Today, AWS launched the ability for Amazon VPC IP Address Manager (IPAM) to automatically acquire non-overlapping IP address allocations from Infoblox Universal IPAM. This feature minimizes manual processes between cloud and on-premises administrators, reducing the turnaround time.

With this launch, you can automatically acquire non-overlapping IP addresses from your on-premises Infoblox Universal IPAM into your top-level AWS IPAM pool and organize them into regional pools based on your business requirements. When you acquire non-overlapping IPs, you reduce the risk of service disruptions because your IPs don’t conflict with on-premise IP addresses. Previously, in hybrid cloud environments, administrators had to use offline means such as tickets or emails to request and allocate IP addresses, which was often error-prone and time-consuming. This integration automates the manual process, improving operational efficiency.

This feature is available in all AWS Regions where Amazon VPC IPAM is supported, excluding 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 launched the ability for Amazon VPC IP Address Manager (IPAM) to automatically acquire non-overlapping IP address allocations from Infoblox Universal IPAM. This feature minimizes manual processes between cloud and on-premises administrators, reducing the turnaround time. With this launch, you can automatically acquire non-overlapping IP addresses from your on-premises Infoblox Universal IPAM into your top-level AWS IPAM pool and organize them into regional pools based on your business requirements. When you acquire non-overlapping IPs, you reduce the risk of service disruptions because your IPs don’t conflict with on-premise IP addresses. Previously, in hybrid cloud environments, administrators had to use offline means such as tickets or emails to request and allocate IP addresses, which was often error-prone and time-consuming. This integration automates the manual process, improving operational efficiency. This feature is available in all AWS Regions where Amazon VPC IPAM is supported, excluding 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.  

Starting today, Amazon EC2 High Memory U7i instances with 24TB of memory (u7in-24tb.224xlarge) are now available in the US East (Ohio) region. U7in-24tb instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7in-24tb instances offer 24TB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment.

U7in-24tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 200Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server..

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

 

​Starting today, Amazon EC2 High Memory U7i instances with 24TB of memory (u7in-24tb.224xlarge) are now available in the US East (Ohio) region. U7in-24tb instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7in-24tb instances offer 24TB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7in-24tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 200Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.. To learn more about U7i instances, visit the High Memory instances page.  

AWS Transform for VMware now allows customers to automatically generate network configurations that can be directly imported into the Landing Zone Accelerator on AWS solution (LZA). Building on AWS Transform’s existing support for infrastructure-as-code generation in AWS CloudFormation, AWS CDK, and Terraform formats, this new capability specifically enables automatic transformation of VMware network environments into LZA-compatible network configuration YAML files. These YAML configurations can be directly deployed through LZA’s deployment pipeline, streamlining the process of setting up your cloud infrastructure.

AWS Transform for VMware is an agentic AI service that automates the discovery, planning, and migration of VMware workloads, accelerating infrastructure modernization with increased speed and confidence. Landing Zone Accelerator on AWS solution (LZA) automates the setup of a secure, multi-account AWS environment using AWS best practices. Migrating workloads to AWS traditionally requires you to manually recreate network configurations while maintaining operational and compliance consistency. The service now automates the generation of LZA network configurations, reducing manual effort, potential configuration errors, and deployment time while ensuring compliance with enterprise security standards.

The LZA configuration generation capability is available in all AWS Regions where the service is offered.

To learn more, visit the AWS Transform for VMware product page, read the user guide, or get started in the AWS Transform web experience.

 

​AWS Transform for VMware now allows customers to automatically generate network configurations that can be directly imported into the Landing Zone Accelerator on AWS solution (LZA). Building on AWS Transform’s existing support for infrastructure-as-code generation in AWS CloudFormation, AWS CDK, and Terraform formats, this new capability specifically enables automatic transformation of VMware network environments into LZA-compatible network configuration YAML files. These YAML configurations can be directly deployed through LZA’s deployment pipeline, streamlining the process of setting up your cloud infrastructure. AWS Transform for VMware is an agentic AI service that automates the discovery, planning, and migration of VMware workloads, accelerating infrastructure modernization with increased speed and confidence. Landing Zone Accelerator on AWS solution (LZA) automates the setup of a secure, multi-account AWS environment using AWS best practices. Migrating workloads to AWS traditionally requires you to manually recreate network configurations while maintaining operational and compliance consistency. The service now automates the generation of LZA network configurations, reducing manual effort, potential configuration errors, and deployment time while ensuring compliance with enterprise security standards. The LZA configuration generation capability is available in all AWS Regions where the service is offered. To learn more, visit the AWS Transform for VMware product page, read the user guide, or get started in the AWS Transform web experience.  

