Amazon CloudWatch now allows you to monitor multiple individual metrics via a single alarm. By dynamically including metrics to monitor via a query, this new capability eliminates the need to manually manage separate alarms for dynamic resource fleets.

As customers rely more on autonomous teams and autoscaled resources, they face a choice between maintenance-free aggregated monitoring and the operational cost of maintaining per-resource alarming. Alarms that evaluate multiple metrics provide granular monitoring with individual actions through an alarm that automatically adjusts in real time as resources get created or deleted. This reduces operational efforts, allowing customers to focus on the value of their observability while ensuring no resources go unmonitored.

Monitoring multiple metrics with a single alarm is now available in all commercial AWS regions, the AWS GovCloud (US) Regions, and the China Regions.

To start alarming on multiple metrics, create an alarm on a Metrics Insights (SQL) metrics query using GROUP BY and ORDER BY conditions. The alarm automatically updates the query results with each evaluation, and matches corresponding metrics as resources change. You can configure alarms through the CloudWatch console, AWS CLI, CloudFormation, or CDK. Metrics Insights query alarms’ pricing applies, see CloudWatch pricing for details. To learn more about monitoring multiple metrics with query alarms and improving your monitoring efficiency, visit the CloudWatch alarms documentation.

 

​Amazon CloudWatch now allows you to monitor multiple individual metrics via a single alarm. By dynamically including metrics to monitor via a query, this new capability eliminates the need to manually manage separate alarms for dynamic resource fleets. As customers rely more on autonomous teams and autoscaled resources, they face a choice between maintenance-free aggregated monitoring and the operational cost of maintaining per-resource alarming. Alarms that evaluate multiple metrics provide granular monitoring with individual actions through an alarm that automatically adjusts in real time as resources get created or deleted. This reduces operational efforts, allowing customers to focus on the value of their observability while ensuring no resources go unmonitored. Monitoring multiple metrics with a single alarm is now available in all commercial AWS regions, the AWS GovCloud (US) Regions, and the China Regions. To start alarming on multiple metrics, create an alarm on a Metrics Insights (SQL) metrics query using GROUP BY and ORDER BY conditions. The alarm automatically updates the query results with each evaluation, and matches corresponding metrics as resources change. You can configure alarms through the CloudWatch console, AWS CLI, CloudFormation, or CDK. Metrics Insights query alarms’ pricing applies, see CloudWatch pricing for details. To learn more about monitoring multiple metrics with query alarms and improving your monitoring efficiency, visit the CloudWatch alarms documentation.  

Amazon CloudWatch now allows you to query metrics data up to two weeks in the past using the Metrics Insights query source. CloudWatch Metrics Insights offers fast, flexible, SQL-based queries. This new capability allows you to display, aggregate, or slice and dice metrics data older than 3 hours, for enhanced visualization and investigation.

Customers creating dashboards and alarms to monitor dynamic groups of metrics over their resources and applications could visualize up to 3 hours of data when using Metrics Insights SQL queries. This enhancement helps customers identify trends and investigate impact for a longer period of time, even days after an event. This extended query time range helps improve the operational health of teams and ensures impacts are never missed.

Querying metrics data up to two weeks old with Metrics Insights is now available in commercial AWS regions.

The ability to query metrics data up to 2 weeks old is automatically available at no additional cost. Standard pricing applies for alarms, dashboards or API usage on Metrics Insights, see CloudWatch pricing for details. To learn more about metrics queries with Metrics Insights, visit the CloudWatch documentation.

 

​Amazon CloudWatch now allows you to query metrics data up to two weeks in the past using the Metrics Insights query source. CloudWatch Metrics Insights offers fast, flexible, SQL-based queries. This new capability allows you to display, aggregate, or slice and dice metrics data older than 3 hours, for enhanced visualization and investigation. Customers creating dashboards and alarms to monitor dynamic groups of metrics over their resources and applications could visualize up to 3 hours of data when using Metrics Insights SQL queries. This enhancement helps customers identify trends and investigate impact for a longer period of time, even days after an event. This extended query time range helps improve the operational health of teams and ensures impacts are never missed. Querying metrics data up to two weeks old with Metrics Insights is now available in commercial AWS regions. The ability to query metrics data up to 2 weeks old is automatically available at no additional cost. Standard pricing applies for alarms, dashboards or API usage on Metrics Insights, see CloudWatch pricing for details. To learn more about metrics queries with Metrics Insights, visit the CloudWatch documentation.  

