AWS has added a fourth Availability Zone to the Europe (London) Region (eu-west-2), expanding infrastructure capacity to meet growing demand for cloud compute in the Region. The new Availability Zone delivers next-generation AI and ML capacity, including Amazon EC2, Trn3, and P6 accelerated instances, alongside general-purpose compute. The new Availability Zone gives AWS customers in eu-west-2 greater capacity for AI and ML workloads and additional fault isolation for building highly available, resilient architectures.

With this new Availability Zone (eu-west-2d), customers can distribute applications across four Availability Zones in eu-west-2, improving fault tolerance and supporting high availability architectures. AI and ML teams can now run model training and inference workloads on the latest accelerated instance types entirely within the London Region. The new Availability Zone is accessible through the AWS Management Console, APIs, and existing workflows with no changes to tooling. Standard Europe (London) Region pricing applies.

To get started, visit AWS Global Infrastructure to learn more about Regions, Availability Zones, and how efficient data center designs and sustainability practices power AWS cloud infrastructure. Explore the AWS Builder Center for hands-on resources, the EC2 Trainium page for AI and ML workloads, and Regional Product Services for a full list of services available by Region.

 

​AWS has added a fourth Availability Zone to the Europe (London) Region (eu-west-2), expanding infrastructure capacity to meet growing demand for cloud compute in the Region. The new Availability Zone delivers next-generation AI and ML capacity, including Amazon EC2, Trn3, and P6 accelerated instances, alongside general-purpose compute. The new Availability Zone gives AWS customers in eu-west-2 greater capacity for AI and ML workloads and additional fault isolation for building highly available, resilient architectures.
With this new Availability Zone (eu-west-2d), customers can distribute applications across four Availability Zones in eu-west-2, improving fault tolerance and supporting high availability architectures. AI and ML teams can now run model training and inference workloads on the latest accelerated instance types entirely within the London Region. The new Availability Zone is accessible through the AWS Management Console, APIs, and existing workflows with no changes to tooling. Standard Europe (London) Region pricing applies.
To get started, visit AWS Global Infrastructure to learn more about Regions, Availability Zones, and how efficient data center designs and sustainability practices power AWS cloud infrastructure. Explore the AWS Builder Center for hands-on resources, the EC2 Trainium page for AI and ML workloads, and Regional Product Services for a full list of services available by Region.  

Amazon WorkSpaces Applications now offers a native monitoring experience embedded directly in the service console. Administrators can now access real-time session-level metrics, instance-level resource data, and network performance metrics without requiring third-party monitoring tools or Amazon CloudWatch expertise.

Previously, enterprise customers managing large WorkSpaces Applications deployments relied on external solutions or built complex custom CloudWatch dashboards. Now, comprehensive monitoring is available with zero configuration required. The WorkSpaces Applications in-console monitoring provides fleet-level capacity visibility showing active sessions and resource utilization, customizable session tables with filtering by user ID, performance metrics, and instance ID, and correlated graphical views displaying session metrics such as frame rate, input latency, bandwidth, and CPU/memory/GPU usage on shared timelines. All these metrics are also available in Amazon CloudWatch giving customers the flexibility to pick the right experience for monitoring their WorkSpaces Applications resources.

This functionality is available today in all AWS Regions where Amazon WorkSpaces Applications is offered.

To learn more, visit the Amazon WorkSpaces Applications documentation OR log on to Amazon WorkSpaces Applications Console, navigate to the fleets menu, and select a fleet to monitor the active session metrics. 

 

​Amazon WorkSpaces Applications now offers a native monitoring experience embedded directly in the service console. Administrators can now access real-time session-level metrics, instance-level resource data, and network performance metrics without requiring third-party monitoring tools or Amazon CloudWatch expertise.
Previously, enterprise customers managing large WorkSpaces Applications deployments relied on external solutions or built complex custom CloudWatch dashboards. Now, comprehensive monitoring is available with zero configuration required. The WorkSpaces Applications in-console monitoring provides fleet-level capacity visibility showing active sessions and resource utilization, customizable session tables with filtering by user ID, performance metrics, and instance ID, and correlated graphical views displaying session metrics such as frame rate, input latency, bandwidth, and CPU/memory/GPU usage on shared timelines. All these metrics are also available in Amazon CloudWatch giving customers the flexibility to pick the right experience for monitoring their WorkSpaces Applications resources.
This functionality is available today in all AWS Regions where Amazon WorkSpaces Applications is offered.
To learn more, visit the Amazon WorkSpaces Applications documentation OR log on to Amazon WorkSpaces Applications Console, navigate to the fleets menu, and select a fleet to monitor the active session metrics.   

