Relevant News - Amazon SageMaker

Link: https://aws.amazon.com/about-aws/whats-new/2026/03/amazon-sagemaker-unified-studio-kiro-ide/

Today, AWS announces the ability to remotely connect from Kiro IDE to Amazon SageMaker Unified Studio. This new capability allows data scientists, ML engineers, and developers to leverage their Kiro setup - including its spec-driven development, conversational coding, and automated feature generation capabilities - while accessing the scalable compute resources of Amazon SageMaker. By connecting Kiro to SageMaker Unified Studio using the AWS toolkit extension, you can eliminate context switching between your local IDE and cloud infrastructure, maintaining your existing agentic development workflows within a single environment for all your AWS analytics and AI/ML services.

SageMaker Unified Studio, part of the next generation of Amazon SageMaker, offers a broad set of fully managed cloud interactive development environments (IDE), including JupyterLab and Code Editor based on Code-OSS (Open-Source Software). Starting today, you can also use your customized local Kiro setup - complete with specs, steering files, and hooks - while accessing your compute resources and data on Amazon SageMaker. Since Kiro is built on Code-OSS, authentication is secure via IAM through the AWS Toolkit extension, giving you access to all your SageMaker Unified Studio domains and projects. This integration provides a convenient path from your local AI-powered development environment to scalable infrastructure for running workloads across data processing, SQL analytics services like Amazon EMR, AWS Glue, and Amazon Athena, and ML workflows - all with enterprise-grade security including customer-managed encryption keys and AWS IAM integration.

This feature is available in all Regions where Amazon SageMaker Unified Studio is available. To learn more, refer to the SageMaker user guide.

Published: 2026-03-03 19:39:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/rds-exports-s3-available-gov-cloud/

Amazon RDS Snapshot Export to S3 is now available in AWS GovCloud (US) regions, enabling you to export snapshot data in Apache Parquet format for analytics, data retention, and machine learning use cases.

Snapshot export to S3 supports all DB snapshot types (manual, automated system, and AWS Backup snapshots) and runs directly on the snapshot without impacting database performance. The exported data in Apache Parquet format can be analyzed using other AWS services such as Amazon Athena, Amazon SageMaker, or Amazon Redshift Spectrum, or with big data processing frameworks such as Apache Spark.

You can create a snapshot export with just a few clicks in the Amazon RDS Management Console or by using the AWS SDK or CLI. Snapshot Export to S3 is supported for Amazon Aurora PostgreSQL - Compatible Edition and Amazon Aurora MySQL, Amazon RDS for PostgreSQL, Amazon RDS for MySQL, and Amazon RDS for MariaDB snapshots. For more information, including instructions on getting started, read Aurora documentation or Amazon RDS documentation.

Published: 2026-02-24 18:26:00+00:00

Link: https://aws.amazon.com/blogs/aws/announcing-amazon-sagemaker-inference-for-custom-amazon-nova-models/

AWS launches Amazon SageMaker Inference for custom Amazon Nova models. You can now configure the instance types, auto-scaling policies, and concurrency settings for custom Nova model deployments to best meet their needs.

Published: 2026-02-16 21:25:23+00:00

Link: https://aws.amazon.com/blogs/aws/aws-weekly-roundup-amazon-bedrock-agent-workflows-amazon-sagemaker-private-connectivity-and-more-february-2-2026/

Over the past week, we passed Laba festival, a traditional marker in the Chinese calendar that signals the final stretch leading up to the Lunar New Year. For many in China, it’s a moment associated with reflection and preparation, wrapping up what the year has carried, and turning attention toward what lies ahead. Looking forward, […]

Published: 2026-02-02 17:19:48+00:00