Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS GovCloud (US-West) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

To learn more, see Amazon EC2 R8g Instances. 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) R8g instances are available in AWS GovCloud (US-West) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. 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.    

AWS Outposts now supports self-service capacity management that can be defined specifically for each individual asset. An Outpost asset can be a single server within an Outposts rack or an Outposts server. This makes it easy for customers to customize the allocation of capacity on Outposts at a more granular level. Outposts brings native AWS services, AWS infrastructure, and operating models to virtually any data center, co-location space, or on-premises facility by providing the same services, tools, and partner solutions with Amazon Elastic Compute Cloud (Amazon EC2) on premises. Customers have evolving business requirements and often need to fine-tune their application needs as their businesses scale. Capacity management, now with asset level control, enables viewing and modifying the configuration of EC2 capacity on any Outposts.

Customers can define the configuration of EC2 instances on each Outposts rack or server when they place an Outposts order. Customers can then utilize capacity management to view these EC2 instances on their Outposts, their configured sizes, and their placement within the Outpost. Customers can also use capacity management to view, plan, and modify their capacity configuration through self-service UI and API.

Capacity management is available in all AWS Regions where Outposts are supported. Check out the Outposts rack FAQs page and the Outposts servers FAQs page for the list of supported Regions.

To learn more about these new capacity management capabilities for Outposts, read the Outposts user guide. To discuss Outposts for your on-premises workloads with an Outposts specialist, submit this form.

 

​AWS Outposts now supports self-service capacity management that can be defined specifically for each individual asset. An Outpost asset can be a single server within an Outposts rack or an Outposts server. This makes it easy for customers to customize the allocation of capacity on Outposts at a more granular level. Outposts brings native AWS services, AWS infrastructure, and operating models to virtually any data center, co-location space, or on-premises facility by providing the same services, tools, and partner solutions with Amazon Elastic Compute Cloud (Amazon EC2) on premises. Customers have evolving business requirements and often need to fine-tune their application needs as their businesses scale. Capacity management, now with asset level control, enables viewing and modifying the configuration of EC2 capacity on any Outposts. Customers can define the configuration of EC2 instances on each Outposts rack or server when they place an Outposts order. Customers can then utilize capacity management to view these EC2 instances on their Outposts, their configured sizes, and their placement within the Outpost. Customers can also use capacity management to view, plan, and modify their capacity configuration through self-service UI and API. Capacity management is available in all AWS Regions where Outposts are supported. Check out the Outposts rack FAQs page and the Outposts servers FAQs page for the list of supported Regions. To learn more about these new capacity management capabilities for Outposts, read the Outposts user guide. To discuss Outposts for your on-premises workloads with an Outposts specialist, submit this form.  

Today, Amazon Elastic Kubernetes Service (EKS) announced a new catalog of community add-ons that includes metrics-server, kube-state-metrics, cert-manager, prometheus-node-exporter, and external-dns. This enables you to easily find, select, configure, and manage popular open-source Kubernetes add-ons directly through EKS. Each add-on has been packaged, scanned, and validated for compatibility by EKS, with container images securely hosted in an EKS-owned private Amazon Elastic Container Registry (ECR) repository.

To make Kubernetes clusters production-ready, you need to integrate various operational tools and add-ons. These add-ons can come from various sources including AWS, AWS Marketplace, and open-source community repositories. Now, EKS makes it easy for you to access a broader selection of add-ons, providing a unified management experience for AWS, AWS Marketplace, and community add-ons. You can view available add-ons, compatible versions, configuration options, and install and manage them directly through the EKS Console, API, CLI, eksctl, or IaC tools like AWS CloudFormation.

This feature is available in all AWS Commercial Regions. To learn more visit the EKS documentation.

 

​Today, Amazon Elastic Kubernetes Service (EKS) announced a new catalog of community add-ons that includes metrics-server, kube-state-metrics, cert-manager, prometheus-node-exporter, and external-dns. This enables you to easily find, select, configure, and manage popular open-source Kubernetes add-ons directly through EKS. Each add-on has been packaged, scanned, and validated for compatibility by EKS, with container images securely hosted in an EKS-owned private Amazon Elastic Container Registry (ECR) repository. To make Kubernetes clusters production-ready, you need to integrate various operational tools and add-ons. These add-ons can come from various sources including AWS, AWS Marketplace, and open-source community repositories. Now, EKS makes it easy for you to access a broader selection of add-ons, providing a unified management experience for AWS, AWS Marketplace, and community add-ons. You can view available add-ons, compatible versions, configuration options, and install and manage them directly through the EKS Console, API, CLI, eksctl, or IaC tools like AWS CloudFormation. This feature is available in all AWS Commercial Regions. To learn more visit the EKS documentation.  

