AWS Deadline Cloud now supports submitting VRED rendering jobs from within Autodesk VRED as well as using the Deadline Cloud Client. AWS Deadline Cloud is a fully-managed service that simplifies render management for teams creating computer-generated graphics and visual effects for films, television and broadcasting, web content, and design. This new integration with Autodesk VRED extends AWS Deadline Cloud’s capabilities to support Automotive and Manufacturing customer segments, which demand high-fidelity 3D design visualization at scale.

With AWS Deadline Cloud, you can submit Autodesk VRED render jobs from anywhere without having to manage your own render farm infrastructure. Autodesk VRED brings your complex 3D visualization data to life for collaboratively developing digital prototypes. You can now send them to AWS Deadline Cloud to rapidly render visualizations for review and iteration. The Deadline Cloud for VRED Submitter (for Windows) is available via an installer and via the AWS Deadline Cloud GitHub repository.

To learn more, please see the AWS Deadline Cloud documentation and the Deadline Cloud for VRED GitHub repository.

 

​AWS Deadline Cloud now supports submitting VRED rendering jobs from within Autodesk VRED as well as using the Deadline Cloud Client. AWS Deadline Cloud is a fully-managed service that simplifies render management for teams creating computer-generated graphics and visual effects for films, television and broadcasting, web content, and design. This new integration with Autodesk VRED extends AWS Deadline Cloud’s capabilities to support Automotive and Manufacturing customer segments, which demand high-fidelity 3D design visualization at scale. With AWS Deadline Cloud, you can submit Autodesk VRED render jobs from anywhere without having to manage your own render farm infrastructure. Autodesk VRED brings your complex 3D visualization data to life for collaboratively developing digital prototypes. You can now send them to AWS Deadline Cloud to rapidly render visualizations for review and iteration. The Deadline Cloud for VRED Submitter (for Windows) is available via an installer and via the AWS Deadline Cloud GitHub repository. To learn more, please see the AWS Deadline Cloud documentation and the Deadline Cloud for VRED GitHub repository.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in the Middle East (UAE) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers.

M7i deliver up to 15% better price-performance compared to M6i. M7i instances are a great choice for workloads that need the largest instance sizes or continuous high CPU usage, such as gaming servers, CPU-based machine learning (ML), and video-streaming. M7i offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads.

To learn more, visit Amazon EC2 M7i Instances. To get started, see the AWS Management Console.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in the Middle East (UAE) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers. M7i deliver up to 15% better price-performance compared to M6i. M7i instances are a great choice for workloads that need the largest instance sizes or continuous high CPU usage, such as gaming servers, CPU-based machine learning (ML), and video-streaming. M7i offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads. To learn more, visit Amazon EC2 M7i Instances. To get started, see the AWS Management Console.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in Africa (Cape Town), Asia Pacific (Seoul), Europe (Milan) and Israel (Tel Aviv) Regions.

R7gd are powered by AWS Graviton3 processors with DDR5 memory are built on the AWS Nitro System. They are ideal for memory-intensive workloads such as open-source databases, in-memory caches, and real-time big data analytics and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud.

To learn more, see Amazon R7gd Instances. To get started, see the AWS Management Console. 

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in Africa (Cape Town), Asia Pacific (Seoul), Europe (Milan) and Israel (Tel Aviv) Regions. R7gd are powered by AWS Graviton3 processors with DDR5 memory are built on the AWS Nitro System. They are ideal for memory-intensive workloads such as open-source databases, in-memory caches, and real-time big data analytics and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud. To learn more, see Amazon R7gd Instances. To get started, see the AWS Management Console.   

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in Asia Pacific (Seoul) Region.

These Graviton3-based instances with DDR5 memory are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud.

To learn more, see Amazon EC2 M7gd instances. To get started, see the AWS Management Console.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in Asia Pacific (Seoul) Region. These Graviton3-based instances with DDR5 memory are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud. To learn more, see Amazon EC2 M7gd instances. To get started, see the AWS Management Console.  