Amazon Quick custom permissions now include deny by default, a governance setting that automatically restricts new AI capabilities before they reach users.

Previously, new AI capabilities were available to all users on release, requiring administrators to react after the fact. With deny by default, administrators restrict the AI capability category in a custom permissions profile and assign it to users, roles, or the entire account. Quick then denies any new AI capability at launch for those users. Restricting a category also restricts existing capabilities in it. Administrators explicitly allow each capability when ready. The restriction applies only to the profile you configure.

Configure deny by default in Manage account in Amazon Quick or through the AWS CLI. To learn more, see Custom permissions deny by default. Deny by default is available in all AWS Regions where Amazon Quick is available.

 

​Amazon Quick custom permissions now include deny by default, a governance setting that automatically restricts new AI capabilities before they reach users. Previously, new AI capabilities were available to all users on release, requiring administrators to react after the fact. With deny by default, administrators restrict the AI capability category in a custom permissions profile and assign it to users, roles, or the entire account. Quick then denies any new AI capability at launch for those users. Restricting a category also restricts existing capabilities in it. Administrators explicitly allow each capability when ready. The restriction applies only to the profile you configure. Configure deny by default in Manage account in Amazon Quick or through the AWS CLI. To learn more, see Custom permissions deny by default. Deny by default is available in all AWS Regions where Amazon Quick is available.  

Amazon Bedrock now supports SpaceXAI Grok 4.6, SpaceXAI’s latest flagship model built for long-running agents and ambitious interactive and visual work. Grok 4.6 offers a 500K context window and configurable reasoning  efforts (low, medium, high, xhigh). 

Grok 4.6 builds on previous generations of Grok with a particular focus on staying with complex tasks across many steps, whether researching a topic, analyzing information, working across a codebase, or turning an idea into a polished application. According to SpaceXAI, it achieves frontier intelligence across several agentic coding and knowledge work benchmarks, matching other frontier models specialized for coding. With Bedrock, customers can access the model with enterprise-grade security and privacy,  comprehensive monitoring and logging, and the flexibility to scale across AWS Regions with cross-Region inference.

 Grok 4.6 is available in all AWS Regions where Amazon Bedrock is offered. To get started, review the model card for Grok 4.6 in the Amazon Bedrock User Guide.

 

​Amazon Bedrock now supports SpaceXAI Grok 4.6, SpaceXAI’s latest flagship model built for long-running agents and ambitious interactive and visual work. Grok 4.6 offers a 500K context window and configurable reasoning  efforts (low, medium, high, xhigh).  Grok 4.6 builds on previous generations of Grok with a particular focus on staying with complex tasks across many steps, whether researching a topic, analyzing information, working across a codebase, or turning an idea into a polished application. According to SpaceXAI, it achieves frontier intelligence across several agentic coding and knowledge work benchmarks, matching other frontier models specialized for coding. With Bedrock, customers can access the model with enterprise-grade security and privacy,  comprehensive monitoring and logging, and the flexibility to scale across AWS Regions with cross-Region inference.  Grok 4.6 is available in all AWS Regions where Amazon Bedrock is offered. To get started, review the model card for Grok 4.6 in the Amazon Bedrock User Guide.  

Amazon Bedrock now supports the OpenAI GPT-5.6 models (Terra and Luna) in India, with India Geo cross-Region inference. Customers with regulatory requirements of in-country inferencing can now use OpenAI models at scale ensuring that inferencing is processed within India.

Cross-Region inference automatically routes inference requests across multiple AWS Regions to give you higher throughput, without you needing to manage capacity across multiple Regions. The new India Geo inference profiles—in.openai.gpt-5.6-terra for Terra and in.openai.gpt-5.6-luna for Luna—route requests only within the India geography, across AWS Regions such as Asia Pacific (Mumbai) and Asia Pacific (Hyderabad), so you can scale to meet demand while keeping data processed within India to meet data residency requirements. The models run on the bedrock-runtime endpoint with support for the Responses, Chat Completions, and Converse APIs, and work with the same account-level controls you already use for other models on Bedrock, including model invocation logging (deliverable to Amazon S3 or Amazon CloudWatch Logs), Amazon CloudWatch metrics, and cost itemization in AWS Cost Explorer and the AWS Cost and Usage Report.

OpenAI models with India cross-Region inference are available in the Asia Pacific (Mumbai) and Asia Pacific (Hyderabad) Regions. To get started, review the model cards for GPT-5.6 (Terra and Luna) and the Cross-Region inference section in the Amazon Bedrock User Guide.