Amazon Connect Contact Lens now supports conversational analytics in 34 new languages including Afrikaans, Arabic (Modern Standard), Bengali, Bosnian, Bulgarian, Chinese (Cantonese), Croatian, Czech, Estonian, Farsi, Galician, Greek, Hebrew, Hungarian, Kannada, Latvian, Lithuanian, Macedonian, Malayalam, Marathi, Romanian, Russian, Serbian, Sinhala, Slovak, Slovenian, Somali, Sundanese, Telugu, Thai, Turkish, Ukrainian, Vietnamese, and Zulu. Additionally, 21 languages that were previously available for post-call analytics are now available for real-time analytics, including Arabic (Gulf), Catalan, Danish, Dutch, English (India), English (Ireland), English (New Zealand), English (Scotland), English (South Africa), English (Wales), Filipino/Tagalog, Finnish, German (Swiss), Hindi, Indonesian, Malay, Norwegian Bokmål, Polish, Portuguese (Portugal), Spain (Spanish) and Swedish.

Amazon Connect Contact Lens helps you to monitor, measure, and continuously improve contact quality and agent performance for a better overall customer experience. With Contact Lens conversational analytics, you can transcribe customer calls, analyze customer sentiment, discover top contact drivers, help redact sensitive data, and more, all natively within Amazon Connect. With this launch, Contact Lens conversational analytics now supports 67 languages.

Conversational analytics support for these new languages is now generally available in US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt) and Europe (London). To learn more, please visit our documentation and our webpage. For information about Contact Lens pricing, please visit our pricing page.

 

​Amazon Connect Contact Lens now supports conversational analytics in 34 new languages including Afrikaans, Arabic (Modern Standard), Bengali, Bosnian, Bulgarian, Chinese (Cantonese), Croatian, Czech, Estonian, Farsi, Galician, Greek, Hebrew, Hungarian, Kannada, Latvian, Lithuanian, Macedonian, Malayalam, Marathi, Romanian, Russian, Serbian, Sinhala, Slovak, Slovenian, Somali, Sundanese, Telugu, Thai, Turkish, Ukrainian, Vietnamese, and Zulu. Additionally, 21 languages that were previously available for post-call analytics are now available for real-time analytics, including Arabic (Gulf), Catalan, Danish, Dutch, English (India), English (Ireland), English (New Zealand), English (Scotland), English (South Africa), English (Wales), Filipino/Tagalog, Finnish, German (Swiss), Hindi, Indonesian, Malay, Norwegian Bokmål, Polish, Portuguese (Portugal), Spain (Spanish) and Swedish. Amazon Connect Contact Lens helps you to monitor, measure, and continuously improve contact quality and agent performance for a better overall customer experience. With Contact Lens conversational analytics, you can transcribe customer calls, analyze customer sentiment, discover top contact drivers, help redact sensitive data, and more, all natively within Amazon Connect. With this launch, Contact Lens conversational analytics now supports 67 languages. Conversational analytics support for these new languages is now generally available in US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt) and Europe (London). To learn more, please visit our documentation and our webpage. For information about Contact Lens pricing, please visit our pricing page.  

The next generation of SageMaker brings together widely adopted AWS machine learning and analytics capabilities, delivering an integrated experience with unified access to all data. Amazon SageMaker Lakehouse supports unified data access, and Amazon SageMaker Catalog, built on Amazon DataZone, offers catalog and governance features to meet enterprise security needs.

Amazon SageMaker Catalog now supports metadata rules, allowing organizations to enforce metadata standards across data publishing and subscription workflows. By standardizing metadata practices, organizations can improve compliance, enhance audit readiness, and streamline access workflows for greater efficiency and control.

With metadata rules, domain owners can define mandatory metadata fields that data users must complete when publishing assets to the catalog or requesting access to data. For example, a financial services organization can require producers to classify data before publication, and consumers to provide project details and compliance evidence as part of an access request. Healthcare providers can use metadata rules to enforce metadata standards to align with patient data regulations.
Metadata rules also enable the creation of custom approval workflows for subscriptions to assets, using collected metadata to facilitate access decisions or auto-fulfillment—outside of Amazon SageMaker.

