Today, AWS announced the ability for Amazon VPC IP Address Manager (IPAM) to distribute IPAM costs to AWS Organizations member accounts. This allows you to easily allocate costs to your internal teams for their IPAM usage.

VPC IPAM makes it easier for you to plan, track, and monitor IP addresses for your AWS workloads. When you enable IPAM for your AWS Organization, IPAM aggregates the organization-wide IP address usage, and charges the AWS account in which IPAM is created. With this launch, you can allocate the charges directly to AWS Organizations member accounts, for their individual usage. For example, you may have IPAM enabled in a central AWS account that runs multiple networking services, and want to allocate the IPAM charges across your internal teams, which you can do easily using this feature.

This feature is now available in all AWS Regions where Amazon VPC IPAM is supported, including AWS China Regions, and AWS GovCloud (US) Regions.

To learn more about IPAM, view the IPAM documentation. For details on pricing, refer to the IPAM tab on the Amazon VPC Pricing Page.

 

​Today, AWS announced the ability for Amazon VPC IP Address Manager (IPAM) to distribute IPAM costs to AWS Organizations member accounts. This allows you to easily allocate costs to your internal teams for their IPAM usage. VPC IPAM makes it easier for you to plan, track, and monitor IP addresses for your AWS workloads. When you enable IPAM for your AWS Organization, IPAM aggregates the organization-wide IP address usage, and charges the AWS account in which IPAM is created. With this launch, you can allocate the charges directly to AWS Organizations member accounts, for their individual usage. For example, you may have IPAM enabled in a central AWS account that runs multiple networking services, and want to allocate the IPAM charges across your internal teams, which you can do easily using this feature. This feature is now available in all AWS Regions where Amazon VPC IPAM is supported, including AWS China Regions, and AWS GovCloud (US) Regions. To learn more about IPAM, view the IPAM documentation. For details on pricing, refer to the IPAM tab on the Amazon VPC Pricing Page.  

AWS Launch Wizard now supports deployment of multi-node SAP NetWeaver applications on SAP ASE database, allowing you to deploy multiple applications servers at the time of deployment. With this deployment pattern, you deploy SAP application and ASE database components on different EC2 instances to meet your application performance requirements. This launch expands on existing Launch Wizard capability that allows you to automate deployment of SAP systems on SAP ASE database in single-node pattern.

AWS Launch Wizard offers a guided way of sizing, configuring, deploying, and scaling AWS resources for third party applications, such as Microsoft SQL Server and SAP systems, without the need to manually identify and provision individual AWS resources. This launch brings parity in supported deployment patterns of SAP NetWeaver on HANA database stack and SAP NetWeaver on ASE database stack.

To learn more about AWS Launch Wizard, visit the Launch Wizard Page.

 

​AWS Launch Wizard now supports deployment of multi-node SAP NetWeaver applications on SAP ASE database, allowing you to deploy multiple applications servers at the time of deployment. With this deployment pattern, you deploy SAP application and ASE database components on different EC2 instances to meet your application performance requirements. This launch expands on existing Launch Wizard capability that allows you to automate deployment of SAP systems on SAP ASE database in single-node pattern. AWS Launch Wizard offers a guided way of sizing, configuring, deploying, and scaling AWS resources for third party applications, such as Microsoft SQL Server and SAP systems, without the need to manually identify and provision individual AWS resources. This launch brings parity in supported deployment patterns of SAP NetWeaver on HANA database stack and SAP NetWeaver on ASE database stack. To learn more about AWS Launch Wizard, visit the Launch Wizard Page.  

Amazon Relational Database Service (Amazon RDS) for MySQL now supports MySQL minor versions 8.0.42 and 8.4.5, the latest minors released by the MySQL community. We recommend upgrading to the newer minor versions to fix known security vulnerabilities in prior versions of MySQL and to benefit from bug fixes, performance improvements, and new functionality added by the MySQL community. Learn more about the enhancements in RDS for MySQL 8.0.42 and 8.4.5 in the Amazon RDS user guide.

You can leverage automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also leverage Amazon RDS Managed Blue/Green deployments for safer, simpler, and faster updates to your MySQL instances. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments, in the Amazon RDS User Guide.

