Amazon SageMaker notebooks now support R out-of-the-box, without needing you to manually install R kernels on the instances. Also, the notebooks come pre-installed with the reticulate library that offers an R interface for the Amazon SageMaker Python SDK enabling you to invoke Python modules from within an R script.  

You can now define Identity and Access Management (IAM) policies to specify granular resource-level and tag-based user permission in CloudFront. These new features give you increased flexibility to manage access to your CloudFront distributions.

Previously, you could apply IAM policies to manage user actions in CloudFront, but you couldn’t restrict actions to specific distributions in your account. Now, with resource-level permissions, you can configure IAM policies that reference individual CloudFront distributions—using Amazon Resource Names (ARNs) or wildcards—and specify the users and actions that have permissions on only those distributions. Similarly, with tag-based access control, you can create IAM user policies that allow or deny actions on specific CloudFront distributions based on the tags associated with them.

To get started with this new functionality, see the CloudFront Developer Guide . To learn more about Amazon CloudFront, visit our product page .

Natural conversations are dynamic and often cover multiple topics. A user could start off with a request, digress to a related topic, and may eventually return to the original query. Previously, you could manage a dynamic conversation like this only on the server-side using Lambda functions. Today, we’re announcing new Amazon Lex Session APIs to manage a dynamic conversation on the client. You can define the dialog state, slot values, prompt messages, and attributes. With this granular control on the session, you can manage the conversation flow by performing operations such as switching to a different topic or continuing from a previous point in the conversation.

Amazon Aurora Multi-Master is now generally available, allowing you to create multiple read-write instances of your Aurora database across multiple Availability Zones, which enables uptime-sensitive applications to achieve continuous write availability through instance failure. In the event of instance or Availability Zone failures, Aurora Multi-Master enables the Aurora database to maintain read and write availability with zero application downtime. With Aurora Multi-Master, there is no need for database failovers to resume write operations. Check out this blog to find out how to build highly available MySQL applications using Aurora Multi-Master.

AWS IoT Device Defender now supports the ability for customers to apply mitigation actions to audit findings. This feature enables customers to use predefined mitigation actions or customize them and apply them at scale. With this release, customers can choose from the following set of predefined mitigation actions to automate a response to findings from an audit: add things to thing group, enable IoT logging, publish to SNS topic, replace default policy version, update CA certificate, and update device certificate. You can use mitigation actions by using the AWS IoT Console, AWS Command Line Interface (CLI) or APIs.

Starting today, Amazon RDS for Oracle db.m5 and db.r5 instance classes are available in new 8xlarge and 16xlarge sizes. With support for these new instance sizes, customers who are currently using either m4.10xlarge, m4.16xlarge, r4.8xlarge, or r4.16xlarge now have an easy upgrade path to the latest generation of instances. 

Amazon Redshift Concurrency Scaling is now available in five additional AWS Regions: Canada (Central), EU (Frankfurt), Asia Pacific (Sydney), Asia Pacific (Singapore), and Asia Pacific (Seoul). The Amazon Redshift Management Console presents performance graphs for monitoring Concurrency Scaling activity and associated performance gains related to query concurrency, throughput, latency, and queueing on your Amazon Redshift cluster.

Amazon DynamoDB now publishes account metrics to help you monitor capacity consumption against your account limits. You can now alarm as your capacity approaches your account limits and proactively request limit increases, helping ensure your DynamoDB tables are always available. These metrics are available in the AWS Management Console by navigating to the CloudWatch console , choosing Metrics, selecting DynamoDB, and finally Account Metrics, or via the AWS CLI . To learn more, see DynamoDB Metrics and Dimensions in the DynamoDB Developer Guide. 

Amazon RDS for SQL Server now supports changing the server-level collation when creating a new DB Instance. If the collation is not specified the default server-level collation will continue to be SQL_Latin1_General_CP1_CI_AS. To learn more about which collations are supported please visit the Amazon RDS for SQL Server User Guide . 

PostgreSQL 12 Beta 2 is now available in the Amazon RDS Database Preview Environment , allowing customers to test the beta version of PostgreSQL 12 on Amazon RDS .

PostgreSQL 12 Beta 2 can now be deployed for development and testing in the Amazon RDS Database Preview Environment without the hassle of installing, provisioning, and managing the database. The PostgreSQL community released PostgreSQL 12 Beta 2 on June 20, 2019. PostgreSQL 12 includes improved functionality, performance, management of indexing, improved partitioning capabilities, JSON path queries per SQL/JSON specifications, nondeterministic collations which support case-insensitive and accent-insensitive comparisons for ICU provided collations, most common-value statistics for improved query plans, creation of generated columns that computes values with an expression, pluggable table storage interface, ability to enable/disable page checksums, and many more.

The Amazon RDS Database Preview Environment supports both Single-AZ and Multi-AZ deployments on the latest generation of instance classes (currently T2, M4, and R4), and can be encrypted at rest using KMS keys. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. Customers can use standard PostgreSQL dump and load functionality to import or export their databases from the preview environment.

Amazon RDS Database Preview Environment database instances are priced the same as production RDS instances created in the US East (Ohio) Region .

The Amazon RDS Database Preview Environment Forum is available for customers and the Amazon RDS team to share information and concerns about both the candidate versions of PostgreSQL 12 and the Amazon RDS Database Preview Environment.