To get started with metadata rules—

• Read the user guide for creating rules in the publishing workflow
• Read the user guide for creating rules in subscription requests

 

​The next generation of SageMaker brings together widely adopted AWS machine learning and analytics capabilities, delivering an integrated experience with unified access to all data. Amazon SageMaker Lakehouse supports unified data access, and Amazon SageMaker Catalog, built on Amazon DataZone, offers catalog and governance features to meet enterprise security needs. Amazon SageMaker Catalog now supports metadata rules, allowing organizations to enforce metadata standards across data publishing and subscription workflows. By standardizing metadata practices, organizations can improve compliance, enhance audit readiness, and streamline access workflows for greater efficiency and control. With metadata rules, domain owners can define mandatory metadata fields that data users must complete when publishing assets to the catalog or requesting access to data. For example, a financial services organization can require producers to classify data before publication, and consumers to provide project details and compliance evidence as part of an access request. Healthcare providers can use metadata rules to enforce metadata standards to align with patient data regulations. Metadata rules also enable the creation of custom approval workflows for subscriptions to assets, using collected metadata to facilitate access decisions or auto-fulfillment—outside of Amazon SageMaker. To get started with metadata rules—

Read the user guide for creating rules in the publishing workflow
Read the user guide for creating rules in subscription requests  

AWS Identity and Access Management (IAM) announces a new dual-stack public endpoint, enabling customers to connect to IAM over the public internet using IPv6, IPv4, or dual-stack clients. Dual-stack support is also available when customers access the new IAM endpoint privately from their Amazon Virtual Private Cloud (VPC) using AWS PrivateLink. With simultaneous support for both IPv4 and IPv6 clients on IAM endpoint, customers can gradually transition from IPv4 to IPv6-based systems and applications.

Support for dual-stack IAM endpoint is available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions. For more information about IAM dual-stack public endpoint, please see the IAM User Guide.

 

​AWS Identity and Access Management (IAM) announces a new dual-stack public endpoint, enabling customers to connect to IAM over the public internet using IPv6, IPv4, or dual-stack clients. Dual-stack support is also available when customers access the new IAM endpoint privately from their Amazon Virtual Private Cloud (VPC) using AWS PrivateLink. With simultaneous support for both IPv4 and IPv6 clients on IAM endpoint, customers can gradually transition from IPv4 to IPv6-based systems and applications. Support for dual-stack IAM endpoint is available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions. For more information about IAM dual-stack public endpoint, please see the IAM User Guide.  

Amazon Bedrock Guardrails announces the general availability of image content filters – offering industry-leading text and image content safeguards that help customers block up to 88% of harmful multi modal content. This new capability removes the heavy lifting required by customers to build their own safeguards for image content or spend cycles with manual content moderation that can be error-prone and tedious. Bedrock Guardrails provides configurable safeguards to detect and block harmful content and prompt attacks, define topics to deny and disallow specific topics, redact personally identifiable information (PII) such as personal data, block specific words, along with contextual grounding checks to detect and block model hallucinations and to identify the relevance of model responses and claims, and identify, correct, and explain factual claims in model responses using Automated Reasoning checks. Guardrails can be applied across any foundation model including those hosted with Amazon Bedrock, self-hosted models, and third-party models outside Bedrock using the ApplyGuardrail API, providing a consistent user experience and helping to standardize safety and privacy controls.

Image content filters can be applied to all categories within the content filter policy of Bedrock Guardrails including hate, insults, sexual, violence, misconduct, and prompt attack. With this new capability, customers have the flexibility to choose either image or text content, or both, and build safe generative AI applications adhering to their responsible AI policies.

This new capability is generally available in US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Asia Pacific (Tokyo) AWS regions.

To learn more, see the blog, technical documentation, and the Bedrock Guardrails product page.

 

​Amazon Bedrock Guardrails announces the general availability of image content filters – offering industry-leading text and image content safeguards that help customers block up to 88% of harmful multi modal content. This new capability removes the heavy lifting required by customers to build their own safeguards for image content or spend cycles with manual content moderation that can be error-prone and tedious. Bedrock Guardrails provides configurable safeguards to detect and block harmful content and prompt attacks, define topics to deny and disallow specific topics, redact personally identifiable information (PII) such as personal data, block specific words, along with contextual grounding checks to detect and block model hallucinations and to identify the relevance of model responses and claims, and identify, correct, and explain factual claims in model responses using Automated Reasoning checks. Guardrails can be applied across any foundation model including those hosted with Amazon Bedrock, self-hosted models, and third-party models outside Bedrock using the ApplyGuardrail API, providing a consistent user experience and helping to standardize safety and privacy controls. Image content filters can be applied to all categories within the content filter policy of Bedrock Guardrails including hate, insults, sexual, violence, misconduct, and prompt attack. With this new capability, customers have the flexibility to choose either image or text content, or both, and build safe generative AI applications adhering to their responsible AI policies. This new capability is generally available in US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Asia Pacific (Tokyo) AWS regions. To learn more, see the blog, technical documentation, and the Bedrock Guardrails product page.  