AWS Lambda now supports building serverless applications using Rust. Previously, AWS classified Rust support in Lambda as ‘experimental’ and did not recommend using Rust for production workloads. With this launch, Rust support in Lambda is now Generally Available, backed by AWS Support and the Lambda SLA.

Rust is a popular programming language, offering high performance, memory efficiency, compile-time code safety features, and a mature package management and tooling ecosystem. This makes Rust an ideal choice for developers building performance-sensitive serverless applications. Developers can now build business-critical serverless applications in Rust and run them in Lambda, taking advantage of Lambda’s built-in event source integrations, fast scaling from zero, automatic patching, and usage-based pricing.

Lambda support for Rust is available in all AWS Regions, including the AWS GovCloud (US) Regions and the China Regions.

For more information, see Building Lambda functions with Rust in the Lambda documentation, or our blog post Building serverless applications with Rust on AWS Lambda.

 

​AWS Lambda now supports building serverless applications using Rust. Previously, AWS classified Rust support in Lambda as ‘experimental’ and did not recommend using Rust for production workloads. With this launch, Rust support in Lambda is now Generally Available, backed by AWS Support and the Lambda SLA. Rust is a popular programming language, offering high performance, memory efficiency, compile-time code safety features, and a mature package management and tooling ecosystem. This makes Rust an ideal choice for developers building performance-sensitive serverless applications. Developers can now build business-critical serverless applications in Rust and run them in Lambda, taking advantage of Lambda’s built-in event source integrations, fast scaling from zero, automatic patching, and usage-based pricing. Lambda support for Rust is available in all AWS Regions, including the AWS GovCloud (US) Regions and the China Regions. For more information, see Building Lambda functions with Rust in the Lambda documentation, or our blog post Building serverless applications with Rust on AWS Lambda.  

Amazon Elastic Container Service (Amazon ECS) now includes enhancements that improve service availability during rolling deployments. These enhancements help maintain availability when new application version tasks are failing, when current tasks are unexpectedly terminated, or when scale-out is triggered during deployments.

Previously, when tasks in your currently running version became unhealthy or were terminated during a rolling deployment, ECS would attempt to replace them with the new version to prioritize deployment progress. If the new version could not launch successfully—such as when new tasks fail health checks or fail to start—these replacements would fail and your service availability could drop. ECS now replaces unhealthy or terminated tasks using the same service revision they belong to. Unhealthy tasks in your currently running version are replaced with healthy tasks from that same version, independent of the new version’s status. Additionally, when Application Auto Scaling triggers during a rolling deployment, ECS applies scale-out to both service revisions, ensuring your currently running version can handle increased load even if the new version is failing.

These improvements respect your service’s maximumPercent and minimumHealthyPercent settings. These enhancements are enabled by default for all services using the rolling deployment strategy and are available in all AWS Regions. To learn more about rolling-update deployments, refer Link.

 

​Amazon Elastic Container Service (Amazon ECS) now includes enhancements that improve service availability during rolling deployments. These enhancements help maintain availability when new application version tasks are failing, when current tasks are unexpectedly terminated, or when scale-out is triggered during deployments.
Previously, when tasks in your currently running version became unhealthy or were terminated during a rolling deployment, ECS would attempt to replace them with the new version to prioritize deployment progress. If the new version could not launch successfully—such as when new tasks fail health checks or fail to start—these replacements would fail and your service availability could drop. ECS now replaces unhealthy or terminated tasks using the same service revision they belong to. Unhealthy tasks in your currently running version are replaced with healthy tasks from that same version, independent of the new version’s status. Additionally, when Application Auto Scaling triggers during a rolling deployment, ECS applies scale-out to both service revisions, ensuring your currently running version can handle increased load even if the new version is failing.
These improvements respect your service’s maximumPercent and minimumHealthyPercent settings. These enhancements are enabled by default for all services using the rolling deployment strategy and are available in all AWS Regions. To learn more about rolling-update deployments, refer Link.  