Amazon RDS for MySQL makes it simple to set up, operate, and scale MySQL deployments in the cloud. Learn more about pricing details and regional availability at Amazon RDS for MySQL. Create or update a fully managed Amazon RDS for MySQL database in the Amazon RDS Management Console.

 

​Amazon Relational Database Service (Amazon RDS) for MySQL now supports MySQL minor versions 8.0.42 and 8.4.5, the latest minors released by the MySQL community. We recommend upgrading to the newer minor versions to fix known security vulnerabilities in prior versions of MySQL and to benefit from bug fixes, performance improvements, and new functionality added by the MySQL community. Learn more about the enhancements in RDS for MySQL 8.0.42 and 8.4.5 in the Amazon RDS user guide. You can leverage automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also leverage Amazon RDS Managed Blue/Green deployments for safer, simpler, and faster updates to your MySQL instances. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments, in the Amazon RDS User Guide. Amazon RDS for MySQL makes it simple to set up, operate, and scale MySQL deployments in the cloud. Learn more about pricing details and regional availability at Amazon RDS for MySQL. Create or update a fully managed Amazon RDS for MySQL database in the Amazon RDS Management Console.  

Today, Amazon CloudWatch launched volume tiered pricing for AWS Lambda logs and support for additional delivery destinations. The new tiered pricing is effective immediately on Lambda function logs, requiring no code or configuration changes. For example in US East (N. Virginia), Lambda logs to CloudWatch pricing starts at $0.50 per GB tiering down to $0.05 per GB.

Additionally, CloudWatch now supports Amazon S3 and Amazon Data Firehose as Lambda log delivery destinations. These new destinations provide additional flexibility in Lambda log management, and are also available at volume tiered pricing. Again in US East (N. Virginia), pricing starts at $0.25 per GB tiering down to $0.05 per GB.

CloudWatch Logs volume tiered pricing is available in all AWS Regions where CloudWatch Logs and Lambda are available.

To learn more about these launches, visit the documentation, launch blog post, and the CloudWatch Logs pricing page.

 

​Today, Amazon CloudWatch launched volume tiered pricing for AWS Lambda logs and support for additional delivery destinations. The new tiered pricing is effective immediately on Lambda function logs, requiring no code or configuration changes. For example in US East (N. Virginia), Lambda logs to CloudWatch pricing starts at $0.50 per GB tiering down to $0.05 per GB. Additionally, CloudWatch now supports Amazon S3 and Amazon Data Firehose as Lambda log delivery destinations. These new destinations provide additional flexibility in Lambda log management, and are also available at volume tiered pricing. Again in US East (N. Virginia), pricing starts at $0.25 per GB tiering down to $0.05 per GB. CloudWatch Logs volume tiered pricing is available in all AWS Regions where CloudWatch Logs and Lambda are available. To learn more about these launches, visit the documentation, launch blog post, and the CloudWatch Logs pricing page.  

AWS HealthImaging announces two enhancements that make it easier to manage diverse medical imaging data in the cloud.

First, HealthImaging now supports video data, encoded per the DICOM standard. With this launch, video data can be stored in a HealthImaging data store, alongside still image data. The service supports the DICOM video formats: MPEG2, MPEG-4 AVC/H.264, HEVC/H.265, corresponding to DICOM transfer syntax UIDs 1.2.840.10008.1.2.4.100 through 1.2.840.10008.1.2.4.108. This data can be retrieved as DICOM instances (.dcm files) and directly as video objects. For more information, see the documentation.

Second, HealthImaging has added support for retrieving lossless images in the JPEG 2000 lossless format (transfer syntax UID 1.2.840.10008.1.2.4.90). The service supports retrieving both DICOM instances (.dcm files) and image frames in the JPEG 2000 lossless format. HealthImaging’s transcoding to JPEG 2000 makes it easier to interoperate with external applications that consume data in this widely adopted format.

AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers and their software partners to store, analyze, and share medical images at petabyte scale. With AWS HealthImaging, you can run your medical imaging applications at scale from a single, authoritative copy of each medical image in the cloud, while reducing total cost of ownership. To learn more, see the AWS HealthImaging Developer Guide.

AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland).

 

​AWS HealthImaging announces two enhancements that make it easier to manage diverse medical imaging data in the cloud. First, HealthImaging now supports video data, encoded per the DICOM standard. With this launch, video data can be stored in a HealthImaging data store, alongside still image data. The service supports the DICOM video formats: MPEG2, MPEG-4 AVC/H.264, HEVC/H.265, corresponding to DICOM transfer syntax UIDs 1.2.840.10008.1.2.4.100 through 1.2.840.10008.1.2.4.108. This data can be retrieved as DICOM instances (.dcm files) and directly as video objects. For more information, see the documentation. Second, HealthImaging has added support for retrieving lossless images in the JPEG 2000 lossless format (transfer syntax UID 1.2.840.10008.1.2.4.90). The service supports retrieving both DICOM instances (.dcm files) and image frames in the JPEG 2000 lossless format. HealthImaging’s transcoding to JPEG 2000 makes it easier to interoperate with external applications that consume data in this widely adopted format. AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers and their software partners to store, analyze, and share medical images at petabyte scale. With AWS HealthImaging, you can run your medical imaging applications at scale from a single, authoritative copy of each medical image in the cloud, while reducing total cost of ownership. To learn more, see the AWS HealthImaging Developer Guide. AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland).  

Amazon Aurora now supports PostgreSQL major version 17 (17.4). This release contains product improvements and bug fixes from the PostgreSQL community along with Aurora- specific feature improvements such as enhanced memory management, faster storage metadata initialization during failovers, and optimized write-heavy workloads on new Graviton 4 high-end instances. This release also includes new features for Babelfish, Aurora-specific security fixes, and updates to key extensions including pgvector 0.8.0 and postgis 3.5.1. Please refer to the PostgreSQL community announcement and Amazon Aurora PostgreSQL updates for more details about the release.

To use the new version, create a new Aurora PostgreSQL-compatible database with just a few clicks in the Amazon RDS Management Console. Please review the Aurora documentation to learn more about upgrading and refer the Aurora version policy to help decide how often to upgrade and plan your upgrade process. PostgreSQL 17.4 is available in all commercial AWS Regions and AWS GovCloud (US) Regions.

Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.
 

 

​Amazon Aurora now supports PostgreSQL major version 17 (17.4). This release contains product improvements and bug fixes from the PostgreSQL community along with Aurora- specific feature improvements such as enhanced memory management, faster storage metadata initialization during failovers, and optimized write-heavy workloads on new Graviton 4 high-end instances. This release also includes new features for Babelfish, Aurora-specific security fixes, and updates to key extensions including pgvector 0.8.0 and postgis 3.5.1. Please refer to the PostgreSQL community announcement and Amazon Aurora PostgreSQL updates for more details about the release. To use the new version, create a new Aurora PostgreSQL-compatible database with just a few clicks in the Amazon RDS Management Console. Please review the Aurora documentation to learn more about upgrading and refer the Aurora version policy to help decide how often to upgrade and plan your upgrade process. PostgreSQL 17.4 is available in all commercial AWS Regions and AWS GovCloud (US) Regions. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.    

Amazon Neptune Database now supports Graviton3-based R7g and Graviton4-based R8g database instances for Amazon Neptune engine versions 1.4.5 or above, and priced -16% vs R6g.

Graviton3-based R7g are the first AWS database instances to feature the latest DDR5 memory, which provides 50% more memory bandwidth compared to DDR4, enabling high-speed access to data in memory. R7g database instances offer up to 30Gbps enhanced networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Graviton4-based R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory.

R7g instances for Neptune are now available US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Hong Kong), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Mumbai), Asia Pacific (Hyderabad), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Malaysia), Canada (Central), Europe (Frankfurt), Europe (Stockholm), Europe (Spain), and South America (São Paulo). R8g instances for Neptune are now available in: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Asia Pacific (Sydney), Europe (Frankfurt), Europe (Stockholm), and Europe (Spain). You can launch R7g and R8g instances for Neptune using the AWS Management Console or using the AWS CLI. Upgrading a Neptune cluster to R7g or R8g instances requires a simple instance type modification for Neptune engine versions 1.4.5 or higher. For more information on pricing and regional availability, refer to the Amazon Neptune pricing page.
 

