On August 5, 2025, AWS announced the availability of two new OpenAI models with open weights in Amazon Bedrock. Today, we’re simplifying access to these foundation models by making them automatically available to all Amazon Bedrock users, eliminating the need to explicitly enable model access. Customers can immediately start using these models through the Amazon Bedrock Console playground or through Amazon Bedrock’s unified API in AWS SDK in the regions where the models are available.

This streamlined access enables customers to quickly begin using OpenAI’s gpt-oss-120b and gpt-oss-20b models without needing to manually activate model access.Soon, we will extend this simplified access approach to other existing non-legacy serverless models in Amazon Bedrock. Going forward, Amazon Bedrock will launch all new serverless foundation models with default access for AWS accounts. Account administrators retain full control over model access through IAM policies and Service Control Policies (SCPs) to restrict model usage as needed.

For information about implementing access controls, visit our documentation and our blog post on implementing least privilege access in Amazon Bedrock. To get started with GPT-OSS models, visit the Amazon Bedrock Console.

 

 

 

 

 

​On August 5, 2025, AWS announced the availability of two new OpenAI models with open weights in Amazon Bedrock. Today, we’re simplifying access to these foundation models by making them automatically available to all Amazon Bedrock users, eliminating the need to explicitly enable model access. Customers can immediately start using these models through the Amazon Bedrock Console playground or through Amazon Bedrock’s unified API in AWS SDK in the regions where the models are available. This streamlined access enables customers to quickly begin using OpenAI’s gpt-oss-120b and gpt-oss-20b models without needing to manually activate model access.Soon, we will extend this simplified access approach to other existing non-legacy serverless models in Amazon Bedrock. Going forward, Amazon Bedrock will launch all new serverless foundation models with default access for AWS accounts. Account administrators retain full control over model access through IAM policies and Service Control Policies (SCPs) to restrict model usage as needed. For information about implementing access controls, visit our documentation and our blog post on implementing least privilege access in Amazon Bedrock. To get started with GPT-OSS models, visit the Amazon Bedrock Console.
 
 
 
   

Amazon announces the expansion of the TwelveLabs’ Pegasus 1.2 video understanding model to the US East (N. Virginia) and Asia Pacific (Seoul) AWS Regions. This expansion makes it easier for customers to build and scale generative AI applications that can understand and interact with video content at an enterprise level.

Pegasus 1.2 is a powerful video-first language model that can generate text based on the visual, audio, and textual content within video. Specifically designed for long-form video, it excels at video-to-text generation and temporal understanding. With Pegasus 1.2’s availability in these additional regions, you can now build video intelligence applications closer to your data and end users in key geographic locations, reducing latency and simplifying your architecture.

With today’s expansion, Pegasus 1.2 is now available in Amazon Bedrock across four regions: US West (Oregon), Europe (Ireland), US East (N. Virginia), and Asia Pacific (Seoul). To get started with Pegasus 1.2, visit the Amazon Bedrock console and request model access. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation. 

 

​Amazon announces the expansion of the TwelveLabs’ Pegasus 1.2 video understanding model to the US East (N. Virginia) and Asia Pacific (Seoul) AWS Regions. This expansion makes it easier for customers to build and scale generative AI applications that can understand and interact with video content at an enterprise level. Pegasus 1.2 is a powerful video-first language model that can generate text based on the visual, audio, and textual content within video. Specifically designed for long-form video, it excels at video-to-text generation and temporal understanding. With Pegasus 1.2’s availability in these additional regions, you can now build video intelligence applications closer to your data and end users in key geographic locations, reducing latency and simplifying your architecture. With today’s expansion, Pegasus 1.2 is now available in Amazon Bedrock across four regions: US West (Oregon), Europe (Ireland), US East (N. Virginia), and Asia Pacific (Seoul). To get started with Pegasus 1.2, visit the Amazon Bedrock console and request model access. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation.   

Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in the AWS Europe (Frankfurt, London), Asia Pacific (Malaysia, Sydney, Tokyo) regions. Powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances.

I7i instances offer the best compute and storage performance for x86-based storage optimized instances in Amazon EC2, ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets (multi-TBs). Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks.

I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth.
To learn more, visit the I7i instances page. 

 

​Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in the AWS Europe (Frankfurt, London), Asia Pacific (Malaysia, Sydney, Tokyo) regions. Powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances. I7i instances offer the best compute and storage performance for x86-based storage optimized instances in Amazon EC2, ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets (multi-TBs). Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks. I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.   

