Amazon SageMaker HyperPod now supports network topology configuration at the partition level for Slurm orchestrated clusters. A single cluster can now run tree topology in one partition and block topology in another, with each partition using the topology best suited to its instance types. This improves distributed training performance by keeping job placement aligned with the interconnect characteristics of each instance type, so GPU-to-GPU communication is faster, NCCL collective operations are more efficient, and training throughput improves.

HyperPod determines the topology for each partition based on the instance types of its compute instance groups. Partitions with Amazon EC2 UltraServer instance types such as ml.p6e-gb200.36xlarge use block topology, and those with hierarchical-interconnect instance types such as ml.p5.48xlarge, ml.p5e.48xlarge, and ml.p5en.48xlarge use tree topology, while partitions with instance types that don’t provide network topology information remain fully schedulable. HyperPod maintains this configuration automatically as the cluster changes through scale-up, scale-down, and node replacement events, so each partition’s topology always reflects the current state of the cluster.

To get started, create or update a SageMaker HyperPod Slurm cluster running Slurm 25.11 or later with supported GPU instance types. Topology-aware scheduling is enabled by default and requires no configuration. This feature is available in all AWS Regions where Amazon SageMaker HyperPod is supported. To learn more, see Using topology-aware scheduling in Amazon SageMaker HyperPod.

 

​Amazon SageMaker HyperPod now supports network topology configuration at the partition level for Slurm orchestrated clusters. A single cluster can now run tree topology in one partition and block topology in another, with each partition using the topology best suited to its instance types. This improves distributed training performance by keeping job placement aligned with the interconnect characteristics of each instance type, so GPU-to-GPU communication is faster, NCCL collective operations are more efficient, and training throughput improves. HyperPod determines the topology for each partition based on the instance types of its compute instance groups. Partitions with Amazon EC2 UltraServer instance types such as ml.p6e-gb200.36xlarge use block topology, and those with hierarchical-interconnect instance types such as ml.p5.48xlarge, ml.p5e.48xlarge, and ml.p5en.48xlarge use tree topology, while partitions with instance types that don’t provide network topology information remain fully schedulable. HyperPod maintains this configuration automatically as the cluster changes through scale-up, scale-down, and node replacement events, so each partition’s topology always reflects the current state of the cluster. To get started, create or update a SageMaker HyperPod Slurm cluster running Slurm 25.11 or later with supported GPU instance types. Topology-aware scheduling is enabled by default and requires no configuration. This feature is available in all AWS Regions where Amazon SageMaker HyperPod is supported. To learn more, see Using topology-aware scheduling in Amazon SageMaker HyperPod.  

Amazon OpenSearch Service now supports one-click migration from legacy OpenSearch Dashboards to OpenSearch UI, for both OpenSearch domains and serverless collections. OpenSearch UI is the new, zero-downtime, serverless interface for search and unified observability across multiple data sources. With this launch, the multiple tenants and thousands of saved objects you created in legacy OpenSearch Dashboards become reusable in your OpenSearch UI applications, reducing the operational complexity of moving between interfaces.

With one-click migration, you can move your existing tenants and saved objects into OpenSearch UI workspaces without recreating them manually. The mechanism works for OpenSearch Dashboards created under Amazon OpenSearch Service domains and serverless collections. You can migrate everything into a new workspace or into an existing one. If you have created multiple tenants in your OpenSearch Dashboard, you have the option to either convert them into a single workspace or keep them separate for different teams.  

This feature is available in all AWS Regions where OpenSearch UI is available. To get started, see Using OpenSearch UI in the Amazon OpenSearch Service Developer Guide. Visit the OpenSearch UI Help page for detailed feature tutorials. To learn more about the service, see the Amazon OpenSearch Service product page.

 

​Amazon OpenSearch Service now supports one-click migration from legacy OpenSearch Dashboards to OpenSearch UI, for both OpenSearch domains and serverless collections. OpenSearch UI is the new, zero-downtime, serverless interface for search and unified observability across multiple data sources. With this launch, the multiple tenants and thousands of saved objects you created in legacy OpenSearch Dashboards become reusable in your OpenSearch UI applications, reducing the operational complexity of moving between interfaces.
With one-click migration, you can move your existing tenants and saved objects into OpenSearch UI workspaces without recreating them manually. The mechanism works for OpenSearch Dashboards created under Amazon OpenSearch Service domains and serverless collections. You can migrate everything into a new workspace or into an existing one. If you have created multiple tenants in your OpenSearch Dashboard, you have the option to either convert them into a single workspace or keep them separate for different teams.  
This feature is available in all AWS Regions where OpenSearch UI is available. To get started, see Using OpenSearch UI in the Amazon OpenSearch Service Developer Guide. Visit the OpenSearch UI Help page for detailed feature tutorials. To learn more about the service, see the Amazon OpenSearch Service product page.  

