Customers can now enable predictive scaling for their Auto Scaling groups (ASGs) in six more regions: Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Israel (Tel Aviv), Canada West (Calgary), Europe (Spain), and Europe (Zurich). Predictive Scaling can proactively scale out your ASGs to be ready for upcoming demand. This allows you to avoid the need to over-provision capacity, resulting in lower EC2 cost, while ensuring your application’s responsiveness. To see the list of all supported AWS public regions and AWS GovCloud (US) regions, click here.

Predictive Scaling is appropriate for applications that experience recurring patterns of steep demand changes, such as early morning spikes when business resumes. It learns from the past patterns and launches instances in advance of predicted demand, giving instances time to warm up. Predictive scaling enhances existing Auto Scaling policies, such as Target Tracking or Simple Scaling, so that your applications scale based on both real-time metrics and historic patterns. You can preview how Predictive Scaling works with your ASG by using the “Forecast Only” mode.

Predictive Scaling is available as a scaling policy type through AWS Command Line Interface (CLI), EC2 Auto Scaling Management Console, AWS CloudFormation and AWS SDKs. To learn more, visit the Predictive Scaling page in the EC2 Auto Scaling documentation.

 

​Customers can now enable predictive scaling for their Auto Scaling groups (ASGs) in six more regions: Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Israel (Tel Aviv), Canada West (Calgary), Europe (Spain), and Europe (Zurich). Predictive Scaling can proactively scale out your ASGs to be ready for upcoming demand. This allows you to avoid the need to over-provision capacity, resulting in lower EC2 cost, while ensuring your application’s responsiveness. To see the list of all supported AWS public regions and AWS GovCloud (US) regions, click here. Predictive Scaling is appropriate for applications that experience recurring patterns of steep demand changes, such as early morning spikes when business resumes. It learns from the past patterns and launches instances in advance of predicted demand, giving instances time to warm up. Predictive scaling enhances existing Auto Scaling policies, such as Target Tracking or Simple Scaling, so that your applications scale based on both real-time metrics and historic patterns. You can preview how Predictive Scaling works with your ASG by using the “Forecast Only” mode. Predictive Scaling is available as a scaling policy type through AWS Command Line Interface (CLI), EC2 Auto Scaling Management Console, AWS CloudFormation and AWS SDKs. To learn more, visit the Predictive Scaling page in the EC2 Auto Scaling documentation.  

Today, Amazon announced two new Amazon CloudWatch metrics that provide insight into when your application exceeds the I/O performance limits for your EC2 instance with attached EBS volumes. These two metrics, Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check, monitor if the driven IOPS or throughput is exceeding the maximum EBS IOPS or throughput that your instance can support.

With these two new metrics at the instance level, you can quickly identify and respond to application performance issues stemming from exceeding the EBS-Optimized limits of your instance. These metrics will return a value of 0 (performance not exceeded) or a 1 (performance exceeded) when your workload is exceeding the EBS-Optimized IOPS or throughput limit of the EC2 instance. With Amazon CloudWatch, you can use these new metrics to create customized dashboards and set alarms that notify you or automatically perform actions based on these metrics, such as moving to a larger instance size or a different instance type that supports higher EBS-Optimized limits.

The Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check metrics are available by default at a 1-minute frequency at no additional charges, for all Nitro-based Amazon EC2 instances with EBS volumes attached. You can access these metrics via the EC2 console, CLI, or CloudWatch API in all Commercial AWS Regions, including the AWS GovCloud (US) Regions and China Regions. To learn more about these CloudWatch metrics, please visit the EC2 CloudWatch Metrics documentation.

