11/22/2022, 12:00:00 AM ~ 11/23/2022, 12:00:00 AM (UTC)

Recent Announcements

Amazon SageMaker Autopilot experiments run with Ensemble training mode provide additional metrics and visibility into the AutoML workflow

Amazon SageMaker Autopilot now provides insights into the underlying workflow for each trial within a SageMaker Autopilot experiment launched with ensemble training mode. SageMaker Autopilot ranks a list of machine learning (ML) models by inference latency i.e. the time one has to wait to get prediction result from a real time endpoint to which the model is deployed, and objective metrics such as accuracy, precision, recall, and area under the curve (AUC) in the model leaderboard. SageMaker Autopilot automatically builds, trains and tunes the best ML models based on your data, while allowing you to maintain full control and visibility.

Amazon EMR on EKS adds support for configuring Spark properties within EMR Studio Jupyter Notebooks

We are excited to announce support for configuring Spark properties within EMR Studio Jupyter Notebook sessions for interactive Spark workloads. Amazon EMR on EKS enables customers to efficiently run open-source big data frameworks such as Apache Spark on Amazon EKS. Amazon EMR on EKS customers setup and use a managed endpoint (available in preview) to run interactive workloads using integrated development environments (IDEs) such as EMR Studio.

AWS announces availability of Microsoft SQL Server 2022 images on Amazon EC2

Amazon EC2 adds support for managed Amazon Machine Images (AMIs) with SQL Server 2022. With these AMIs, you can easily launch SQL Server 2022 on EC2 and take advantage of the fully compliant SQL Server licenses with per-second billing model. The new AMIs are available for both Windows Server and Linux operating systems. In addition, you can use related AWS services such as AWS Launch Wizard and CloudWatch Application Insights to further simplify your SQL Server deployment and management experience on EC2.

AWS Control Tower now displays compliance status of external AWS Config rules

AWS Control Tower now displays the compliance status of AWS Config rules deployed outside of AWS Control Tower. This view provides you with visibility into the compliance status of externally applied AWS Config rules in addition to AWS Config rules set up by AWS Control Tower.

Amazon SNS adds support for payload-based message filtering

Amazon Simple Notification Service (Amazon SNS) now supports payload-based message filtering, expanding the feature set that already supported attribute-based message filtering. With this release, you can apply subscription filter policies to filter out messages based on their contents, unlocking a variety of workloads. You may use this new capability to filter events from 60+ AWS services that publish events to Amazon SNS, including Amazon S3, Amazon EC2, Amazon CloudFront, and Amazon CloudWatch. You may also use payload-based message filtering for your cross-account workloads, where subscribers may not be able to influence a given publisher to have its messages published with attributes to Amazon SNS.

Amazon Kinesis Data Analytics for Apache Flink now supports Apache Flink version 1.15

Amazon Kinesis Data Analytics for Apache Flink now supports Apache Flink version 1.15. This new version includes improvements to Flink’s exactly-once processing semantics, Kinesis Data Streams and Kinesis Data Firehose connectors, Python User Defined Functions, Flink SQL, and more. The release also includes an AWS-contributed capability, a new Async-Sink framework which simplifies the creation of custom sinks to deliver processed data. For a complete list of features, improvements, and bug fixes please see the Apache Flink release notes for 1.15.

Announcing AWS Graviton2 support for Amazon EMR Serverless - Get up to 35% better price-performance for your serverless Spark and Hive workload

Amazon EMR Serverless is a serverless option in Amazon EMR that makes it simple to run applications using open-source analytics frameworks such as Apache Spark and Hive without configuring, managing, or scaling clusters.

Support for reading and writing data in Amazon DynamoDB and cross account Amazon S3 access with Amazon EMR Serverless

Amazon EMR Serverless announces support for reading and writing data in Amazon DynamoDB with your Spark and Hive workflows. You can now export, import, query and, join tables in Amazon DynamoDB directly from your EMR Serverless Spark and/or Hive applications. Amazon DynamoDB is a fully managed NoSQL database that meets the latency and throughput requirements of highly demanding applications by providing single-digit millisecond latency and predictable performance with seamless throughput and storage scalability.

Manage Table metadata in Glue Data Catalog when running Flink workloads on Amazon EMR

Amazon EMR customers can now use AWS Glue Data Catalog from their streaming and batch SQL workflows on Flink. The AWS Glue Data Catalog is an Apache Hive metastore-compatible catalog. You can configure your Flink jobs on Amazon EMR to use the Data Catalog as an external Apache Hive metastore. With this release, You can then directly run Flink SQL queries against the tables stored in the Data Catalog.

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