Amazon Q Developer has expanded its AWS Console error coverage from US East (N. Virginia) and US West (Oregon) to AWS Commercial regions. Users can now troubleshoot AWS Console errors using Amazon Q Developer regardless of their console region, including locations like Europe (Frankfurt).

In the Amazon Web Services (AWS) Management Console, Amazon Q Developer diagnoses common errors you encounter while working with AWS services, such as insufficient permissions, incorrect configuration, and exceeding service limits. Q Developer troubleshoots errors arising from the following services in the AWS Management Console: Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS), Amazon Simple Storage Service (Amazon S3), AWS Lambda and Amazon CloudFormation (Amazon CFn). In addition, Q Developer troubleshoots IAM Permission and Athena console errors across all AWS Console pages.

To learn more about using Amazon Q Developer to troubleshoot AWS Console errors, visit the AWS documentation. Amazon Q Developer is currently available in select regions, and you can review information about where your data is processed here. For pricing details, visit the Amazon Q Developer pricing page.

 

​Amazon Q Developer has expanded its AWS Console error coverage from US East (N. Virginia) and US West (Oregon) to AWS Commercial regions. Users can now troubleshoot AWS Console errors using Amazon Q Developer regardless of their console region, including locations like Europe (Frankfurt). In the Amazon Web Services (AWS) Management Console, Amazon Q Developer diagnoses common errors you encounter while working with AWS services, such as insufficient permissions, incorrect configuration, and exceeding service limits. Q Developer troubleshoots errors arising from the following services in the AWS Management Console: Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS), Amazon Simple Storage Service (Amazon S3), AWS Lambda and Amazon CloudFormation (Amazon CFn). In addition, Q Developer troubleshoots IAM Permission and Athena console errors across all AWS Console pages. To learn more about using Amazon Q Developer to troubleshoot AWS Console errors, visit the AWS documentation. Amazon Q Developer is currently available in select regions, and you can review information about where your data is processed here. For pricing details, visit the Amazon Q Developer pricing page.  

Amazon Connect now provides the ability to choose which states an agent can be in when adhering to their schedule, making it easier for you to customize adherence tracking to match your unique operational needs. With this launch, you can now define custom mappings between agent statuses and schedule activities. For example, schedule activity “Work” can be mapped to multiple agent statuses such as “Available” and “Back-office work.” An agent scheduled for “Work” from 8 AM to 10 AM will be considered adherent if they are either in “Available” or “Back-office work” status. Additionally, you can now view the actual name of the scheduled activity in the real-time adherence dashboard (as opposed to only Productive/Non-productive). With custom mappings and enhanced real-time dashboard, this launch provides more accurate and flexible agent adherence monitoring.

This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.
 

 

​Amazon Connect now provides the ability to choose which states an agent can be in when adhering to their schedule, making it easier for you to customize adherence tracking to match your unique operational needs. With this launch, you can now define custom mappings between agent statuses and schedule activities. For example, schedule activity “Work” can be mapped to multiple agent statuses such as “Available” and “Back-office work.” An agent scheduled for “Work” from 8 AM to 10 AM will be considered adherent if they are either in “Available” or “Back-office work” status. Additionally, you can now view the actual name of the scheduled activity in the real-time adherence dashboard (as opposed to only Productive/Non-productive). With custom mappings and enhanced real-time dashboard, this launch provides more accurate and flexible agent adherence monitoring. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.    

AWS Batch on EKS now supports configurable Kubernetes namespaces, Persistent Volume Claims (PVCs), subPath to Kubernetes pod container volumes, and Kubernetes pod annotations. Using different Kubernetes namespaces for your AWS Batch jobs, you can improve workload isolation by defining job permission boundaries both within EKS cluster and for access to other AWS services. With Kubernetes PVCs and subPath you can give your AWS Batch jobs access only to the right data or particular subPath within a data volume. Finally, EKS pod annotations make it easier to integrate with external tools and other AWS services such as AWS Secrets Manager by allowing you to attach necessary metadata directly to your AWS Batch job.

You can configure Kubernetes namespaces, PVCs, subPath, and annotations while registering a new AWS Batch job definition or making a revision to an existing job definition. You can also override the namespace and annotations from your job definition when you submit the job. For more information, see Register Job Definition and Submit Job pages in the AWS Batch API reference and our AWS HPC Blog post.

AWS Batch supports developers, scientists, and engineers in running efficient batch processing for ML model training, simulations, and analysis at any scale. Configurable Kubernetes namespaces, PVCs, subPath, and annotations are available in any AWS Region where AWS Batch is available.
 