Today, AWS Billing and Cost Management (BCM) announces support for Cost Efficiency widget in BCM Dashboards. You can now view cost efficiency trends alongside Cost Explorer, Budgets, and reports for Savings Plans and Reserved Instance coverage and utilization reports. This provides a unified view of your spending, commitments, and optimization performance in a single, tailored dashboard.

The Cost Efficiency widget displays your efficiency score over time, showing how your efficiency across your AWS environment changes over time. You can view efficiency by AWS account, region, or overall, and adjust granularity to analyze trends at the level that matters most to your team. By adding one or more Cost Efficiency widget to a BCM Dashboard, you can monitor your optimization performance from your existing cost management workflows. The widget links directly to the Cost Optimization Hub console so you can easily take actions when you have recommendations for savings opportunities.

With the Cost Efficiency widget, you can create a unified view of your spending, commitments, budgets, and optimization performance. The widget is fully integrated with dashboard exports and can be included in scheduled email reports or downloaded as a CSV or PDF for offline analysis. They are also included with cross-account dashboard sharing.

The Cost Efficiency widget for BCM Dashboards is available in all AWS commercial Regions at no additional charge. To learn more, visit our User Guide.

 

​Today, AWS Billing and Cost Management (BCM) announces support for Cost Efficiency widget in BCM Dashboards. You can now view cost efficiency trends alongside Cost Explorer, Budgets, and reports for Savings Plans and Reserved Instance coverage and utilization reports. This provides a unified view of your spending, commitments, and optimization performance in a single, tailored dashboard.
The Cost Efficiency widget displays your efficiency score over time, showing how your efficiency across your AWS environment changes over time. You can view efficiency by AWS account, region, or overall, and adjust granularity to analyze trends at the level that matters most to your team. By adding one or more Cost Efficiency widget to a BCM Dashboard, you can monitor your optimization performance from your existing cost management workflows. The widget links directly to the Cost Optimization Hub console so you can easily take actions when you have recommendations for savings opportunities.
With the Cost Efficiency widget, you can create a unified view of your spending, commitments, budgets, and optimization performance. The widget is fully integrated with dashboard exports and can be included in scheduled email reports or downloaded as a CSV or PDF for offline analysis. They are also included with cross-account dashboard sharing.
The Cost Efficiency widget for BCM Dashboards is available in all AWS commercial Regions at no additional charge. To learn more, visit our User Guide.  

Amazon Managed Grafana is now a FedRAMP High authorized service in the AWS GovCloud (US-East) and AWS GovCloud (US-West) regions. Federal agencies, public sector organizations, and other enterprises with FedRAMP High compliance requirements can now use Amazon Managed Grafana to visualize, query, and alert on operational metrics across their AWS and hybrid environments while meeting their strict security and compliance requirements.

Amazon Managed Grafana is a fully managed service based on open-source Grafana that makes it easier for you to visualize and analyze your operational data at scale. The Federal Risk and Authorization Management Program (FedRAMP) is a US government-wide program that delivers a standard approach to the security assessment, authorization, and continuous monitoring for cloud products and services. 

For more details about Amazon Managed Grafana in AWS GovCloud (US), visit the Amazon Managed Grafana GovCloud documentation or contact your AWS account team for more information. To learn more, visit the Amazon Managed Grafana product page.

 

​Amazon Managed Grafana is now a FedRAMP High authorized service in the AWS GovCloud (US-East) and AWS GovCloud (US-West) regions. Federal agencies, public sector organizations, and other enterprises with FedRAMP High compliance requirements can now use Amazon Managed Grafana to visualize, query, and alert on operational metrics across their AWS and hybrid environments while meeting their strict security and compliance requirements.
Amazon Managed Grafana is a fully managed service based on open-source Grafana that makes it easier for you to visualize and analyze your operational data at scale. The Federal Risk and Authorization Management Program (FedRAMP) is a US government-wide program that delivers a standard approach to the security assessment, authorization, and continuous monitoring for cloud products and services. 
For more details about Amazon Managed Grafana in AWS GovCloud (US), visit the Amazon Managed Grafana GovCloud documentation or contact your AWS account team for more information. To learn more, visit the Amazon Managed Grafana product page.  