AWS IoT Core, AWS IoT Device Management, and AWS IoT Device Defender have expanded support for Virtual Private Cloud (VPC) endpoints and IPv6. Developers can now use AWS PrivateLink to establish VPC endpoints for all data plane operations, management APIs, and credential provider. This enhancement allows IoT workloads to operate entirely within virtual private clouds without traversing the public internet, helping strengthen the security posture for IoT deployments.

Additionally, IPv6 support for both VPC and public endpoints gives developers the flexibility to connect IoT devices and applications using either IPv6 or IPv4. This helps organizations meet local requirements for IPv6 while maintaining compatibility with existing IPv4 infrastructure.

These features can be configured through the AWS Management Console, AWS CLI, and AWS CloudFormation. The functionality is now generally available in all AWS Regions where the relevant AWS IoT services are offered. For more information about the IPv6 support and VPCe support, customers can visit the AWS IoT technical documentation pages. For information about PrivateLink pricing, visit the AWS PrivateLink pricing page.

 

​AWS IoT Core, AWS IoT Device Management, and AWS IoT Device Defender have expanded support for Virtual Private Cloud (VPC) endpoints and IPv6. Developers can now use AWS PrivateLink to establish VPC endpoints for all data plane operations, management APIs, and credential provider. This enhancement allows IoT workloads to operate entirely within virtual private clouds without traversing the public internet, helping strengthen the security posture for IoT deployments. Additionally, IPv6 support for both VPC and public endpoints gives developers the flexibility to connect IoT devices and applications using either IPv6 or IPv4. This helps organizations meet local requirements for IPv6 while maintaining compatibility with existing IPv4 infrastructure. These features can be configured through the AWS Management Console, AWS CLI, and AWS CloudFormation. The functionality is now generally available in all AWS Regions where the relevant AWS IoT services are offered. For more information about the IPv6 support and VPCe support, customers can visit the AWS IoT technical documentation pages. For information about PrivateLink pricing, visit the AWS PrivateLink pricing page.  

Amazon RDS Blue/Green deployments now support safer, simpler, and faster updates for your Aurora Global Databases. With just a few clicks, you can create a staging (green) environment that mirrors your production (blue) Aurora Global Database, including primary and all secondary regions. When you’re ready to make your staging environment the new production environment, perform a blue/green switchover. This operation transitions your primary and all secondary regions to the green environment, which now serves as the active production environment. Your application begins accessing it immediately without any configuration changes, minimizing operational overhead.

With Global Database, a single Aurora cluster can span multiple AWS Regions, providing disaster recovery for your applications in case of single Region impairment and enabling fast local reads for globally distributed applications. With this launch, you can perform critical database operations including major and minor version upgrades, OS updates, parameter modifications, instance type validations, and schema changes with minimal downtime. During blue/green switchover, Aurora automatically renames clusters, instances, and endpoints to match the original production environment, enabling applications to continue operating without any modifications. You can leverage this capability using the AWS Management console, SDK, or CLI.

This capability is available in Amazon Aurora MySQL-Compatible Edition and Amazon Aurora PostgreSQL-Compatible Edition versions that support the Aurora Global Database configuration and in all commercial AWS Regions and AWS GovCloud (US) Regions.

Start planning your next Global Database upgrade using RDS Blue/Green deployments by following the steps in the blog. For more details, refer to our documentation.