 

​AWS Batch on EKS now supports configurable Kubernetes namespaces, Persistent Volume Claims (PVCs), subPath to Kubernetes pod container volumes, and Kubernetes pod annotations. Using different Kubernetes namespaces for your AWS Batch jobs, you can improve workload isolation by defining job permission boundaries both within EKS cluster and for access to other AWS services. With Kubernetes PVCs and subPath you can give your AWS Batch jobs access only to the right data or particular subPath within a data volume. Finally, EKS pod annotations make it easier to integrate with external tools and other AWS services such as AWS Secrets Manager by allowing you to attach necessary metadata directly to your AWS Batch job. You can configure Kubernetes namespaces, PVCs, subPath, and annotations while registering a new AWS Batch job definition or making a revision to an existing job definition. You can also override the namespace and annotations from your job definition when you submit the job. For more information, see Register Job Definition and Submit Job pages in the AWS Batch API reference and our AWS HPC Blog post. AWS Batch supports developers, scientists, and engineers in running efficient batch processing for ML model training, simulations, and analysis at any scale. Configurable Kubernetes namespaces, PVCs, subPath, and annotations are available in any AWS Region where AWS Batch is available.    

Amazon EC2 now supports automated recovery of Microsoft SQL Server databases from Volume Shadow Copy Services (VSS) based EBS snapshots. Customers can use an AWS Systems Manager Automation Runbook and specify a restore point of time to automate the recovery process without needing to stop a running Microsoft SQL Server database.

Volume Shadow Copy Services (VSS) allows application data to be backed up while applications are still running. This new feature allows customers to automate the recovery from VSS-based EBS snapshots and ensure rapid recovery of large databases within minutes. This feature also offers customers the flexibility to restore to a new database or achieve point-in-time recovery.

This feature is available in all commercial AWS Regions and the AWS GovCloud (US) Regions.

To learn more, visit this technical document in the Microsoft SQL Server on Amazon EC2 User Guide.

 

​Amazon EC2 now supports automated recovery of Microsoft SQL Server databases from Volume Shadow Copy Services (VSS) based EBS snapshots. Customers can use an AWS Systems Manager Automation Runbook and specify a restore point of time to automate the recovery process without needing to stop a running Microsoft SQL Server database. Volume Shadow Copy Services (VSS) allows application data to be backed up while applications are still running. This new feature allows customers to automate the recovery from VSS-based EBS snapshots and ensure rapid recovery of large databases within minutes. This feature also offers customers the flexibility to restore to a new database or achieve point-in-time recovery. This feature is available in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, visit this technical document in the Microsoft SQL Server on Amazon EC2 User Guide.  

A new minor version of Microsoft SQL Server is now available on Amazon RDS for SQL Server, providing performance enhancements and security fixes. Amazon RDS for SQL Server now supports this latest minor version of SQL Server 2019 across the Express, Web, Standard, and Enterprise editions.

We encourage you to upgrade your Amazon RDS for SQL Server database instances at your convenience. You can upgrade with just a few clicks in the Amazon RDS Management Console or by using the AWS CLI. Learn more about upgrading your database instances from the Amazon RDS User Guide. The new minor version is SQL Server 2019 CU30 – 15.0.4415.2.

This minor version is available in all AWS commercial regions where Amazon RDS for SQL Server databases are available, including the AWS GovCloud (US) Regions.

Amazon RDS for SQL Server makes it simple to set up, operate, and scale SQL Server deployments in the cloud. See Amazon RDS for SQL Server Pricing for pricing details and regional availability.

 

​A new minor version of Microsoft SQL Server is now available on Amazon RDS for SQL Server, providing performance enhancements and security fixes. Amazon RDS for SQL Server now supports this latest minor version of SQL Server 2019 across the Express, Web, Standard, and Enterprise editions. We encourage you to upgrade your Amazon RDS for SQL Server database instances at your convenience. You can upgrade with just a few clicks in the Amazon RDS Management Console or by using the AWS CLI. Learn more about upgrading your database instances from the Amazon RDS User Guide. The new minor version is SQL Server 2019 CU30 – 15.0.4415.2. This minor version is available in all AWS commercial regions where Amazon RDS for SQL Server databases are available, including the AWS GovCloud (US) Regions. Amazon RDS for SQL Server makes it simple to set up, operate, and scale SQL Server deployments in the cloud. See Amazon RDS for SQL Server Pricing for pricing details and regional availability.  