Amazon Connect now supports multi-user web, in-app and video calling, allowing multiple users to join the same session with an agent through a web browser or mobile application. Contact center agents can dynamically add participants during a live call or multiple participants can join a scheduled session with the same agent. Participants can engage in audio, video, and screen sharing for a fully collaborative experience.

This capability helps organizations support scenarios such as joint financial planning between spouses, partners and advisors, family medical consultations, or conversations that involve legal representatives, translators, or subject matter experts. With this capability, you can enable a rich, inclusive interaction across stakeholders in a single session, reducing friction and improving the quality of support for complex engagements.

These new features are available in all AWS regions where Amazon Connect is offered. To learn more, visit our product page or refer to our Admin Guide.

 

​Amazon Connect now supports multi-user web, in-app and video calling, allowing multiple users to join the same session with an agent through a web browser or mobile application. Contact center agents can dynamically add participants during a live call or multiple participants can join a scheduled session with the same agent. Participants can engage in audio, video, and screen sharing for a fully collaborative experience. This capability helps organizations support scenarios such as joint financial planning between spouses, partners and advisors, family medical consultations, or conversations that involve legal representatives, translators, or subject matter experts. With this capability, you can enable a rich, inclusive interaction across stakeholders in a single session, reducing friction and improving the quality of support for complex engagements. These new features are available in all AWS regions where Amazon Connect is offered. To learn more, visit our product page or refer to our Admin Guide.  

AWS is announcing the general availability of new memory-optimized Amazon EC2 R8i and R8i-flex instances. These instances are powered by custom Intel Xeon 6 processors, available only on AWS, delivering the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. The R8i and R8i-flex instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. They deliver 20% better performance than R7i instances, with even higher gains for specific workloads. They are up to 30% faster for PostgreSQL databases, up to 60% faster for NGINX web applications, and up to 40% faster for AI deep learning recommendation models compared to R7i.

R8i-flex, our first memory-optimized Flex instances, are the easiest way to get price performance benefits for a majority of memory-intensive workloads. They 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.

R8i instances are a great choice for all memory-intensive workloads, especially for workloads that need the largest instance sizes or continuous high CPU usage. R8i instances offer 13 sizes including 2 bare metal and the new 96xlarge size for the largest applications. R8i instances are SAP-certified and deliver 142,100 aSAPS, the highest among all comparable machines in on-premises and cloud environments, delivering exceptional performance for mission-critical SAP workloads.

R8i and R8i-flex instances are available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), and Europe (Spain).

To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information about the new R8i and R8i-flex instances visit the AWS News blog.

 

​AWS is announcing the general availability of new memory-optimized Amazon EC2 R8i and R8i-flex instances. These instances are powered by custom Intel Xeon 6 processors, available only on AWS, delivering the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. The R8i and R8i-flex instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. They deliver 20% better performance than R7i instances, with even higher gains for specific workloads. They are up to 30% faster for PostgreSQL databases, up to 60% faster for NGINX web applications, and up to 40% faster for AI deep learning recommendation models compared to R7i. R8i-flex, our first memory-optimized Flex instances, are the easiest way to get price performance benefits for a majority of memory-intensive workloads. They 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. R8i instances are a great choice for all memory-intensive workloads, especially for workloads that need the largest instance sizes or continuous high CPU usage. R8i instances offer 13 sizes including 2 bare metal and the new 96xlarge size for the largest applications. R8i instances are SAP-certified and deliver 142,100 aSAPS, the highest among all comparable machines in on-premises and cloud environments, delivering exceptional performance for mission-critical SAP workloads. R8i and R8i-flex instances are available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), and Europe (Spain). To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information about the new R8i and R8i-flex instances visit the AWS News blog.  

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports Kerberos authentication with self-managed Microsoft Active Directory (AD). With this launch, your applications can use Kerberos authentication to connect to your Amazon RDS for SQL Server instances joined to self-managed AD.

Previously, customers integrating Amazon RDS for SQL Server with Microsoft Active Directory had to use AWS Managed AD for Kerberos authentication. Now, customers can setup Kerberos authentication when integrating Amazon RDS for SQL Server with Microsoft AD without having to use AWS Managed AD. For customers that are migrating on-premises SQL Server databases to Amazon RDS for SQL Server, this feature simplifies migration by removing the requirement to adopt Amazon Managed AD to use Kerberos authentication. Customers who use Amazon RDS for SQL Server with AWS Managed AD can continue to use their existing integration.