Customers can now view annual water withdrawals data associated with their AWS workloads in AWS Sustainability, alongside existing carbon emissions data. This enhancement helps organizations gain comprehensive visibility into their environmental impact across carbon and water.

Water withdrawals data is available by AWS Region, service, and AWS account on an annual basis through the AWS Sustainability console and API. The data represents the total volume of water withdrawn for data center operations, with efficiency improvements reflected as lower withdrawal volumes.

AWS Sustainability water withdrawals data is available at no additional charge in all AWS Regions where the service is available.

To get started visit the AWS Sustainability user guide. For more information, see the AWS Sustainability console page.

 

​Customers can now view annual water withdrawals data associated with their AWS workloads in AWS Sustainability, alongside existing carbon emissions data. This enhancement helps organizations gain comprehensive visibility into their environmental impact across carbon and water.
Water withdrawals data is available by AWS Region, service, and AWS account on an annual basis through the AWS Sustainability console and API. The data represents the total volume of water withdrawn for data center operations, with efficiency improvements reflected as lower withdrawal volumes.
AWS Sustainability water withdrawals data is available at no additional charge in all AWS Regions where the service is available.
To get started visit the AWS Sustainability user guide. For more information, see the AWS Sustainability console page.  

Amazon RDS for PostgreSQL 19 Beta 2 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 19 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 19 Beta 2 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database.

PostgreSQL 19 introduces parallel autovacuum with configurable worker limits, so routine maintenance no longer bottlenecks large databases. The new REPACK CONCURRENTLY command rebuilds tables and reclaims storage online, keeping production databases accessible without third-party extensions. Native SQL Property Graph Queries (SQL/PGQ) let you express relationship traversals directly in standard SQL, eliminating separate application logic. Logical replication now synchronizes sequence values automatically and can be enabled dynamically without a server restart, reducing planned downtime. Beta 2 adds bug fixes and stability improvements from the Beta 1 testing period, including refinements to parallel autovacuum worker coordination and REPACK CONCURRENTLY lock handling. Please refer to PostgreSQL community announcement for more details.

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. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment.

Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.

 

​Amazon RDS for PostgreSQL 19 Beta 2 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 19 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 19 Beta 2 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database. PostgreSQL 19 introduces parallel autovacuum with configurable worker limits, so routine maintenance no longer bottlenecks large databases. The new REPACK CONCURRENTLY command rebuilds tables and reclaims storage online, keeping production databases accessible without third-party extensions. Native SQL Property Graph Queries (SQL/PGQ) let you express relationship traversals directly in standard SQL, eliminating separate application logic. Logical replication now synchronizes sequence values automatically and can be enabled dynamically without a server restart, reducing planned downtime. Beta 2 adds bug fixes and stability improvements from the Beta 1 testing period, including refinements to parallel autovacuum worker coordination and REPACK CONCURRENTLY lock handling. Please refer to PostgreSQL community announcement for more details. 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. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment. Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.  

Amazon Redshift announces the general availability of two new RG instance sizes – rg.large and rg.12xlarge. These new sizes deliver the same Graviton-powered performance benefits as existing RG instances, including up to 2.4x faster query performance than previous-generation RA3 instances at 30% lower price per vCPU, giving you more flexibility to right-size your provisioned clusters for any workload.

rg.large and rg.12xlarge instance sizes are available on the current track (P202) only. Customers on the trailing track (P201) can continue to use rg.xlarge and rg.4xlarge. Existing RA3 clusters can migrate to RG instances using Snapshot and Restore, Elastic Resize, or Classic Resize. RG instances are available with flexible pricing options, including On-Demand, and 1-year and 3-year Reserved Instances with No Upfront payment.

The new rg.large and rg.12xlarge instance sizes are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), Mexico (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Thailand), and Asia Pacific (Melbourne).