Amazon OpenSearch Serverless announces support for Neural Search, Hybrid Search, Workflow API, and AI connectors. This new set of APIs facilitates use cases such as retrieval augmented generation (RAG) and semantic search.

Neural search enables semantic queries through text and images instead of vectors. Neural search uses a high-level API with connectors to Amazon SageMaker, Amazon Bedrock, and other AI services to generate enrichments like dense or sparse vectors during query and ingestion. Hybrid search enables combining lexical, neural, and k-NN (vector) queries to deliver higher search relevancy. The workflow API allows you to package OpenSearch AI resources like models, connectors, and pipelines into templates to automate multi-step configurations required to enable AI features such as neural search, and simplified integration with specific model providers like Amazon Bedrock, Cohere, OpenAI or DeepSeek.

Neural Search, Hybrid Search, Workflow API, and AI connectors are enabled for all serverless collections in the following regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (Spain), Europe (Stockholm). Check the AWS Regional Services List for availability in your region.

For more information about these features, please see the documentation for Neural Search, Hybrid Search, Workflow API, and AI connectors. To learn more about Amazon OpenSearch Serverless, please visit the product page.

 

​Amazon OpenSearch Serverless announces support for Neural Search, Hybrid Search, Workflow API, and AI connectors. This new set of APIs facilitates use cases such as retrieval augmented generation (RAG) and semantic search. Neural search enables semantic queries through text and images instead of vectors. Neural search uses a high-level API with connectors to Amazon SageMaker, Amazon Bedrock, and other AI services to generate enrichments like dense or sparse vectors during query and ingestion. Hybrid search enables combining lexical, neural, and k-NN (vector) queries to deliver higher search relevancy. The workflow API allows you to package OpenSearch AI resources like models, connectors, and pipelines into templates to automate multi-step configurations required to enable AI features such as neural search, and simplified integration with specific model providers like Amazon Bedrock, Cohere, OpenAI or DeepSeek. Neural Search, Hybrid Search, Workflow API, and AI connectors are enabled for all serverless collections in the following regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (Spain), Europe (Stockholm). Check the AWS Regional Services List for availability in your region. For more information about these features, please see the documentation for Neural Search, Hybrid Search, Workflow API, and AI connectors. To learn more about Amazon OpenSearch Serverless, please visit the product page.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7g instances are available in the AWS Middle East (Bahrain), AWS Africa (Cape Town), and AWS Asia Pacific (Jakarta) regions. These instances are powered by AWS Graviton3 processors that provide up to 25% better compute performance compared to AWS Graviton2 processors, and built on top of the the AWS Nitro System, a collection of AWS designed innovations that deliver efficient, flexible, and secure cloud services with isolated multi-tenancy, private networking, and fast local storage.

Amazon EC2 Graviton3 instances also use up to 60% less energy to reduce your cloud carbon footprint for the same performance than comparable EC2 instances. For increased scalability, these instances are available in 9 different instance sizes, including bare metal, and offer up to 30 Gbps networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (EBS).

To learn more, see Amazon EC2 C7g. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7g instances are available in the AWS Middle East (Bahrain), AWS Africa (Cape Town), and AWS Asia Pacific (Jakarta) regions. These instances are powered by AWS Graviton3 processors that provide up to 25% better compute performance compared to AWS Graviton2 processors, and built on top of the the AWS Nitro System, a collection of AWS designed innovations that deliver efficient, flexible, and secure cloud services with isolated multi-tenancy, private networking, and fast local storage. Amazon EC2 Graviton3 instances also use up to 60% less energy to reduce your cloud carbon footprint for the same performance than comparable EC2 instances. For increased scalability, these instances are available in 9 different instance sizes, including bare metal, and offer up to 30 Gbps networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (EBS). To learn more, see Amazon EC2 C7g. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i and M7i-flex instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in Asia Pacific (Osaka) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers.

