Amazon Cognito is now available in the Middle East (Bahrain) Region. Amazon Cognito makes it easy to add authentication, authorization, and user management to your web and mobile apps. Amazon Cognito scales to millions of users and supports sign-in with social identity providers such as Apple, Facebook, Google, and Amazon, and enterprise identity providers via standards such as SAML 2.0 and OpenID Connect. 

Today, AWS announces the general availability of AWS Proton, the first fully managed delivery service for container and serverless applications. It is designed to provide platform teams the management tools, governance, and visibility needed to provide consistent standards and best practices when managing deployments, while helping to increase developer productivity and innovation.

Amazon AppFlow, a fully managed integration service that helps customers securely transfer data between AWS services and cloud applications expands its features with Veeva. Customers can now export documents from Veeva Vault into Amazon Simple Storage Service (Amazon S3). When choosing the document option for the Veeva connector in AppFlow, customers can choose to bring just the latest version (default) or all versions of documents, along with document metadata.

The latest query engine for Amazon Athena is generally available in all 24 AWS Regions where Athena is available. Customers who use Athena engine version 2 benefit from new features and performance enhancements that make analyzing data easier and more cost-effective than before. 

Amazon Managed Blockchain now supports customer-managed customer master keys (CMKs) for Hyperledger Fabric networks. Customers can encrypt new member-specific resources using their own CMK. These CMKs are declared in AWS Key Management Service (KMS) and used by Amazon Managed Blockchain. Each member can use their own CMK and manage it according to their security policy.

Starting today AWS Transit Gateway supports internet group management protocol (IGMP) multicast in the Africa (Cape Town), EU (Milan), Middle East (Bahrain), and Asia Pacific (Hong Kong) AWS Regions.

Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for machine learning (ML), now supports a new callback step that allows customers to integrate any task or job outside Amazon SageMaker as a step in the model building pipeline. When a callback step is invoked, the current execution of a SageMaker model building pipeline will pause and wait for an external task or job to return a task token that was generated by SageMaker at the start of call back step execution. You can use the call back step to include processing jobs external to SageMaker such a Spark job running on an Amazon EMR cluster or an extract-transform-load (ETL) task in AWS Glue as part of the SageMaker model building pipeline.

You can now launch NAT Gateways in your Amazon Virtual Private Cloud (VPC) without associating an internet gateway to your VPC. Internet Gateway is required to provide internet access to the NAT Gateway. However, some customers use their NAT Gateways with Transit Gateway or virtual private gateway to communicate privately with other VPCs or on-premises environments and thus, do not need an internet gateway attached to their VPCs.

By default, Amazon Cognito refresh tokens expire 30 days after a user signs in to a user pool. When you create an app, you can set the app’s refresh token expiration to any value between 60 minutes and 10 years. Amazon Cognito now enables you to revoke refresh tokens in real time so that those refresh tokens cannot be used to generate additional access tokens.

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, update, retrieve, and share machine learning (ML) features. Customers can retrieve features from SageMaker Feature Store at low millisecond latencies for real-time use-cases using the GetRecord API. This API allows customers to retrieve features from a single feature group and access one record per API call. Until now, to read multiple records at a time from SageMaker Feature Store, customers needed to call the GetRecord API multiple times and manage parallelization of the API calls to achieve lower latency, which increased operational complexity.