Amazon RDS for Oracle and Amazon RDS Custom for Oracle now support bare metal instances. You can use M7i, R7i, X2iedn, X2idn, X2iezn, M6i, M6id, M6in, R6i, R6id, and R6in bare metal instances at 25% lower price compared to equivalent virtualized instances.

With bare metal instances, you can combine multiple databases onto a single bare metal instance to reduce cost by using the Multi-tenant feature. For example, databases running on a db.r7i.16xlarge instance and a db.r7i.8xlarge instance can be consolidated to individual pluggable databases on a single db.r7i.metal-24xl instance. Furthermore, you may be able to reduce your commercial database license and support costs by using bare metal instances since they provide full visibility into the number of CPU cores and sockets of the underlying server. Refer to Oracle Cloud Policy and Oracle Core Factor Table, and consult your licensing partner to determine if you can reduce license and support costs.

Bare metal instances are available with Bring Your Own License (BYOL) license for Oracle Enterprise Edition. Refer to Amazon RDS for Oracle Pricing and Amazon RDS Custom for Oracle Pricing for available instance configurations, pricing, and region availability. 

 

​Amazon RDS for Oracle and Amazon RDS Custom for Oracle now support bare metal instances. You can use M7i, R7i, X2iedn, X2idn, X2iezn, M6i, M6id, M6in, R6i, R6id, and R6in bare metal instances at 25% lower price compared to equivalent virtualized instances. With bare metal instances, you can combine multiple databases onto a single bare metal instance to reduce cost by using the Multi-tenant feature. For example, databases running on a db.r7i.16xlarge instance and a db.r7i.8xlarge instance can be consolidated to individual pluggable databases on a single db.r7i.metal-24xl instance. Furthermore, you may be able to reduce your commercial database license and support costs by using bare metal instances since they provide full visibility into the number of CPU cores and sockets of the underlying server. Refer to Oracle Cloud Policy and Oracle Core Factor Table, and consult your licensing partner to determine if you can reduce license and support costs. Bare metal instances are available with Bring Your Own License (BYOL) license for Oracle Enterprise Edition. Refer to Amazon RDS for Oracle Pricing and Amazon RDS Custom for Oracle Pricing for available instance configurations, pricing, and region availability.   

AWS Clean Rooms now supports the ability to add data provider members to an existing collaboration, offering customers enhanced flexibility as they iterate on and develop new use cases with their partners. With this launch, you can collaborate with new data providers without having to set up a new collaboration. Collaboration owners can configure an existing Clean Rooms collaboration to add new members that only contribute data, while benefiting from the privacy controls existing members already configured within the collaboration. New data providers invited to an existing collaboration can be reviewed in the change history, enhancing transparency across members. For example, when a publisher creates a Clean Rooms collaboration with an advertiser, they can enable adding new data providers such as a measurement company, which allows the advertiser to enrich their audience segments with third-party data before activating an audience with the publisher. This approach reduces onboarding time while maintaining the existing privacy controls for you and your partners.

AWS Clean Rooms helps companies and their partners easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.

 

​AWS Clean Rooms now supports the ability to add data provider members to an existing collaboration, offering customers enhanced flexibility as they iterate on and develop new use cases with their partners. With this launch, you can collaborate with new data providers without having to set up a new collaboration. Collaboration owners can configure an existing Clean Rooms collaboration to add new members that only contribute data, while benefiting from the privacy controls existing members already configured within the collaboration. New data providers invited to an existing collaboration can be reviewed in the change history, enhancing transparency across members. For example, when a publisher creates a Clean Rooms collaboration with an advertiser, they can enable adding new data providers such as a measurement company, which allows the advertiser to enrich their audience segments with third-party data before activating an audience with the publisher. This approach reduces onboarding time while maintaining the existing privacy controls for you and your partners. AWS Clean Rooms helps companies and their partners easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.  