 

​Today, Amazon announced two new Amazon CloudWatch metrics that provide insight into when your application exceeds the I/O performance limits for your EC2 instance with attached EBS volumes. These two metrics, Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check, monitor if the driven IOPS or throughput is exceeding the maximum EBS IOPS or throughput that your instance can support. With these two new metrics at the instance level, you can quickly identify and respond to application performance issues stemming from exceeding the EBS-Optimized limits of your instance. These metrics will return a value of 0 (performance not exceeded) or a 1 (performance exceeded) when your workload is exceeding the EBS-Optimized IOPS or throughput limit of the EC2 instance. With Amazon CloudWatch, you can use these new metrics to create customized dashboards and set alarms that notify you or automatically perform actions based on these metrics, such as moving to a larger instance size or a different instance type that supports higher EBS-Optimized limits. The Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check metrics are available by default at a 1-minute frequency at no additional charges, for all Nitro-based Amazon EC2 instances with EBS volumes attached. You can access these metrics via the EC2 console, CLI, or CloudWatch API in all Commercial AWS Regions, including the AWS GovCloud (US) Regions and China Regions. To learn more about these CloudWatch metrics, please visit the EC2 CloudWatch Metrics documentation.  

Data engineers and data analysts using Amazon SageMaker Unified Studio can now connect to and run queries with pre-existing Amazon Athena workgroups. This feature enables data teams to run SQL queries in SageMaker Unified Studio with the default settings and properties from existing Athena workgroups. Since Athena workgroups are used to manage query access and control costs, data engineers and data analysts can save time by reusing Athena workgroups as their SQL analytics compute while maintaining data usage limits and tracking query usage by team or project.

When choosing a compute for SQL analytics within SageMaker Unified Studio, customers can create a new Athena compute connection or choose to connect to an existing Athena workgroup. To get started, navigate to SageMaker Unified Studio, select “Add compute” and choose “Connect to existing compute resources”. Then create a connection to your pre-existing Athena workgroups and save. This new compute is now available within the SageMaker Unified Studio query editor to run SQL queries.

Connecting to Athena workgroups within SageMaker Unified Studio is available in all regions where SageMaker Unified Studio is supported.

To learn more, refer to the SageMaker Unified Studio Guide and Athena Workgroups Guide.

 

​Data engineers and data analysts using Amazon SageMaker Unified Studio can now connect to and run queries with pre-existing Amazon Athena workgroups. This feature enables data teams to run SQL queries in SageMaker Unified Studio with the default settings and properties from existing Athena workgroups. Since Athena workgroups are used to manage query access and control costs, data engineers and data analysts can save time by reusing Athena workgroups as their SQL analytics compute while maintaining data usage limits and tracking query usage by team or project. When choosing a compute for SQL analytics within SageMaker Unified Studio, customers can create a new Athena compute connection or choose to connect to an existing Athena workgroup. To get started, navigate to SageMaker Unified Studio, select “Add compute” and choose “Connect to existing compute resources”. Then create a connection to your pre-existing Athena workgroups and save. This new compute is now available within the SageMaker Unified Studio query editor to run SQL queries. Connecting to Athena workgroups within SageMaker Unified Studio is available in all regions where SageMaker Unified Studio is supported. To learn more, refer to the SageMaker Unified Studio Guide and Athena Workgroups Guide.  

Amazon Aurora DSQL now supports resource-based policies, enabling you to simplify access control for your Aurora DSQL resources. With resource-based policies, you can specify Identity and Access Management (IAM) principals and the specific IAM actions they can perform against your Aurora DSQL resources. Resource-based policies also enable you to implement Block Public Access (BPA), which helps to further restrict access to your Aurora DSQL public or VPC endpoints.

Aurora DSQL support for resource-based policies is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Frankfurt). To get started, visit the Aurora DSQL resource-based policies documentation.

 

​Amazon Aurora DSQL now supports resource-based policies, enabling you to simplify access control for your Aurora DSQL resources. With resource-based policies, you can specify Identity and Access Management (IAM) principals and the specific IAM actions they can perform against your Aurora DSQL resources. Resource-based policies also enable you to implement Block Public Access (BPA), which helps to further restrict access to your Aurora DSQL public or VPC endpoints. Aurora DSQL support for resource-based policies is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Frankfurt). To get started, visit the Aurora DSQL resource-based policies documentation.  