M7i-flex instances are the easiest way for you to get price-performance benefits for a majority of general-purpose workloads. They deliver up to 19% better price-performance compared to M6i. M7i-flex instances offer the most common sizes, from large to 16xlarge, and are a great first choice for applications that don’t fully utilize all compute resources such as web and application servers, virtual-desktops, batch-processing, and microservices.

M7i deliver up to 15% better price-performance compared to M6i. M7i instances are a great choice for workloads that need the largest instance sizes or continuous high CPU usage, such as gaming servers, CPU-based machine learning (ML), and video-streaming. M7i offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads.

To learn more, visit Amazon EC2 M7i Instances. To get started, see the AWS Management Console.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i and M7i-flex instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in Asia Pacific (Osaka) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers. M7i-flex instances are the easiest way for you to get price-performance benefits for a majority of general-purpose workloads. They deliver up to 19% better price-performance compared to M6i. M7i-flex instances offer the most common sizes, from large to 16xlarge, and are a great first choice for applications that don’t fully utilize all compute resources such as web and application servers, virtual-desktops, batch-processing, and microservices. M7i deliver up to 15% better price-performance compared to M6i. M7i instances are a great choice for workloads that need the largest instance sizes or continuous high CPU usage, such as gaming servers, CPU-based machine learning (ML), and video-streaming. M7i offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads. To learn more, visit Amazon EC2 M7i Instances. To get started, see the AWS Management Console.  

We’re excited to announce the general availability of two new Amazon CloudWatch metrics for AWS Outposts racks: VifConnectionStatus and VifBgpSessionState. These metrics provide you with greater visibility into the connectivity status of your Outposts racks’ Local Gateway (LGW) and Service Link Virtual Interfaces (VIFs) with your on-premises devices.

These metrics provide you with the ability to monitor Outposts VIF connectivity status directly within the CloudWatch console, without having to rely on external networking tools or coordination with other teams. You can use these metrics to set alarms, troubleshoot connectivity issues, and ensure your Outposts racks are properly integrated with your on-premises infrastructure. The VifConnectionStatus metric indicates whether an Outposts VIF is successfully connected, configured, and ready to forward traffic. A value of «1» means that the VIF is operational, while «0» means that it is not ready. The VifBgpSessionState metric shows the current state of the BGP session between the Outposts VIF and the on-premises device, with values ranging from 1 (IDLE) to 6 (ESTABLISHED).

The VifConnectionStatus and VifBgpSessionState metrics are available for all Outposts VIFs in all commercial AWS Regions where Outposts racks are available.

To get started, read this blog post and access the metrics in the CloudWatch console. To learn more, check out the CloudWatch metrics for AWS Outposts documentation for second-generation Outposts racks and first-generation Outposts racks.

 

​We’re excited to announce the general availability of two new Amazon CloudWatch metrics for AWS Outposts racks: VifConnectionStatus and VifBgpSessionState. These metrics provide you with greater visibility into the connectivity status of your Outposts racks’ Local Gateway (LGW) and Service Link Virtual Interfaces (VIFs) with your on-premises devices.
These metrics provide you with the ability to monitor Outposts VIF connectivity status directly within the CloudWatch console, without having to rely on external networking tools or coordination with other teams. You can use these metrics to set alarms, troubleshoot connectivity issues, and ensure your Outposts racks are properly integrated with your on-premises infrastructure. The VifConnectionStatus metric indicates whether an Outposts VIF is successfully connected, configured, and ready to forward traffic. A value of «1» means that the VIF is operational, while «0» means that it is not ready. The VifBgpSessionState metric shows the current state of the BGP session between the Outposts VIF and the on-premises device, with values ranging from 1 (IDLE) to 6 (ESTABLISHED).
The VifConnectionStatus and VifBgpSessionState metrics are available for all Outposts VIFs in all commercial AWS Regions where Outposts racks are available.
To get started, read this blog post and access the metrics in the CloudWatch console. To learn more, check out the CloudWatch metrics for AWS Outposts documentation for second-generation Outposts racks and first-generation Outposts racks.  

