We are thrilled to announce that we have also released another requested feature – improved CloudFormation support. With this update, you can leverage improved CloudFormation support to quickly take resources from development into production, or replicate existing configurations into new regions. Check out the documentation for more details.

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 prior no machine learning experience.  

AWS AppSync is a managed GraphQL service that simplifies application development by letting you create a flexible API to securely access, manipulate, and combine data from one or more data sources. AppSync allows you to easily make any of its supported data sources real time, with connection management handled automatically between the client and the service. With today’s launch we’re releasing enhancements to AppSync that will further optimize access to applications requiring real-time updates, such as gaming leaderboards, social media apps, sports scores, live streaming, interactive chatrooms, IoT dashboards, and many others, by enabling a new protocol option with support to metrics and larger payloads.

Amazon GuardDuty customers can now export findings to Amazon S3 using the GuardDuty management console and API. With findings export, aggregating findings from across regions is simplified. When configured from the GuardDuty master account, customers can export findings from all associated member accounts and all AWS regions to a single customer owned S3 bucket. The S3 bucket used can be in the same account in which GuardDuty is enabled, or in a different AWS account. Once Findings export is configured in each Region, Amazon GuardDuty findings are automatically exported from GuardDuty to the configured Amazon S3 bucket. This feature enhancement gives customers a simplified way to aggregate all findings to a single customer owned Amazon S3 bucket across all accounts and regions for integration with other AWS services, third-party applications, or for long-term retention.  

Amazon EMR release 5.28.0 now supports Apache Hudi (Incubating). Data engineers using Amazon EMR for data pipeline development and data processing can now use Apache Hudi to simplify incremental data management and data privacy use cases requiring record-level insert, updates, and delete operations. Apache Hudi enables Amazon S3-based data lakes to comply with data privacy laws, consume real time streams and change data capture logs, reinstate late arriving data, and track change history and rollback. Apache Hudi is open-source and supports storing data on Amazon S3 in vendor neutral, open source formats such as Apache Parquet and Apache Avro.

AWS App Mesh has increased the default limits for a set of App Mesh resources – virtual nodes, backends, routers, and routes. These limit increases make it easier for you to manage larger applications with App Mesh. The number of virtual nodes per mesh, which map to your services, tasksets, or deployments that can be connected to the mesh, increased from 20 to 200. The number of backends per node; the number of dependent services that a specific service can connect with, increased from 25 to 50. The number of virtual routers per mesh increased from 20 to 200, to enable routing on all mesh connected services. The number of routes per virtual router increased from 20 to 50, to enable matching on multiple parameters for routing decisions.  

Today, AWS Systems Manager Parameter Store launched enhanced search capability to enable you to search for parameters easily by parameter name. The new search experience enables easy discovery of parameters when you have large number of parameters in your account or when you do not remember the exact name of a parameter.  

Elastic Fabric Adapter (EFA) is now compatible with Intel® MPI Library 2019 Update 6. Intel® MPI Library is a multi-fabric message passing library that implements the Message Passing Interface (MPI). Customers can use the library to create, maintain, and test applications that perform better on HPC clusters based on Intel® processors.

Amazon Redshift now offers a new console for Redshift users. The new user interface and new features simplify management and improve insights into the health and performance of your Redshift clusters and workloads .

Amazon DynamoDB adaptive capacity now handles imbalanced workloads better by isolating frequently accessed items automatically. If your application drives disproportionately high traffic to one or more items, DynamoDB will rebalance your partitions such that frequently accessed items do not reside on the same partition. This latest enhancement helps you maintain uninterrupted performance for your workloads. In addition, it helps you reduce costs by enabling you to provision throughput capacity more efficiently, instead of overprovisioning to accommodate uneven data access patterns.