 

​Amazon Neptune Database now supports Graviton3-based R7g and Graviton4-based R8g database instances for Amazon Neptune engine versions 1.4.5 or above, and priced -16% vs R6g. Graviton3-based R7g are the first AWS database instances to feature the latest DDR5 memory, which provides 50% more memory bandwidth compared to DDR4, enabling high-speed access to data in memory. R7g database instances offer up to 30Gbps enhanced networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Graviton4-based R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory. R7g instances for Neptune are now available US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Hong Kong), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Mumbai), Asia Pacific (Hyderabad), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Malaysia), Canada (Central), Europe (Frankfurt), Europe (Stockholm), Europe (Spain), and South America (São Paulo). R8g instances for Neptune are now available in: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Asia Pacific (Sydney), Europe (Frankfurt), Europe (Stockholm), and Europe (Spain). You can launch R7g and R8g instances for Neptune using the AWS Management Console or using the AWS CLI. Upgrading a Neptune cluster to R7g or R8g instances requires a simple instance type modification for Neptune engine versions 1.4.5 or higher. For more information on pricing and regional availability, refer to the Amazon Neptune pricing page.    

Starting today, you can use Amazon Route 53 Resolver DNS Firewall and DNS Firewall Advanced in the Asia Pacific (Thailand) and Mexico (Central) Regions, to govern and filter outbound DNS traffic for your Amazon Virtual Private Cloud (VPC).

Route 53 Resolver DNS Firewall is a managed service that enables you to block DNS queries made for domains identified as low-reputation or suspected to be malicious, and to allow queries for trusted domains. In addition, Route 53 Resolver DNS Firewall Advanced is a capability of DNS Firewall that allows you to detect and block DNS traffic associated with Domain Generation Algorithms (DGA) and DNS Tunneling threats. DNS Firewall can be enabled only for Route 53 Resolver, which is a recursive DNS server that is available by default in all Amazon Virtual Private Clouds (VPCs). The Route 53 Resolver responds to DNS queries from AWS resources within a VPC for public DNS records, VPC-specific domain names, and Route 53 private hosted zones.

See here for the list of AWS Regions where Route 53 Resolver DNS Firewall is available. Visit our product page and documentation to learn more about Amazon Route 53 Resolver DNS Firewall and its pricing.

 

​Starting today, you can use Amazon Route 53 Resolver DNS Firewall and DNS Firewall Advanced in the Asia Pacific (Thailand) and Mexico (Central) Regions, to govern and filter outbound DNS traffic for your Amazon Virtual Private Cloud (VPC). Route 53 Resolver DNS Firewall is a managed service that enables you to block DNS queries made for domains identified as low-reputation or suspected to be malicious, and to allow queries for trusted domains. In addition, Route 53 Resolver DNS Firewall Advanced is a capability of DNS Firewall that allows you to detect and block DNS traffic associated with Domain Generation Algorithms (DGA) and DNS Tunneling threats. DNS Firewall can be enabled only for Route 53 Resolver, which is a recursive DNS server that is available by default in all Amazon Virtual Private Clouds (VPCs). The Route 53 Resolver responds to DNS queries from AWS resources within a VPC for public DNS records, VPC-specific domain names, and Route 53 private hosted zones. See here for the list of AWS Regions where Route 53 Resolver DNS Firewall is available. Visit our product page and documentation to learn more about Amazon Route 53 Resolver DNS Firewall and its pricing.  

Amazon Connect outbound campaigns now offers reporting on recipients and campaign executions along with additional metrics for tracking progress and troubleshooting issues. These capabilities are available in the Contact Lens dashboards and allow you to easily monitor campaign engagement by tracking total outreach against the total number of recipients targeted. You can drill down into your campaign and examine performance data for each campaign execution – for example, if you run a campaign every week for a month, you can drill down to view campaign performance for each week. You can also identify and resolve any delivery issues against each campaign – for example, out of the 20 delivery issues, you now know 12 had ineligible timezones, and 8 reached communication limit thresholds. The real-time campaigns dashboard shows the journey of your campaign, from how many recipients you targeted to how many you reached. All new metrics are also available through the GetMetricDataV2 API and Zero-ETL data lake for custom reporting or integrations with other data sources.