 

​Amazon RDS Blue/Green deployments now support safer, simpler, and faster updates for your Aurora Global Databases. With just a few clicks, you can create a staging (green) environment that mirrors your production (blue) Aurora Global Database, including primary and all secondary regions. When you’re ready to make your staging environment the new production environment, perform a blue/green switchover. This operation transitions your primary and all secondary regions to the green environment, which now serves as the active production environment. Your application begins accessing it immediately without any configuration changes, minimizing operational overhead. With Global Database, a single Aurora cluster can span multiple AWS Regions, providing disaster recovery for your applications in case of single Region impairment and enabling fast local reads for globally distributed applications. With this launch, you can perform critical database operations including major and minor version upgrades, OS updates, parameter modifications, instance type validations, and schema changes with minimal downtime. During blue/green switchover, Aurora automatically renames clusters, instances, and endpoints to match the original production environment, enabling applications to continue operating without any modifications. You can leverage this capability using the AWS Management console, SDK, or CLI. This capability is available in Amazon Aurora MySQL-Compatible Edition and Amazon Aurora PostgreSQL-Compatible Edition versions that support the Aurora Global Database configuration and in all commercial AWS Regions and AWS GovCloud (US) Regions. Start planning your next Global Database upgrade using RDS Blue/Green deployments by following the steps in the blog. For more details, refer to our documentation.  

Amazon SageMaker Catalog now supports read and write access to Amazon S3 general purpose buckets. This capability helps data scientists and analysts search for unstructured data, process it alongside structured datasets, and share transformed datasets with other teams. Data publishers gain additional controls to support analytics and generative AI workflows within SageMaker Unified Studio while maintaining security and governance controls over shared data. 

When approving subscription requests or directly sharing S3 data within the SageMaker Catalog, data producers can choose to grant read-only or read and write access. If granted read and write access, data consumers can process datasets in SageMaker and store the results back to the S3 bucket or folder. The data can then be published and automatically discoverable by other teams. This capability is now available in all AWS Regions where Amazon SageMaker Unified Studio is supported. To get started, you can log into SageMaker Unified Studio, or you can use the Amazon DataZone API, SDK, or AWS CLI. To learn more, see the SageMaker Unified Studio guide.

 

​Amazon SageMaker Catalog now supports read and write access to Amazon S3 general purpose buckets. This capability helps data scientists and analysts search for unstructured data, process it alongside structured datasets, and share transformed datasets with other teams. Data publishers gain additional controls to support analytics and generative AI workflows within SageMaker Unified Studio while maintaining security and governance controls over shared data. 
When approving subscription requests or directly sharing S3 data within the SageMaker Catalog, data producers can choose to grant read-only or read and write access. If granted read and write access, data consumers can process datasets in SageMaker and store the results back to the S3 bucket or folder. The data can then be published and automatically discoverable by other teams. This capability is now available in all AWS Regions where Amazon SageMaker Unified Studio is supported. To get started, you can log into SageMaker Unified Studio, or you can use the Amazon DataZone API, SDK, or AWS CLI. To learn more, see the SageMaker Unified Studio guide.  

Amazon Simple Queue Service (Amazon SQS) now allows customers to make API requests over Internet Protocol version 6 (IPv6) in the AWS GovCloud (US) Regions. The new endpoints have also been validated under the Federal Information Processing Standard (FIPS) 140-3 program.

Amazon SQS is a fully managed message queuing service that enables decoupling and scaling of distributed systems, microservices, and serverless applications. With this update, customers have the option of using either IPv6 or IPv4 when sending requests over dual-stack public or VPC endpoints.

Amazon SQS now supports IPv6 in all Regions where the service is available, including AWS Commercial, AWS GovCloud (US) and China Regions. For more information on using IPv6 with Amazon SQS, please refer to our developer guide. 

 

​Amazon Simple Queue Service (Amazon SQS) now allows customers to make API requests over Internet Protocol version 6 (IPv6) in the AWS GovCloud (US) Regions. The new endpoints have also been validated under the Federal Information Processing Standard (FIPS) 140-3 program. Amazon SQS is a fully managed message queuing service that enables decoupling and scaling of distributed systems, microservices, and serverless applications. With this update, customers have the option of using either IPv6 or IPv4 when sending requests over dual-stack public or VPC endpoints. Amazon SQS now supports IPv6 in all Regions where the service is available, including AWS Commercial, AWS GovCloud (US) and China Regions. For more information on using IPv6 with Amazon SQS, please refer to our developer guide.   