 

​Amazon Bedrock now supports the OpenAI GPT-5.6 models (Terra and Luna) in India, with India Geo cross-Region inference. Customers with regulatory requirements of in-country inferencing can now use OpenAI models at scale ensuring that inferencing is processed within India.
Cross-Region inference automatically routes inference requests across multiple AWS Regions to give you higher throughput, without you needing to manage capacity across multiple Regions. The new India Geo inference profiles—in.openai.gpt-5.6-terra for Terra and in.openai.gpt-5.6-luna for Luna—route requests only within the India geography, across AWS Regions such as Asia Pacific (Mumbai) and Asia Pacific (Hyderabad), so you can scale to meet demand while keeping data processed within India to meet data residency requirements. The models run on the bedrock-runtime endpoint with support for the Responses, Chat Completions, and Converse APIs, and work with the same account-level controls you already use for other models on Bedrock, including model invocation logging (deliverable to Amazon S3 or Amazon CloudWatch Logs), Amazon CloudWatch metrics, and cost itemization in AWS Cost Explorer and the AWS Cost and Usage Report.
OpenAI models with India cross-Region inference are available in the Asia Pacific (Mumbai) and Asia Pacific (Hyderabad) Regions. To get started, review the model cards for GPT-5.6 (Terra and Luna) and the Cross-Region inference section in the Amazon Bedrock User Guide.  

AWS Identity and Access Management (IAM) now enables AWS workloads in the AWS European Sovereign Cloud (Germany) Region to securely authenticate with external services using short-lived JSON Web Tokens (JWTs). The AWS European Sovereign Cloud is an independent cloud for Europe entirely located within the European Union (EU), designed to help customers meet their evolving sovereignty requirements.

With outbound identity federation, AWS workloads can securely authenticate with third-party cloud providers, SaaS providers, and self-hosted applications without using long-term credentials or implementing complex workarounds. Customers can exchange their AWS IAM credentials for cryptographically signed, short-lived JWTs, providing a simple and secure mechanism to access external services. These tokens contain rich context about the AWS workloads, enabling external services to implement fine-grained access control. Administrators can control access to token generation and enforce token properties (such as lifetime, audience, and signing algorithms) using IAM policies and audit token usage using CloudTrail logs, allowing them to meet their organization’s security and compliance requirements.

To learn more, visit the outbound identity federation product page, see the IAM user guide, or read the AWS News Blog Post.

 

​AWS Identity and Access Management (IAM) now enables AWS workloads in the AWS European Sovereign Cloud (Germany) Region to securely authenticate with external services using short-lived JSON Web Tokens (JWTs). The AWS European Sovereign Cloud is an independent cloud for Europe entirely located within the European Union (EU), designed to help customers meet their evolving sovereignty requirements.
With outbound identity federation, AWS workloads can securely authenticate with third-party cloud providers, SaaS providers, and self-hosted applications without using long-term credentials or implementing complex workarounds. Customers can exchange their AWS IAM credentials for cryptographically signed, short-lived JWTs, providing a simple and secure mechanism to access external services. These tokens contain rich context about the AWS workloads, enabling external services to implement fine-grained access control. Administrators can control access to token generation and enforce token properties (such as lifetime, audience, and signing algorithms) using IAM policies and audit token usage using CloudTrail logs, allowing them to meet their organization’s security and compliance requirements.
To learn more, visit the outbound identity federation product page, see the IAM user guide, or read the AWS News Blog Post.  

On Aug 18, 2026, Amazon announced critical security patch update (CSPU) for Amazon Corretto Long-Term Support (LTS) and Feature Release (FR) versions of OpenJDK. Corretto 26.0.2.11.1, 25.0.4.8.1, 21.0.12.9.1, 17.0.20.10.1, 11.0.32.10.1, and 8u504 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK.

Visit Corretto home page to download Corretto 26, Corretto 25, Corretto 21, Corretto 17, Corretto 11, or Corretto 8. You can also get the updates on your Linux system by configuring a Corretto Apt, Yum, or Apk repo.

Feedback is welcomed!

 

​On Aug 18, 2026, Amazon announced critical security patch update (CSPU) for Amazon Corretto Long-Term Support (LTS) and Feature Release (FR) versions of OpenJDK. Corretto 26.0.2.11.1, 25.0.4.8.1, 21.0.12.9.1, 17.0.20.10.1, 11.0.32.10.1, and 8u504 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK.
Visit Corretto home page to download Corretto 26, Corretto 25, Corretto 21, Corretto 17, Corretto 11, or Corretto 8. You can also get the updates on your Linux system by configuring a Corretto Apt, Yum, or Apk repo.
Feedback is welcomed!  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8i instances are available in the Israel (Tel Aviv) region. 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 instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. They deliver 20% higher 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 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 sizes 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.  