Today, AWS announces the ability to manage access to AWS Regions and AWS Local Zones from a single place within the AWS Management Console. With this new capability, customers can now efficiently monitor and manage access to AWS Regions and AWS Local Zones globally.

AWS Global View enables customers to view resources across multiple Regions in a single console. To get started, customers can find «AWS Global View» in the AWS Management Console and navigate to the Regions and Zones page. The Regions and Zones page displays infrastructure location details, opt-in status, as well as any parent Region relationships, making it easier for customers to manage and monitor their global AWS footprint.

This capability is available in all AWS commercial Regions. To learn more, visit the AWS Global View documentation, or navigate to the Regions and Zones page here.

 

​Today, AWS announces the ability to manage access to AWS Regions and AWS Local Zones from a single place within the AWS Management Console. With this new capability, customers can now efficiently monitor and manage access to AWS Regions and AWS Local Zones globally. AWS Global View enables customers to view resources across multiple Regions in a single console. To get started, customers can find «AWS Global View» in the AWS Management Console and navigate to the Regions and Zones page. The Regions and Zones page displays infrastructure location details, opt-in status, as well as any parent Region relationships, making it easier for customers to manage and monitor their global AWS footprint. This capability is available in all AWS commercial Regions. To learn more, visit the AWS Global View documentation, or navigate to the Regions and Zones page here.  

Beginning today, customers can use Amazon Bedrock in the Asia Pacific (Jakarta) region to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications.

Amazon Bedrock is a fully managed service that offers a choice of high-performing large language models and other FMs from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities, such as Guardrails and Model customization, that customers need to build generative AI applications with security, privacy, and responsible AI built into Amazon Bedrock. These capabilities help customers build tailored applications for multiple use cases across different industries, helping organizations unlock sustained growth from generative AI while ensuring customer trust and data governance.

To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.

 

​Beginning today, customers can use Amazon Bedrock in the Asia Pacific (Jakarta) region to easily build and scale generative AI applications using a variety of foundation models (FMs) as well as powerful tools to build generative AI applications. Amazon Bedrock is a fully managed service that offers a choice of high-performing large language models and other FMs from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities, such as Guardrails and Model customization, that customers need to build generative AI applications with security, privacy, and responsible AI built into Amazon Bedrock. These capabilities help customers build tailored applications for multiple use cases across different industries, helping organizations unlock sustained growth from generative AI while ensuring customer trust and data governance. To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.  

Amazon CloudWatch Synthetics now enables customers to test and monitor web applications in Firefox, in addition to existing Chrome support. This enhancement helps customers ensure consistent functionality and performance across different browsers, making it easier to identify browser-specific issues before they impact end users.

With this launch, you can run the same canary script across Chrome and Firefox when using Playwright-based canaries or Puppeteer-based canaries. CloudWatch Synthetics automatically collects browser-specific performance metrics, success rates, and visual monitoring results while maintaining an aggregate view of overall application health. This helps development and operations teams quickly identify and resolve browser compatibility issues that could affect application reliability.

Multi-browser support is available in all commercial AWS Regions. To learn more about configuring multi-browser canaries, see the canary docs in the Amazon CloudWatch Synthetics User Guide.

 

​Amazon CloudWatch Synthetics now enables customers to test and monitor web applications in Firefox, in addition to existing Chrome support. This enhancement helps customers ensure consistent functionality and performance across different browsers, making it easier to identify browser-specific issues before they impact end users. With this launch, you can run the same canary script across Chrome and Firefox when using Playwright-based canaries or Puppeteer-based canaries. CloudWatch Synthetics automatically collects browser-specific performance metrics, success rates, and visual monitoring results while maintaining an aggregate view of overall application health. This helps development and operations teams quickly identify and resolve browser compatibility issues that could affect application reliability. Multi-browser support is available in all commercial AWS Regions. To learn more about configuring multi-browser canaries, see the canary docs in the Amazon CloudWatch Synthetics User Guide.  

Amazon Relational Database Service (Amazon RDS) for Oracle now offers Oracle Database Standard Edition 2 (SE2) License Included R7i and M7i instances in Asia Pacific (Thailand) and Mexico (Central) regions.