Amazon Connect now provides granular permissions to access conversation recordings and transcripts in the UI, giving administrators greater flexibility and security control. Contact center administrators can now separately configure access to recordings and transcripts, allowing users to listen to calls while preventing unauthorized copying of transcripts. The system also provides flexible download controls, enabling users to download redacted recordings while restricting downloads of unredacted versions. Administrators can also create sophisticated permission scenarios, providing access to redacted recordings of sensitive conversations while granting unredacted recording access for other conversations.

This feature is available in all regions where Amazon Connect is offered. To learn more, please visit our documentation and our webpage. 

 

​Amazon Connect now provides granular permissions to access conversation recordings and transcripts in the UI, giving administrators greater flexibility and security control. Contact center administrators can now separately configure access to recordings and transcripts, allowing users to listen to calls while preventing unauthorized copying of transcripts. The system also provides flexible download controls, enabling users to download redacted recordings while restricting downloads of unredacted versions. Administrators can also create sophisticated permission scenarios, providing access to redacted recordings of sensitive conversations while granting unredacted recording access for other conversations. This feature is available in all regions where Amazon Connect is offered. To learn more, please visit our documentation and our webpage.   

Amazon DynamoDB zero-ETL integration with Amazon Redshift is now supported in the Asia Pacific (Taipei) region. This expansion enables customers to run high-performance analytics on their DynamoDB data in Amazon Redshift with no impact on production workloads running on DynamoDB. 

Zero-ETL integrations help you derive holistic insights across many applications, break data silos in your organization, and gain significant cost savings and operational efficiencies. Now you can run enhanced analysis on your DynamoDB data with the rich capabilities of Amazon Redshift, such as high performance SQL, built-in ML and Spark integrations, materialized views with automatic and incremental refresh, and data sharing. Additionally, you can use history mode to easily run advanced analytics on historical data, build lookback reports, and build Type 2 Slowly Changing Dimension (SCD 2) tables on your historical data from DynamoDB, out-of-the-box in Amazon Redshift, without writing any code.

The Amazon DynamoDB zero-ETL integration with Amazon Redshift is now available in Asia Pacific (Taipei), in addition to previously supported regions. For a complete list of supported regions, please refer to the AWS Region Table where Amazon Redshift is available.

To learn more, visit the getting started guides for DynamoDB and Amazon Redshift. For more information on using history mode, we encourage you to visit our recent blog post here.

 

​Amazon DynamoDB zero-ETL integration with Amazon Redshift is now supported in the Asia Pacific (Taipei) region. This expansion enables customers to run high-performance analytics on their DynamoDB data in Amazon Redshift with no impact on production workloads running on DynamoDB.  Zero-ETL integrations help you derive holistic insights across many applications, break data silos in your organization, and gain significant cost savings and operational efficiencies. Now you can run enhanced analysis on your DynamoDB data with the rich capabilities of Amazon Redshift, such as high performance SQL, built-in ML and Spark integrations, materialized views with automatic and incremental refresh, and data sharing. Additionally, you can use history mode to easily run advanced analytics on historical data, build lookback reports, and build Type 2 Slowly Changing Dimension (SCD 2) tables on your historical data from DynamoDB, out-of-the-box in Amazon Redshift, without writing any code. The Amazon DynamoDB zero-ETL integration with Amazon Redshift is now available in Asia Pacific (Taipei), in addition to previously supported regions. For a complete list of supported regions, please refer to the AWS Region Table where Amazon Redshift is available. To learn more, visit the getting started guides for DynamoDB and Amazon Redshift. For more information on using history mode, we encourage you to visit our recent blog post here.  

Amazon Quick Sight, a capability of Amazon Quick Suite, now offers a visual data preparation experience that helps business users perform advanced data transformations without writing complex code. Users can now clean, transform, and combine data in multi-step workflows—appending tables, aggregating data, executing flexible joins, and other advanced operations that previously required custom programming or SQL commands.