To join your Amazon RDS for SQL Server instance to a self-managed AD and setup Kerberos authentication, refer to the Amazon RDS for SQL Server User Guide. This feature is available in all AWS Commercial and AWS GovCloud (US) Regions.

 

​Amazon Relational Database Service (Amazon RDS) for SQL Server now supports Kerberos authentication with self-managed Microsoft Active Directory (AD). With this launch, your applications can use Kerberos authentication to connect to your Amazon RDS for SQL Server instances joined to self-managed AD. Previously, customers integrating Amazon RDS for SQL Server with Microsoft Active Directory had to use AWS Managed AD for Kerberos authentication. Now, customers can setup Kerberos authentication when integrating Amazon RDS for SQL Server with Microsoft AD without having to use AWS Managed AD. For customers that are migrating on-premises SQL Server databases to Amazon RDS for SQL Server, this feature simplifies migration by removing the requirement to adopt Amazon Managed AD to use Kerberos authentication. Customers who use Amazon RDS for SQL Server with AWS Managed AD can continue to use their existing integration. To join your Amazon RDS for SQL Server instance to a self-managed AD and setup Kerberos authentication, refer to the Amazon RDS for SQL Server User Guide. This feature is available in all AWS Commercial and AWS GovCloud (US) Regions.  

Today, AWS announced the opening of a new AWS Direct Connect location within the Equinix BA1 data center near Barcelona, Spain. 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. This site is the first AWS Direct Connect location in Barcelona and the third AWS Direct connect location within Spain. This Direct Connect location offers dedicated 10 Gbps and 100 Gbps connections with MACsec encryption available.

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 143 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 opening of a new AWS Direct Connect location within the Equinix BA1 data center near Barcelona, Spain. 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. This site is the first AWS Direct Connect location in Barcelona and the third AWS Direct connect location within Spain. This Direct Connect location offers dedicated 10 Gbps and 100 Gbps connections with MACsec encryption available. 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 143 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.  

Anthropic’s Claude Sonnet 4 and OpenAI’s GPT-OSS 120B and 20B models are now available for Batch inference in Amazon Bedrock. With Batch inference, you can run multiple inference requests asynchronously, improving performance on large datasets at 50% of the on-demand inference pricing. Amazon Bedrock offers select foundation models (FMs) from leading AI providers such as Anthropic, OpenAI, Meta, and Amazon for batch inference, making it easier and more cost-effective to process high-volume workloads.

With Batch inference on Claude Sonnet 4 and OpenAI GPT-OSS models, you can process large datasets for scenarios such as document and customer feedback analysis, bulk content generation (e.g., marketing copy, product descriptions), large-scale prompt or output evaluations, automated summarization of knowledge bases and archives, mass categorization of support tickets or emails, and extraction of structured data from unstructured text—at scale and with lower costs. We’ve optimized our Batch offering to deliver higher overall batch throughput on these newer models compared to previous ones. In addition, you can now track your Batch workload progress at the AWS account level with Amazon CloudWatch metrics. For all models, these metrics include total pending records, processed records and tokens per minute, and for Claude models, they also include tokens pending processing.

To learn more about Batch inference in Amazon Bedrock, visit the Batch inference documentation. You can visit Supported Regions and models for batch inference page for more details on supported models and follow Amazon Bedrock API reference to get started with Batch inference. 

 

​Anthropic’s Claude Sonnet 4 and OpenAI’s GPT-OSS 120B and 20B models are now available for Batch inference in Amazon Bedrock. With Batch inference, you can run multiple inference requests asynchronously, improving performance on large datasets at 50% of the on-demand inference pricing. Amazon Bedrock offers select foundation models (FMs) from leading AI providers such as Anthropic, OpenAI, Meta, and Amazon for batch inference, making it easier and more cost-effective to process high-volume workloads. With Batch inference on Claude Sonnet 4 and OpenAI GPT-OSS models, you can process large datasets for scenarios such as document and customer feedback analysis, bulk content generation (e.g., marketing copy, product descriptions), large-scale prompt or output evaluations, automated summarization of knowledge bases and archives, mass categorization of support tickets or emails, and extraction of structured data from unstructured text—at scale and with lower costs. We’ve optimized our Batch offering to deliver higher overall batch throughput on these newer models compared to previous ones. In addition, you can now track your Batch workload progress at the AWS account level with Amazon CloudWatch metrics. For all models, these metrics include total pending records, processed records and tokens per minute, and for Claude models, they also include tokens pending processing. To learn more about Batch inference in Amazon Bedrock, visit the Batch inference documentation. You can visit Supported Regions and models for batch inference page for more details on supported models and follow Amazon Bedrock API reference to get started with Batch inference.   