To get started, refer to the following resources:

• Amazon Redshift node types
• RA3 to RG upgrade guide
• Amazon Redshift cluster versions
• Amazon Redshift pricing

 

​Amazon Redshift announces the general availability of two new RG instance sizes – rg.large and rg.12xlarge. These new sizes deliver the same Graviton-powered performance benefits as existing RG instances, including up to 2.4x faster query performance than previous-generation RA3 instances at 30% lower price per vCPU, giving you more flexibility to right-size your provisioned clusters for any workload. rg.large and rg.12xlarge instance sizes are available on the current track (P202) only. Customers on the trailing track (P201) can continue to use rg.xlarge and rg.4xlarge. Existing RA3 clusters can migrate to RG instances using Snapshot and Restore, Elastic Resize, or Classic Resize. RG instances are available with flexible pricing options, including On-Demand, and 1-year and 3-year Reserved Instances with No Upfront payment.
The new rg.large and rg.12xlarge instance sizes are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), Mexico (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Thailand), and Asia Pacific (Melbourne). To get started, refer to the following resources:

Amazon Redshift node types
RA3 to RG upgrade guide
Amazon Redshift cluster versions
Amazon Redshift pricing  

Amazon EC2 now surfaces the AWS Systems Manager (SSM) Parameter Store parameters associated with public AMIs directly in the AMI metadata. When you describe a public AMI, the response includes the associated public SSM parameter, making it easy to discover and reference in your configurations.

Previously, finding the SSM parameter associated with a public AMI required searching through SSM parameter namespaces manually. Now, when you describe a public AMI, the response includes the public SSM parameter it is associated with. This allows you to discover the SSM parameter for a public AMI easily and use it as an alias that always resolves to the latest version, simplifying AMI updates across your infrastructure.

This capability is available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions. To learn more, please visit the documentation.

 

​Amazon EC2 now surfaces the AWS Systems Manager (SSM) Parameter Store parameters associated with public AMIs directly in the AMI metadata. When you describe a public AMI, the response includes the associated public SSM parameter, making it easy to discover and reference in your configurations.
Previously, finding the SSM parameter associated with a public AMI required searching through SSM parameter namespaces manually. Now, when you describe a public AMI, the response includes the public SSM parameter it is associated with. This allows you to discover the SSM parameter for a public AMI easily and use it as an alias that always resolves to the latest version, simplifying AMI updates across your infrastructure. This capability is available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions. To learn more, please visit the documentation.  

Amazon S3 Event Notifications now include system-generated tags in events delivered to all destinations including Amazon EventBridge, Amazon SQS, Amazon SNS, and AWS Lambda. System-generated tags are metadata labels attached to your bucket by AWS services. You can use these tags to filter events from thousands of buckets with a single EventBridge rule, instead of listing each bucket name individually.

To get started, enable S3 Event Notifications on your general purpose buckets through the AWS Management Console, AWS SDK, or AWS CLI. If AWS services like AWS CloudFormation have already applied system-generated tags to your buckets, S3 automatically includes them in new event notifications. System-generated tags in S3 Event Notifications are available at no additional cost in all AWS Regions and require no changes to existing configurations. To learn more, visit the S3 Event Notifications documentation.

 

​Amazon S3 Event Notifications now include system-generated tags in events delivered to all destinations including Amazon EventBridge, Amazon SQS, Amazon SNS, and AWS Lambda. System-generated tags are metadata labels attached to your bucket by AWS services. You can use these tags to filter events from thousands of buckets with a single EventBridge rule, instead of listing each bucket name individually. To get started, enable S3 Event Notifications on your general purpose buckets through the AWS Management Console, AWS SDK, or AWS CLI. If AWS services like AWS CloudFormation have already applied system-generated tags to your buckets, S3 automatically includes them in new event notifications. System-generated tags in S3 Event Notifications are available at no additional cost in all AWS Regions and require no changes to existing configurations. To learn more, visit the S3 Event Notifications documentation.  

Amazon EC2 High Memory U7in-24TB instances (u7in-24tb.224xlarge) are now available in AWS Europe (Paris) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7in-24TB instances offer 24 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i instances offer up to 45% better price performance over existing U-1 instances.

U7in-24TB instances deliver 896 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 200 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.

To learn more about U7i instances, visit the High Memory instances page.

 

​Amazon EC2 High Memory U7in-24TB instances (u7in-24tb.224xlarge) are now available in AWS Europe (Paris) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7in-24TB instances offer 24 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i instances offer up to 45% better price performance over existing U-1 instances.
U7in-24TB instances deliver 896 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 200 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.
To learn more about U7i instances, visit the High Memory instances page.