Users can easily track data transformations step-by-step, enhancing traceability and shareability. With the ability to utilize datasets as a source expanded from 3 to 10 levels, teams can build reusable transformation logic that cascades across departments. For instance, centralized data analysts can now prepare foundational data sets that can then be further customized by regional business users, applying territory-specific calculations and business logic with simple clicks. The enhanced experience now also supports 20X larger cross-source joins, moving from a previous capacity of 1GB to 20GB today.

This feature is available to Quick Sight Author and Author Pro customers in the following regions: US East (N.Virginia and Ohio), US West (Oregon), Canada (Central), South America (Sao Paulo), Europe (Frankfurt, Milan, Paris, Spain, Stockholm, Ireland, London, Zurich), Africa (Cape Town), Middle East (UAE), Israel (Tel Aviv), Asia Pacific (Jakarta, Mumbai, Singapore, Tokyo, Seoul, Sydney), AWS GovCloud (US-West, US- East) and to Quick Suite Enterprise subscribers in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). For more details, read our documentation here.

 

​Amazon Quick Sight, a capability of Amazon Quick Suite, now offers a visual data preparation experience that helps business users perform advanced data transformations without writing complex code. Users can now clean, transform, and combine data in multi-step workflows—appending tables, aggregating data, executing flexible joins, and other advanced operations that previously required custom programming or SQL commands. Users can easily track data transformations step-by-step, enhancing traceability and shareability. With the ability to utilize datasets as a source expanded from 3 to 10 levels, teams can build reusable transformation logic that cascades across departments. For instance, centralized data analysts can now prepare foundational data sets that can then be further customized by regional business users, applying territory-specific calculations and business logic with simple clicks. The enhanced experience now also supports 20X larger cross-source joins, moving from a previous capacity of 1GB to 20GB today. This feature is available to Quick Sight Author and Author Pro customers in the following regions: US East (N.Virginia and Ohio), US West (Oregon), Canada (Central), South America (Sao Paulo), Europe (Frankfurt, Milan, Paris, Spain, Stockholm, Ireland, London, Zurich), Africa (Cape Town), Middle East (UAE), Israel (Tel Aviv), Asia Pacific (Jakarta, Mumbai, Singapore, Tokyo, Seoul, Sydney), AWS GovCloud (US-West, US- East) and to Quick Suite Enterprise subscribers in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). For more details, read our documentation here.  

Starting today, Amazon Aurora DSQL is now available in Europe (Frankfurt). Aurora DSQL is the fastest serverless, distributed SQL database with active-active high availability and multi-Region strong consistency. Aurora DSQL enables you to build always available applications with virtually unlimited scalability, the highest availability, and zero infrastructure management. It is designed to make scaling and resilience effortless for your applications and offers the fastest distributed SQL reads and writes.

Aurora DSQL is now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Frankfurt).

Get started with Aurora DSQL for free with the AWS Free Tier. To learn more, visit the Aurora DSQL webpage and documentation.

 

​Starting today, Amazon Aurora DSQL is now available in Europe (Frankfurt). Aurora DSQL is the fastest serverless, distributed SQL database with active-active high availability and multi-Region strong consistency. Aurora DSQL enables you to build always available applications with virtually unlimited scalability, the highest availability, and zero infrastructure management. It is designed to make scaling and resilience effortless for your applications and offers the fastest distributed SQL reads and writes. Aurora DSQL is now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Frankfurt). Get started with Aurora DSQL for free with the AWS Free Tier. To learn more, visit the Aurora DSQL webpage and documentation.  

Amazon Connect outbound campaigns now offers a preview dialing mode that gives agents more context about a customer before placing a call. Agents can see key customer information—such as name, account balance, and prior interactions—and choose the right moment to call. Campaign managers can tailor preview settings and monitor performance through new dashboards that bring visibility to agent behavior, campaign outcomes, and customer engagement trends.

Without proper context, agents struggle to personalize interactions, leading to low customer engagement and poor experiences. Additionally, businesses can face steep regulatory penalties under laws such as the U.S. Telephone Consumer Protection Act (TCPA) or the UK Office of Communications (OFCOM) for delays in customer-agent connection.

