The AWS Serverless Application Model (SAM) Command Line Interface (CLI) announces the launch of remote invoke command which enables developers to quickly invoke their AWS Lambda functions deployed to the AWS cloud. The AWS SAM CLI is a developer tool that makes it easier to build, test, package, and deploy serverless applications.
Amazon SageMaker Neo now supports compilation of PyTorch and TensorFlow models for Inferentia 2 and Trainium 1 instances
Starting today, you can choose Inferentia 2 and Trainium 1 as additional targets to compile your PyTorch and TensorFlow models for Amazon SageMaker Neo, a capability of Amazon SageMaker that enables customers to optimize machine learning (ML) models for inference on SageMaker to achieve faster inference without any loss in accuracy. Amazon Elastic Compute Cloud (Amazon EC2) Inf2 instances deliver high performance at the lowest cost for generative artificial intelligence (AI) models, including large language models (LLMs) and vision transformers. AWS Trainium is a machine learning (ML) accelerator that AWS purpose built for deep learning training of 100B+ parameter models.
AWS Control Tower achieves FedRAMP High authorization in AWS GovCloud (US) Regions
Starting today, you can now use AWS Control Tower with workloads that require FedRAMP High categorization level in the AWS GovCloud (US-East and US-West) Regions.
Amazon Redshift announces native console integration with ThoughtSpot
Amazon Redshift, a fully-managed cloud data warehouse, now supports native integration with ThoughtSpot from the Amazon Redshift Console. Thoughtspot simplifies the exploration and analysis of data in a user friendly environment without the need for complex transformations or technical expertise.
Amazon SageMaker Data Wrangler now enables direct connection to Snowflake data
Amazon SageMaker Data Wrangler now enables direct connection to Snowflake to prepare data and create features for machine learning (ML). SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for ML from weeks to minutes using a visual interface in Amazon SageMaker Studio.
AWS Glue now supports native Snowflake connectivity with new ETL capabilities (preview)
AWS Glue for Spark now supports the Snowflake connector for Spark out-of-the-box with new ETL capabilities enabling users to preview Snowflake data, use Snowflake SQL queries as a source, and write to new or existing Snowflake tables. AWS Glue Studio offers a visual extract-transform-and-load (ETL) interface that helps ETL developers to author, run, and monitor AWS Glue ETL jobs quickly. With this new feature, ETL developers can read and write data into Snowflake more effectively using AWS Glue.
Amazon OpenSearch Ingestion now supports ingesting events from Amazon Security Lake
Amazon OpenSearch Ingestion now allows you to ingest events from Amazon Security Lake in real-time, reducing the time taken to index your security data in Amazon OpenSearch Service and uncover valuable insights into potential security issues. Amazon Security Lake automatically centralizes security data from AWS environments, SaaS providers and on- premises into a purpose-built data lake. With this integration, customers can now use the extensive security analytics capabilities and rich dashboard visualizations of Amazon OpenSearch Service to quickly make sense of all their security data.
Amazon SageMaker Role Manager now provides CDK library to create fine-grained permissions within minutes
Today, we are excited to announce the CDK library for Amazon SageMaker Role Manager. This CDK library allows you to define activity based fine-grained permissions in minutes.
Amazon Pinpoint journeys now supports time zone estimation for endpoints
Amazon Pinpoint journeys now offers organizations the ability to estimate local time zone and allows them to contact customers at convenient times. Journeys are customized, multi-step engagement experience to send customer communication across channels such as SMS, email, push notifications, and voice.
Amazon Connect now allows you to search for tags within an instance
Amazon Connect now provides the ability to search for existing tags within an instance, both programmatically via API and within the UI. When tagging resources, you can now search from pre-existing key:value pairs before creating new ones. For example, administrators can create a tag such as “Division:ConsumerCredit”, and users with permissions to tag resources within the same instance will be able to view and apply “Division:ConsumerCredit”, to save time and avoid mistakenly creating new variations of the intended tag such as “Division:CC” or “Div:ConsumerCredit”. To learn more about how to search for tags within an instance, see the Administrative Guide .