AWS CodeBuild now offers native support for self-hosted Buildkite runners, enabling you to execute Buildkite pipeline jobs within the CodeBuild environment. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment.

Buildkite is a continuous integration and continuous delivery platform. With this feature, your Buildkite jobs can access CodeBuild’s comprehensive suite of instance types and managed images, and utilize native integrations with AWS services. You have control over the build environment, without the overhead of manually provisioning and scaling the compute resources.

The Buildkite runner feature is available in all regions where CodeBuild is offered. For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page.

To use the self-hosted Buildkite runners, follow the tutorial to set up a runner project in CodeBuild. To learn more about how to get started with CodeBuild, visit the AWS CodeBuild product page.

 

​AWS CodeBuild now offers native support for self-hosted Buildkite runners, enabling you to execute Buildkite pipeline jobs within the CodeBuild environment. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment. Buildkite is a continuous integration and continuous delivery platform. With this feature, your Buildkite jobs can access CodeBuild’s comprehensive suite of instance types and managed images, and utilize native integrations with AWS services. You have control over the build environment, without the overhead of manually provisioning and scaling the compute resources. The Buildkite runner feature is available in all regions where CodeBuild is offered. For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page. To use the self-hosted Buildkite runners, follow the tutorial to set up a runner project in CodeBuild. To learn more about how to get started with CodeBuild, visit the AWS CodeBuild product page.  

Amazon Redshift Concurrency Scaling is now available in the Asia Pacific (Malaysia) region.

Amazon Redshift Concurrency Scaling elastically scales query processing power to provide consistently fast performance for hundreds of concurrent queries. Concurrency Scaling resources are added to your Redshift cluster transparently in seconds, as concurrency increases, to process queries without wait time. Amazon Redshift customers with an active Redshift cluster earn up to one hour of free Concurrency Scaling credits, which is sufficient for the concurrency needs of most customers. Concurrency scaling allows you to specify usage control providing customers with predictability in their month-to-month cost, even during periods of fluctuating analytical demand.

To enable Concurrency Scaling, set the Concurrency Scaling Mode to Auto in your Amazon Web Services Management Console. You can allocate Concurrency Scaling usage to specific user groups and workloads, control the number of Concurrency Scaling clusters that can be used, and monitor Cloudwatch performance and usage metrics.

To learn more about concurrency scaling including regional-availability, see our documentation and pricing page.
 

 

​Amazon Redshift Concurrency Scaling is now available in the Asia Pacific (Malaysia) region.
Amazon Redshift Concurrency Scaling elastically scales query processing power to provide consistently fast performance for hundreds of concurrent queries. Concurrency Scaling resources are added to your Redshift cluster transparently in seconds, as concurrency increases, to process queries without wait time. Amazon Redshift customers with an active Redshift cluster earn up to one hour of free Concurrency Scaling credits, which is sufficient for the concurrency needs of most customers. Concurrency scaling allows you to specify usage control providing customers with predictability in their month-to-month cost, even during periods of fluctuating analytical demand. To enable Concurrency Scaling, set the Concurrency Scaling Mode to Auto in your Amazon Web Services Management Console. You can allocate Concurrency Scaling usage to specific user groups and workloads, control the number of Concurrency Scaling clusters that can be used, and monitor Cloudwatch performance and usage metrics. To learn more about concurrency scaling including regional-availability, see our documentation and pricing page.    

AWS Transfer Family web apps are now available in the following additional Regions: North America (N. California, Canada West, Canada Central), South America (São Paulo), Europe (London, Paris, Zurich, Milan, Spain), Africa (Cape Town), Israel (Tel Aviv), Middle East (Bahrain, UAE), and Asia Pacific (Osaka, Hong Kong, Hyderabad, Jakarta, Melbourne, Seoul, Mumbai). This expansion allows you to create Transfer Family web apps in additional commercial Regions where Transfer Family is available.

AWS Transfer Family web apps provide a simple interface for accessing your data in Amazon S3 through a web browser. With Transfer Family web apps, you can provide your workforce with a fully managed, branded, and secure portal for your end users to browse, upload, and download data in S3.

To learn more about AWS Transfer Family web apps, read our blog and visit the Transfer Family User Guide. For complete regional availability information, see the AWS Region Table.