With preview dialing, campaign managers can define review time limits and optionally enable contact removal from campaigns. During preview, agents see a countdown timer alongside customer data and can initiate calls at any moment. Analytics reveal performance patterns—such as average preview time or discard volume—giving managers data to optimize strategy and coach teams effectively. By reserving an agent prior to placing the call, companies can support compliance with regulations while bringing precision to outbound calling, improving both customer connection and operational control.

With Amazon Connect outbound campaigns, companies pay-as-they-go for campaign processing and channel usage. Preview dialing is available in AWS regions, including US East (N. Virginia), US West (Oregon), Africa (Cape Town), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London).

To learn more about configuring preview dialing, visit our webpage.

 

​Amazon Connect outbound campaigns now offers a preview dialing mode that gives agents more context about a customer before placing a call. Agents can see key customer information—such as name, account balance, and prior interactions—and choose the right moment to call. Campaign managers can tailor preview settings and monitor performance through new dashboards that bring visibility to agent behavior, campaign outcomes, and customer engagement trends. Without proper context, agents struggle to personalize interactions, leading to low customer engagement and poor experiences. Additionally, businesses can face steep regulatory penalties under laws such as the U.S. Telephone Consumer Protection Act (TCPA) or the UK Office of Communications (OFCOM) for delays in customer-agent connection. With preview dialing, campaign managers can define review time limits and optionally enable contact removal from campaigns. During preview, agents see a countdown timer alongside customer data and can initiate calls at any moment. Analytics reveal performance patterns—such as average preview time or discard volume—giving managers data to optimize strategy and coach teams effectively. By reserving an agent prior to placing the call, companies can support compliance with regulations while bringing precision to outbound calling, improving both customer connection and operational control. With Amazon Connect outbound campaigns, companies pay-as-they-go for campaign processing and channel usage. Preview dialing is available in AWS regions, including US East (N. Virginia), US West (Oregon), Africa (Cape Town), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London). To learn more about configuring preview dialing, visit our webpage.  

AWS Outposts 2U server is now supported in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions. Outposts 2U server is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to on-premises or edge locations with limited space or smaller capacity requirements for a truly consistent hybrid experience. It is delivered in an industry-standard 2U form factor and provides up to 128 vCPUs of compute. It is ideal for applications that need to run on-premises to meet low latency and stringent compliance requirements. You can also use Outposts 2U server to manage your local data processing needs.

With the availability of Outposts 2U server in the GovCloud (US-East) and GovCloud (US-West) Regions, you can now run Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS), and AWS IoT Greengrass locally on Outposts 2U servers, and connect to a broader range of AWS services available in the parent AWS GovCloud (US) Region. For AWS GovCloud (US) Regions customers, this means you can run sensitive and controlled unclassified information (CUI) data on-premises at your facilities and connect to the parent AWS GovCloud (US) Region for management and operations.

To learn more about Outposts 2U server, visit the product page and read the user guide.

 

​AWS Outposts 2U server is now supported in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions. Outposts 2U server is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to on-premises or edge locations with limited space or smaller capacity requirements for a truly consistent hybrid experience. It is delivered in an industry-standard 2U form factor and provides up to 128 vCPUs of compute. It is ideal for applications that need to run on-premises to meet low latency and stringent compliance requirements. You can also use Outposts 2U server to manage your local data processing needs.
With the availability of Outposts 2U server in the GovCloud (US-East) and GovCloud (US-West) Regions, you can now run Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS), and AWS IoT Greengrass locally on Outposts 2U servers, and connect to a broader range of AWS services available in the parent AWS GovCloud (US) Region. For AWS GovCloud (US) Regions customers, this means you can run sensitive and controlled unclassified information (CUI) data on-premises at your facilities and connect to the parent AWS GovCloud (US) Region for management and operations.
To learn more about Outposts 2U server, visit the product page and read the user guide.