Amazon DocumentDB (with MongoDB compatibility) announces version 8.0, which now offers added support for drivers supporting the MongoDB API versions 6.0, 7.0, and 8.0. Amazon DocumentDB 8.0 also improves query latency by up to 7x and compression ratio by up to 5x, enabling you to build high-performance applications at a lower cost. 

The following are features and capabilities introduced in Amazon DocumentDB 8.0:

• Compatibility with MongoDB 8.0: Amazon DocumentDB 8.0 provides compatibility with MongoDB 8.0 by adding support for MongoDB 8.0 API drivers. Amazon DocumentDB 8.0 also supports applications that are built using MongoDB API versions 6.0 and 7.0.
• Planner Version3: New query planner in Amazon DocumentDB 8.0 extends performance improvements to aggregation stage operators, along with supporting aggregation pipeline optimizations and distinct commands.
• New aggregation stages and operators: Amazon DocumentDB 8.0 offers 6 new aggregation stages: $replaceWith, $vectorSearch, $merge, $set, $unset, $bucket, and 3 new aggregation operators $pow, $rand, $dateTrunc.
• Compression: Support for dictionary-based compression through the Zstandard compression algorithm improves compression ratio by up to 5x, thus improving storage efficiency and reducing I/O costs.
• New capabilities: Amazon DocumentDB 8.0 supports collation and views.
• A new version of text index: Text index v2 in Amazon DocumentDB 8.0 introduces additional tokens, enhancing text search capabilities.
• Vector search improvements: Through parallel vector index build, Amazon DocumentDB 8.0 reduces index build time by up to 30x.

You can use AWS Database Migration Service (DMS) to upgrade your Amazon DocumentDB 5.0 instance-based clusters to Amazon DocumentDB 8.0 clusters. Please see upgrading your DocumentDB cluster to learn more. Amazon DocumentDB 8.0 is available in all AWS Regions where Amazon DocumentDB is available. To learn more about Amazon DocumentDB 8.0 visit the documentation.

 

​Amazon DocumentDB (with MongoDB compatibility) announces version 8.0, which now offers added support for drivers supporting the MongoDB API versions 6.0, 7.0, and 8.0. Amazon DocumentDB 8.0 also improves query latency by up to 7x and compression ratio by up to 5x, enabling you to build high-performance applications at a lower cost. 
The following are features and capabilities introduced in Amazon DocumentDB 8.0:

Compatibility with MongoDB 8.0: Amazon DocumentDB 8.0 provides compatibility with MongoDB 8.0 by adding support for MongoDB 8.0 API drivers. Amazon DocumentDB 8.0 also supports applications that are built using MongoDB API versions 6.0 and 7.0.
Planner Version3: New query planner in Amazon DocumentDB 8.0 extends performance improvements to aggregation stage operators, along with supporting aggregation pipeline optimizations and distinct commands.
New aggregation stages and operators: Amazon DocumentDB 8.0 offers 6 new aggregation stages: $replaceWith, $vectorSearch, $merge, $set, $unset, $bucket, and 3 new aggregation operators $pow, $rand, $dateTrunc.
Compression: Support for dictionary-based compression through the Zstandard compression algorithm improves compression ratio by up to 5x, thus improving storage efficiency and reducing I/O costs.
New capabilities: Amazon DocumentDB 8.0 supports collation and views.
A new version of text index: Text index v2 in Amazon DocumentDB 8.0 introduces additional tokens, enhancing text search capabilities.
Vector search improvements: Through parallel vector index build, Amazon DocumentDB 8.0 reduces index build time by up to 30x.

You can use AWS Database Migration Service (DMS) to upgrade your Amazon DocumentDB 5.0 instance-based clusters to Amazon DocumentDB 8.0 clusters. Please see upgrading your DocumentDB cluster to learn more. Amazon DocumentDB 8.0 is available in all AWS Regions where Amazon DocumentDB is available. To learn more about Amazon DocumentDB 8.0 visit the documentation.