These enhanced outbound campaign analytics are available in all AWS regions where Amazon Connect outbound campaigns is available. For more information about outbound campaign analytics, consult the Amazon Connect Administrator Guide and Amazon Connect API Reference. To learn more about Amazon Connect Outbound Campaigns, please visit the outbound campaigns webpage.

 

​Amazon Connect outbound campaigns now offers reporting on recipients and campaign executions along with additional metrics for tracking progress and troubleshooting issues. These capabilities are available in the Contact Lens dashboards and allow you to easily monitor campaign engagement by tracking total outreach against the total number of recipients targeted. You can drill down into your campaign and examine performance data for each campaign execution – for example, if you run a campaign every week for a month, you can drill down to view campaign performance for each week. You can also identify and resolve any delivery issues against each campaign – for example, out of the 20 delivery issues, you now know 12 had ineligible timezones, and 8 reached communication limit thresholds. The real-time campaigns dashboard shows the journey of your campaign, from how many recipients you targeted to how many you reached. All new metrics are also available through the GetMetricDataV2 API and Zero-ETL data lake for custom reporting or integrations with other data sources. These enhanced outbound campaign analytics are available in all AWS regions where Amazon Connect outbound campaigns is available. For more information about outbound campaign analytics, consult the Amazon Connect Administrator Guide and Amazon Connect API Reference. To learn more about Amazon Connect Outbound Campaigns, please visit the outbound campaigns webpage.  

Model Distillation is the process of transferring knowledge from a more capable model (teacher) to a less capable one (student) with the goal to make the faster and cost-efficient student model as performant as the teacher for a specific use-case. With general availability, we now add support for the following new models: Amazon Nova Premier (teacher) and Nova Pro (student), Claude 3.5 Sonnet v2 (teacher), Llama 3.3 70B (teacher) and Llama 3.2 1B/3B (student). Amazon Bedrock Model Distillation now enables smaller models to accurately predict function calling for Agents use cases while helping to deliver substantially faster response times and lower operational costs. Distilled models in Amazon Bedrock are up to 500% faster and 75% less expensive than original models, with less than 2% accuracy loss for use cases like RAG. In addition to RAG use cases, Model Distillation also adds support for data augmentation for Agents use cases for function calling prediction.

Amazon Bedrock Model Distillation offers a single workflow that automates the process needed to generate teacher responses, adds data synthesis to improve teacher responses, and then trains the student model. Amazon Bedrock Model Distillation may choose to apply different data synthesis methods that are best suited for your use-case to create a distilled model that approximately matches the advanced model for the specific use-case. 

Learn more in our documentation, website, and blog.

 

​Model Distillation is the process of transferring knowledge from a more capable model (teacher) to a less capable one (student) with the goal to make the faster and cost-efficient student model as performant as the teacher for a specific use-case. With general availability, we now add support for the following new models: Amazon Nova Premier (teacher) and Nova Pro (student), Claude 3.5 Sonnet v2 (teacher), Llama 3.3 70B (teacher) and Llama 3.2 1B/3B (student). Amazon Bedrock Model Distillation now enables smaller models to accurately predict function calling for Agents use cases while helping to deliver substantially faster response times and lower operational costs. Distilled models in Amazon Bedrock are up to 500% faster and 75% less expensive than original models, with less than 2% accuracy loss for use cases like RAG. In addition to RAG use cases, Model Distillation also adds support for data augmentation for Agents use cases for function calling prediction. Amazon Bedrock Model Distillation offers a single workflow that automates the process needed to generate teacher responses, adds data synthesis to improve teacher responses, and then trains the student model. Amazon Bedrock Model Distillation may choose to apply different data synthesis methods that are best suited for your use-case to create a distilled model that approximately matches the advanced model for the specific use-case.  Learn more in our documentation, website, and blog.