 

​AWS Transfer Family web apps are now available in the following additional Regions: North America (N. California, Canada West, Canada Central), South America (São Paulo), Europe (London, Paris, Zurich, Milan, Spain), Africa (Cape Town), Israel (Tel Aviv), Middle East (Bahrain, UAE), and Asia Pacific (Osaka, Hong Kong, Hyderabad, Jakarta, Melbourne, Seoul, Mumbai). This expansion allows you to create Transfer Family web apps in additional commercial Regions where Transfer Family is available. AWS Transfer Family web apps provide a simple interface for accessing your data in Amazon S3 through a web browser. With Transfer Family web apps, you can provide your workforce with a fully managed, branded, and secure portal for your end users to browse, upload, and download data in S3. To learn more about AWS Transfer Family web apps, read our blog and visit the Transfer Family User Guide. For complete regional availability information, see the AWS Region Table.  

Dashboard Q&A by Amazon Q in QuickSight enables QuickSight Authors to add Data Q&A to their dashboards in one-click. With dashboard Q&A, QuickSight users can ask and answer questions about their data using natural language.

Dashboard Q&A capabilities of Q in QuickSight automatically extract semantic information presented in dashboards and use it to enable Q&A over specific data and improves existing Topic based Q&A experiences by automatically using semantics from dashboards to improve Q&A answers. With Dashboard Q&A Authors can quickly deliver self-service access to customized data insights for the entire organization.

Dashboard Q&A is launching to all regions in which QuickSight’s generative data Q&A is available today, as documented here.

To learn more, visit our documentation.

 

​Dashboard Q&A by Amazon Q in QuickSight enables QuickSight Authors to add Data Q&A to their dashboards in one-click. With dashboard Q&A, QuickSight users can ask and answer questions about their data using natural language. Dashboard Q&A capabilities of Q in QuickSight automatically extract semantic information presented in dashboards and use it to enable Q&A over specific data and improves existing Topic based Q&A experiences by automatically using semantics from dashboards to improve Q&A answers. With Dashboard Q&A Authors can quickly deliver self-service access to customized data insights for the entire organization. Dashboard Q&A is launching to all regions in which QuickSight’s generative data Q&A is available today, as documented here. To learn more, visit our documentation.  

Amazon Managed Service for Prometheus collector, a fully-managed agentless collector for Prometheus metrics, adds support for cross-account ingestion. Starting today, you can agentlessly scrape metrics from Amazon Elastic Kubernetes Service clusters in different accounts than your Amazon Managed Service for Prometheus workspace.

While it was previously possible to apply AWS multi-account best practices for centralized observability with Amazon Managed Service for Prometheus workspaces, you had to use self-managed collection. This meant that you had to run, scale, and patch telemetry agents yourself to scrape metrics from Amazon Elastic Kubernetes Service clusters in various accounts in order to ingest them into a central Amazon Managed Service for Prometheus workspaces in a different account. With this launch, you can now use the Amazon Managed Service for Prometheus collector to get rid of this heavy lifting and ingest metrics in a cross-account setup without having to self-run a collector. In addition, you can now also use the Amazon Managed Service for Prometheus collector to scrape metrics from for Amazon Elastic Kubernetes Service clusters to ingest them into Amazon Managed Service for Prometheus workspaces created with customer managed keys.

Amazon Managed Service for Prometheus collector is available in all regions where Amazon Managed Service for Prometheus is available. To learn more about Amazon Managed Service for Prometheus collector, visit the user guide or product page.
 

 

​Amazon Managed Service for Prometheus collector, a fully-managed agentless collector for Prometheus metrics, adds support for cross-account ingestion. Starting today, you can agentlessly scrape metrics from Amazon Elastic Kubernetes Service clusters in different accounts than your Amazon Managed Service for Prometheus workspace. While it was previously possible to apply AWS multi-account best practices for centralized observability with Amazon Managed Service for Prometheus workspaces, you had to use self-managed collection. This meant that you had to run, scale, and patch telemetry agents yourself to scrape metrics from Amazon Elastic Kubernetes Service clusters in various accounts in order to ingest them into a central Amazon Managed Service for Prometheus workspaces in a different account. With this launch, you can now use the Amazon Managed Service for Prometheus collector to get rid of this heavy lifting and ingest metrics in a cross-account setup without having to self-run a collector. In addition, you can now also use the Amazon Managed Service for Prometheus collector to scrape metrics from for Amazon Elastic Kubernetes Service clusters to ingest them into Amazon Managed Service for Prometheus workspaces created with customer managed keys. Amazon Managed Service for Prometheus collector is available in all regions where Amazon Managed Service for Prometheus is available. To learn more about Amazon Managed Service for Prometheus collector, visit the user guide or product page.