With Amazon RDS for Oracle SE2 License Included instances, you do not need to purchase Oracle Database licenses. You simply launch Amazon RDS for Oracle instances through the AWS Management Console, AWS CLI, or AWS SDKs, and there are no separate license or support charges. Review the AWS blog Rethink Oracle Standard Edition Two on Amazon RDS for Oracle to explore how you can lower cost and simplify operations by using Amazon RDS Oracle SE2 License Included instances for your Oracle databases.

To learn more about pricing and regional availability, see Amazon RDS for Oracle pricing.

 

​Amazon Relational Database Service (Amazon RDS) for Oracle now offers Oracle Database Standard Edition 2 (SE2) License Included R7i and M7i instances in Asia Pacific (Thailand) and Mexico (Central) regions. With Amazon RDS for Oracle SE2 License Included instances, you do not need to purchase Oracle Database licenses. You simply launch Amazon RDS for Oracle instances through the AWS Management Console, AWS CLI, or AWS SDKs, and there are no separate license or support charges. Review the AWS blog Rethink Oracle Standard Edition Two on Amazon RDS for Oracle to explore how you can lower cost and simplify operations by using Amazon RDS Oracle SE2 License Included instances for your Oracle databases. To learn more about pricing and regional availability, see Amazon RDS for Oracle pricing.  

Today, AWS announced the expansion of 10 Gbps and 100 Gbps dedicated connections with MACsec encryption capabilities at the existing AWS Direct Connect location in the Rack Centre LGS1 data center near Lagos, Nigeria. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location.

The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.

For more information on the over 145 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.

 

​Today, AWS announced the expansion of 10 Gbps and 100 Gbps dedicated connections with MACsec encryption capabilities at the existing AWS Direct Connect location in the Rack Centre LGS1 data center near Lagos, Nigeria. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet. For more information on the over 145 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.  

Starting today, Split Cost Allocation Data now adds support for accelerated-computing workloads running in the Amazon Elastic Kubernetes Service (EKS). The new feature in Split Cost Allocation Data for EKS allows customers to track the costs associated with accelerator-powered (Trainium, Inferentia, NVIDIA and AMD GPUs) container-level resources within their EKS clusters, in addition to the costs for CPU and Memory. This cost data is available in the AWS Cost and Usage Report, including CUR 2.0.

With this new capability, customers get greater visibility over their AI/ML cloud infrastructure expenses. Customers can now allocate application costs to individual business units and teams based on the CPU, memory and accelerator resource reservations of their containerized accelerated-computing workloads. New Split Cost Allocation Data customers can enable this feature in the AWS Billing and Cost Management console. This feature is automatically enabled for existing Split Cost Allocation Data customers. You can use the Containers Cost Allocation dashboard to visualize the costs in Amazon QuickSight and the CUR query library to query the costs using Amazon Athena.

This feature is available in all AWS Regions where Split Cost Allocation Data for Amazon EKS is available. To get started, visit Understanding Split Cost Allocation Data and Improve cost visibility of Machine Learning workloads on Amazon EKS with AWS Split Cost Allocation Data.

 

​Starting today, Split Cost Allocation Data now adds support for accelerated-computing workloads running in the Amazon Elastic Kubernetes Service (EKS). The new feature in Split Cost Allocation Data for EKS allows customers to track the costs associated with accelerator-powered (Trainium, Inferentia, NVIDIA and AMD GPUs) container-level resources within their EKS clusters, in addition to the costs for CPU and Memory. This cost data is available in the AWS Cost and Usage Report, including CUR 2.0.
With this new capability, customers get greater visibility over their AI/ML cloud infrastructure expenses. Customers can now allocate application costs to individual business units and teams based on the CPU, memory and accelerator resource reservations of their containerized accelerated-computing workloads. New Split Cost Allocation Data customers can enable this feature in the AWS Billing and Cost Management console. This feature is automatically enabled for existing Split Cost Allocation Data customers. You can use the Containers Cost Allocation dashboard to visualize the costs in Amazon QuickSight and the CUR query library to query the costs using Amazon Athena.
This feature is available in all AWS Regions where Split Cost Allocation Data for Amazon EKS is available. To get started, visit Understanding Split Cost Allocation Data and Improve cost visibility of Machine Learning workloads on Amazon EKS with AWS Split Cost Allocation Data.