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports Cumulative Update CU20 for SQL Server 2022 (RDS version 16.00.4205.1.v1), and General Distribution Releases (GDR) for SQL Server 2016 SP3 (RDS version 13.00.6460.7.v1), SQL Server 2017 (RDS version 14.00.3495.9.v1) and SQL Server 2019 (RDS version 15.00.4435.7.v1). The new CU20 and GDR releases address the vulnerabilities described in CVE-2025-49717, CVE-2025-49718 and CVE-2025-49719. Additionally, CU20 also includes important security fixes, performance improvements, and bug fixes. For additional information, see the Microsoft SQL Server 2022 CU20 documentation and GDR release notes KB5058717, KB5058714, KB5058722 and KB5058721.

We recommend that you upgrade your Amazon RDS for SQL Server instances to these latest versions using Amazon RDS Management Console or by using the AWS SDK or CLI. You can learn more about upgrading your database instances by using Amazon RDS User Guide.

These updates are available in all AWS regions.

 

​Amazon Relational Database Service (Amazon RDS) for SQL Server now supports Cumulative Update CU20 for SQL Server 2022 (RDS version 16.00.4205.1.v1), and General Distribution Releases (GDR) for SQL Server 2016 SP3 (RDS version 13.00.6460.7.v1), SQL Server 2017 (RDS version 14.00.3495.9.v1) and SQL Server 2019 (RDS version 15.00.4435.7.v1). The new CU20 and GDR releases address the vulnerabilities described in CVE-2025-49717, CVE-2025-49718 and CVE-2025-49719. Additionally, CU20 also includes important security fixes, performance improvements, and bug fixes. For additional information, see the Microsoft SQL Server 2022 CU20 documentation and GDR release notes KB5058717, KB5058714, KB5058722 and KB5058721. We recommend that you upgrade your Amazon RDS for SQL Server instances to these latest versions using Amazon RDS Management Console or by using the AWS SDK or CLI. You can learn more about upgrading your database instances by using Amazon RDS User Guide. These updates are available in all AWS regions.  

With this launch, Amazon VPC Reachability Analyzer and Amazon VPC Network Access Analyzer are now available in Asia Pacific (Jakarta), Asia Pacific (Malaysia), Asia Pacific (Thailand), Europe (Zurich), and Middle East (UAE).

VPC Reachability Analyzer allows you to diagnose network reachability between a source resource and a destination resource in your virtual private clouds (VPCs) by analyzing your network configurations. For example, Reachability Analyzer can help you identify a missing route table entry in your VPC route table that could be blocking network reachability between an EC2 instance in Account A that is not able to connect to another EC2 instance in Account B in your AWS Organization.

VPC Network Access Analyzer allows you to identify unintended network access to your AWS resources, helping you meet your security and compliance guidelines. For example, you can create a scope to verify that all paths from your web-applications to the internet, traverse the firewall, and detect any paths that bypass the firewall.

For more information, visit documentation for VPC Reachability Analyzer and VPC Network Access Analyzer. For pricing, refer to the Network Analysis tab on the Amazon VPC Pricing Page. 

 

​With this launch, Amazon VPC Reachability Analyzer and Amazon VPC Network Access Analyzer are now available in Asia Pacific (Jakarta), Asia Pacific (Malaysia), Asia Pacific (Thailand), Europe (Zurich), and Middle East (UAE). VPC Reachability Analyzer allows you to diagnose network reachability between a source resource and a destination resource in your virtual private clouds (VPCs) by analyzing your network configurations. For example, Reachability Analyzer can help you identify a missing route table entry in your VPC route table that could be blocking network reachability between an EC2 instance in Account A that is not able to connect to another EC2 instance in Account B in your AWS Organization. VPC Network Access Analyzer allows you to identify unintended network access to your AWS resources, helping you meet your security and compliance guidelines. For example, you can create a scope to verify that all paths from your web-applications to the internet, traverse the firewall, and detect any paths that bypass the firewall. For more information, visit documentation for VPC Reachability Analyzer and VPC Network Access Analyzer. For pricing, refer to the Network Analysis tab on the Amazon VPC Pricing Page.