Amazon EC2 now supports up to the full EC2 instance bandwidth for inter-region VPC peering traffic and to AWS Direct Connect. Additionally, EC2 supports jumbo frames up to 8500 Bytes for cross region VPC peering. Before today, the egress bandwidth for EC2 instances was limited to 50% of the aggregate bandwidth limit for instances with 32 or more vCPUs, and 5 Gbps for smaller instances. Cross region peering supported up to 1500 bytes. Now, customers can send bandwidth from EC2 between regions or towards AWS Direct Connect at the full instance baseline specification or 5Gbps, whichever is greater and customers can use jumbo frames across regions for peered VPCs.

Customers transferring data between regions or from EC2 to their on-premises network via AWS Direct Connect now have access to the full instance bandwidth capabilities. Before today, customers sending traffic to any destination not in the same region had a lower bandwidth limit. With this change, the lower limit has been removed for destinations between AWS regions and to on-premises through AWS Direct Connect, allowing for faster transfers. Additionally, supporting jumbo frames for peering makes sending large volumes of data faster than before.

This capability is available in all AWS commercial regions, the AWS GovCloud (US) Regions, and the Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. Customers can take advantage of this capability without any additional changes. To learn more about EC2 bandwidth capabilities, please review our user guide.

 

​Amazon EC2 now supports up to the full EC2 instance bandwidth for inter-region VPC peering traffic and to AWS Direct Connect. Additionally, EC2 supports jumbo frames up to 8500 Bytes for cross region VPC peering. Before today, the egress bandwidth for EC2 instances was limited to 50% of the aggregate bandwidth limit for instances with 32 or more vCPUs, and 5 Gbps for smaller instances. Cross region peering supported up to 1500 bytes. Now, customers can send bandwidth from EC2 between regions or towards AWS Direct Connect at the full instance baseline specification or 5Gbps, whichever is greater and customers can use jumbo frames across regions for peered VPCs. Customers transferring data between regions or from EC2 to their on-premises network via AWS Direct Connect now have access to the full instance bandwidth capabilities. Before today, customers sending traffic to any destination not in the same region had a lower bandwidth limit. With this change, the lower limit has been removed for destinations between AWS regions and to on-premises through AWS Direct Connect, allowing for faster transfers. Additionally, supporting jumbo frames for peering makes sending large volumes of data faster than before. This capability is available in all AWS commercial regions, the AWS GovCloud (US) Regions, and the Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. Customers can take advantage of this capability without any additional changes. To learn more about EC2 bandwidth capabilities, please review our user guide.  

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and third-party sources. Amazon DataZone now supports metadata rules for data publishing workflows, in addition to existing support for subscription workflows. This enhancement allows organizations to enforce metadata standards consistently across both producer and consumer workflows. By standardizing metadata practices, organizations can improve compliance, enhance audit readiness, and streamline workflows for greater efficiency and control.

With metadata rules, domain owners can define mandatory metadata fields that data users must complete when publishing assets to the catalog or requesting access to data. For example, a financial services organization can require producers to classify data before publication, and consumers to provide project details and compliance evidence as part of an access request. Healthcare providers can use metadata rules to enforce metadata standards to align with patient data regulations.
Metadata rules also enable the creation of custom approval workflows for subscriptions to assets, using collected metadata to facilitate access decisions or auto-fulfillment—outside of Amazon DataZone.

To get started with metadata rules—

• Read the user guide for creating rules in the publishing workflow
• Read the user guide for creating rules in subscription requests

 

​Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and third-party sources. Amazon DataZone now supports metadata rules for data publishing workflows, in addition to existing support for subscription workflows. This enhancement allows organizations to enforce metadata standards consistently across both producer and consumer workflows. By standardizing metadata practices, organizations can improve compliance, enhance audit readiness, and streamline workflows for greater efficiency and control. With metadata rules, domain owners can define mandatory metadata fields that data users must complete when publishing assets to the catalog or requesting access to data. For example, a financial services organization can require producers to classify data before publication, and consumers to provide project details and compliance evidence as part of an access request. Healthcare providers can use metadata rules to enforce metadata standards to align with patient data regulations. Metadata rules also enable the creation of custom approval workflows for subscriptions to assets, using collected metadata to facilitate access decisions or auto-fulfillment—outside of Amazon DataZone. To get started with metadata rules—

Read the user guide for creating rules in the publishing workflow
Read the user guide for creating rules in subscription requests  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS US West (N. California) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

To learn more, see Amazon EC2 R8g Instances. 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) R8g instances are available in AWS US West (N. California) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. 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.