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 instances visit the AWS News blog.

 

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8i instances are available in the Israel (Tel Aviv) region. 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 instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. They deliver 20% higher 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 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 sizes 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.   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 instances visit the AWS News blog.
   

Amazon SageMaker Unified Studio now supports data profiling and anomaly detection, powered by AWS Glue Data Quality. Data stewards, engineers and analysts can generate statistical profiles of their data to understand its shape and completeness, and track how these statistics change over time. Anomaly detection helps identify when data points drift from historical patterns without requiring predefined thresholds or custom rules. These capabilities are available for both data at rest in catalog tables and data in transit within Visual ETL jobs.

With this launch, a dedicated Data profile tab on catalog tables provides on-demand and scheduled profiling that computes dataset-level and column-level statistics. As profile history accumulates, anomaly detection builds a baseline of expected behavior and flags data points that fall outside the predicted range. This is particularly useful when you may not be aware of specific thresholds, or when expected values change over time and fixed rules could become stale. For data in transit, the same profiling statistics and anomaly detection are available on the results page of any Visual ETL job with an Evaluate Data Quality transform.

This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio documentation.

 

​Amazon SageMaker Unified Studio now supports data profiling and anomaly detection, powered by AWS Glue Data Quality. Data stewards, engineers and analysts can generate statistical profiles of their data to understand its shape and completeness, and track how these statistics change over time. Anomaly detection helps identify when data points drift from historical patterns without requiring predefined thresholds or custom rules. These capabilities are available for both data at rest in catalog tables and data in transit within Visual ETL jobs.
With this launch, a dedicated Data profile tab on catalog tables provides on-demand and scheduled profiling that computes dataset-level and column-level statistics. As profile history accumulates, anomaly detection builds a baseline of expected behavior and flags data points that fall outside the predicted range. This is particularly useful when you may not be aware of specific thresholds, or when expected values change over time and fixed rules could become stale. For data in transit, the same profiling statistics and anomaly detection are available on the results page of any Visual ETL job with an Evaluate Data Quality transform.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio documentation.  

Today, AWS announces the general availability of AgentCore payments, a capability within Amazon Bedrock AgentCore that enables AI agents to autonomously discover, access, and pay for paid APIs, MCPs, and content with just a few lines of code. AgentCore payments provides the security, guardrails, and observability enterprises need to deploy transacting agents in production at scale.

AgentCore payments integrates with Coinbase and Stripe Privy wallets for microtransactions, provides payment orchestration across protocols, enforces configurable payment limits at the infrastructure layer, and delivers end-to-end observability through AgentCore Observability. At general availability, AgentCore payments includes Quick Create for Coinbase credential provisioning directly within the AgentCore console, a curated Coinbase Bazar MCP server of pay-per-use x402 endpoints via AgentCore gateway, support for the Machine Payment Protocol (MPP), and the «upto» scheme in the x402 protocol for pay-per-inference and dynamic pricing use cases.

Developers can get started using coding assistant skills such as Claude Code, Kiro, and Codex, AgentCore CLI, or AWS Management Console – follow this link.

AgentCore payments is available in the regions listed here. To learn more, visit the AgentCore payments documentation or the AWS News Blog.

To learn about pricing, visit AgentCore pricing.

 

​Today, AWS announces the general availability of AgentCore payments, a capability within Amazon Bedrock AgentCore that enables AI agents to autonomously discover, access, and pay for paid APIs, MCPs, and content with just a few lines of code. AgentCore payments provides the security, guardrails, and observability enterprises need to deploy transacting agents in production at scale.
AgentCore payments integrates with Coinbase and Stripe Privy wallets for microtransactions, provides payment orchestration across protocols, enforces configurable payment limits at the infrastructure layer, and delivers end-to-end observability through AgentCore Observability. At general availability, AgentCore payments includes Quick Create for Coinbase credential provisioning directly within the AgentCore console, a curated Coinbase Bazar MCP server of pay-per-use x402 endpoints via AgentCore gateway, support for the Machine Payment Protocol (MPP), and the «upto» scheme in the x402 protocol for pay-per-inference and dynamic pricing use cases.
Developers can get started using coding assistant skills such as Claude Code, Kiro, and Codex, AgentCore CLI, or AWS Management Console – follow this link.
AgentCore payments is available in the regions listed here. To learn more, visit the AgentCore payments documentation or the AWS News Blog.
To learn about pricing, visit AgentCore pricing.