance RESTful APIs that offer up to 71% cost savings and 60% latency reduction compared to REST APIs available from API Gateway. As part of this launch, customers will be able to take advantage of several new features including the ability the route requests to private AWS Elastic Load Balancers (ELB), including new support for AWS ALB, and IP-based services registered in AWS CloudMap. 

You can now assign tags to Amazon Lex bots, aliases and channel associations. Tags allow you to categorize your resources in different ways, such as by cost center or owner, which simplifies cost allocation in your organization. You can also use tags to control creation, modification or deletion of tagged resources. 

Starting today, Amazon Redshift supports materialized views functionality. Materialized views provide significantly faster query performance for repeated and predictable analytical workloads such as dashboarding, queries from business intelligence (BI) tools, and ELT (Extract, Load, Transform) data processing.