Amazon S3 provides a new way to verify the content of stored datasets. You can efficiently verify billions of objects and automatically generate integrity reports to prove that your datasets remain intact over time using S3 Batch Operations. This capability works with any object stored in S3, regardless of storage class or object size, without the need to restore or download data. Whether you’re verifying objects for data preservation, accuracy checks, or compliance requirements, you can reduce the cost, time, and effort required.

With S3 Batch Operations, you can create a compute checksum job for your objects. To get started, provide a list of objects (called a manifest) or specify the bucket with filters like prefix or suffix. Then choose «Compute checksum» as the operation type and select from supported algorithms including SHA-1, SHA-256, CRC32, CRC32C, CRC64, and MD5. When the job completes, you receive a detailed report with checksum information for all processed objects. You can use this report for compliance or audit purposes. This capability complements S3’s built-in validation, letting you independently verify your stored data any time.

This new data verification, compute checksum operation, is now available in all AWS Regions. For pricing details, visit the S3 pricing page. To learn more, visit the S3 User Guide.

 

​Amazon S3 provides a new way to verify the content of stored datasets. You can efficiently verify billions of objects and automatically generate integrity reports to prove that your datasets remain intact over time using S3 Batch Operations. This capability works with any object stored in S3, regardless of storage class or object size, without the need to restore or download data. Whether you’re verifying objects for data preservation, accuracy checks, or compliance requirements, you can reduce the cost, time, and effort required. With S3 Batch Operations, you can create a compute checksum job for your objects. To get started, provide a list of objects (called a manifest) or specify the bucket with filters like prefix or suffix. Then choose «Compute checksum» as the operation type and select from supported algorithms including SHA-1, SHA-256, CRC32, CRC32C, CRC64, and MD5. When the job completes, you receive a detailed report with checksum information for all processed objects. You can use this report for compliance or audit purposes. This capability complements S3’s built-in validation, letting you independently verify your stored data any time. This new data verification, compute checksum operation, is now available in all AWS Regions. For pricing details, visit the S3 pricing page. To learn more, visit the S3 User Guide.  

AWS Marketplace now offers a streamlined fulfillment experience for Amazon Machine Image (AMI) and AMI with CloudFormation products across both the AWS Marketplace website and console. Additionally, users can now also access the new launch experience for container products directly within AWS Marketplace console.

The new fulfillment experience in AWS Marketplace simplifies product deployment for AMI products by combining the configuration and fulfillment experience into a single page, clearly presenting fulfillment options and AWS services available for purchased products. Users will also have access to new resources, including detailed guides from AWS Marketplace Sellers. The new experience is available through both the AWS Marketplace website and console, in all AWS Marketplace supported commercial regions and languages, delivering a consistent experience worldwide.

To learn more about the new fulfillment experience for AMI-based products in AWS Marketplace and how it can benefit your organization, visit the AWS Marketplace Buyer Guide or start exploring AMI products in AWS Marketplace today.

 

​AWS Marketplace now offers a streamlined fulfillment experience for Amazon Machine Image (AMI) and AMI with CloudFormation products across both the AWS Marketplace website and console. Additionally, users can now also access the new launch experience for container products directly within AWS Marketplace console. The new fulfillment experience in AWS Marketplace simplifies product deployment for AMI products by combining the configuration and fulfillment experience into a single page, clearly presenting fulfillment options and AWS services available for purchased products. Users will also have access to new resources, including detailed guides from AWS Marketplace Sellers. The new experience is available through both the AWS Marketplace website and console, in all AWS Marketplace supported commercial regions and languages, delivering a consistent experience worldwide. To learn more about the new fulfillment experience for AMI-based products in AWS Marketplace and how it can benefit your organization, visit the AWS Marketplace Buyer Guide or start exploring AMI products in AWS Marketplace today.