Amazon Neptune Database is now available in the Asia Pacific (Malaysia) Region on engine versions 1.1.0.0 and later. You can now create Neptune clusters using R6g, R6i, T4g, and T3 instance types in the AWS Asia Pacific (Malaysia) Region.

Amazon Neptune Database is a fast, reliable, and fully managed graph database as a service that makes it easy to build and run applications work with highly connected datasets. You can build applications using Apache TinkerPop Gremlin or openCypher on the Property Graph model, or using the SPARQL query language on W3C Resource Description Framework (RDF). Neptune also offers enterprise features such as high availability, automated backups, and network isolation to help customers quickly deploy applications to production.

To get started, you can create a new Neptune cluster using the AWS Management Console, AWS CLI, or a quickstart AWS CloudFormation template. For more information on pricing and region availability, refer to the Neptune pricing page and AWS Region Table.
 

 

​Amazon Neptune Database is now available in the Asia Pacific (Malaysia) Region on engine versions 1.1.0.0 and later. You can now create Neptune clusters using R6g, R6i, T4g, and T3 instance types in the AWS Asia Pacific (Malaysia) Region. Amazon Neptune Database is a fast, reliable, and fully managed graph database as a service that makes it easy to build and run applications work with highly connected datasets. You can build applications using Apache TinkerPop Gremlin or openCypher on the Property Graph model, or using the SPARQL query language on W3C Resource Description Framework (RDF). Neptune also offers enterprise features such as high availability, automated backups, and network isolation to help customers quickly deploy applications to production. To get started, you can create a new Neptune cluster using the AWS Management Console, AWS CLI, or a quickstart AWS CloudFormation template. For more information on pricing and region availability, refer to the Neptune pricing page and AWS Region Table.    

AWS Transfer Family has reduced the service side login latency from 1-2 seconds to under 500 milliseconds.

AWS Transfer Family offers fully managed support for the transfer of files over SFTP, AS2, FTPS, FTP, and web browser-based transfers directly into and out of AWS storage services. With this launch, you benefit from significantly reduced latency from the service to initiate the transfer over SFTP. This optimization offers substantial benefits, particularly for high-frequency, low-latency use cases with automated processes or applications requiring rapid file operations.

Reduced server-side login latency is immediately available at no additional cost for all new and existing Transfer Family SFTP servers in all AWS Regions where the service is available. To create an SFTP server, visit the Transfer Family User Guide.
 

 

​AWS Transfer Family has reduced the service side login latency from 1-2 seconds to under 500 milliseconds. AWS Transfer Family offers fully managed support for the transfer of files over SFTP, AS2, FTPS, FTP, and web browser-based transfers directly into and out of AWS storage services. With this launch, you benefit from significantly reduced latency from the service to initiate the transfer over SFTP. This optimization offers substantial benefits, particularly for high-frequency, low-latency use cases with automated processes or applications requiring rapid file operations. Reduced server-side login latency is immediately available at no additional cost for all new and existing Transfer Family SFTP servers in all AWS Regions where the service is available. To create an SFTP server, visit the Transfer Family User Guide.    

Etiquetas:

• IA
• Seguridad

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Amazon API Gateway (APIGW) now supports all features of HTTP APIs as well as Mutual TLS and multi-level base path mappings on REST APIs in the following additional Regions: Middle East (UAE), Asia Pacific (Jakarta), Asia Pacific (Osaka), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Europe (Zurich), Europe (Spain), Israel (Tel Aviv), and Canada West (Calgary). AWS Web Application Firewall (WAF) for REST APIs is now available in two additional regions: Asia Pacific (Kuala Lumpur) and Canada West (Calgary).

HTTP APIs simplify API development for serverless applications with a simpler user interface that includes support for OAuth2.0 and automatic deployments. Mutual TLS enhances security by authenticating x509 certificate based identities at the APIGW. Multi-level base path mappings enable routing requests based on segments in custom domain paths, supporting path-based versioning and traffic redirection. Integration of AWS WAF offers APIs protections against common web exploits through configurable rules that allow, block, or monitor web requests.

To learn more, see API Gateway developer guide.

 

​Amazon API Gateway (APIGW) now supports all features of HTTP APIs as well as Mutual TLS and multi-level base path mappings on REST APIs in the following additional Regions: Middle East (UAE), Asia Pacific (Jakarta), Asia Pacific (Osaka), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Europe (Zurich), Europe (Spain), Israel (Tel Aviv), and Canada West (Calgary). AWS Web Application Firewall (WAF) for REST APIs is now available in two additional regions: Asia Pacific (Kuala Lumpur) and Canada West (Calgary). HTTP APIs simplify API development for serverless applications with a simpler user interface that includes support for OAuth2.0 and automatic deployments. Mutual TLS enhances security by authenticating x509 certificate based identities at the APIGW. Multi-level base path mappings enable routing requests based on segments in custom domain paths, supporting path-based versioning and traffic redirection. Integration of AWS WAF offers APIs protections against common web exploits through configurable rules that allow, block, or monitor web requests. To learn more, see API Gateway developer guide.  

Amazon Cognito now allows customers to customize access tokens for M2M flows, enabling you to implement fine-grained authorization in your applications, APIs, and workloads. M2M authorization is commonly used for automated processes such as scheduled data synchronization tasks, event-driven workflows, microservices communication, or real-time data streaming between systems. In M2M authorization flows, an app client can represent a software system or service that can request access tokens to interact with resources, such as a reporting system or a data processing service. With this launch, customers can now customize their access tokens with custom claims (attributes about the app client) and scopes (level of access that an app client can request to a resource), making it easier to control and manage how their automated systems interact with each other.

Customers can now add custom attributes directly in access tokens, reducing the complexity of authorization logic needed in their application code. For example, customers can customize access tokens with claims that allow an app client for a reporting system to only read data while allowing an app client for a data processing service to both read and modify data. This allows customers to streamline authentication by embedding custom authorization attributes directly into access tokens during the token issuance process.

Access token customization for M2M authorization is available to Amazon Cognito customers using Essentials or Plus tiers in all AWS Regions where Cognito is available, except the AWS GovCloud (US) Regions. To learn more, refer to the developer guide.
 

 

​Amazon Cognito now allows customers to customize access tokens for M2M flows, enabling you to implement fine-grained authorization in your applications, APIs, and workloads. M2M authorization is commonly used for automated processes such as scheduled data synchronization tasks, event-driven workflows, microservices communication, or real-time data streaming between systems. In M2M authorization flows, an app client can represent a software system or service that can request access tokens to interact with resources, such as a reporting system or a data processing service. With this launch, customers can now customize their access tokens with custom claims (attributes about the app client) and scopes (level of access that an app client can request to a resource), making it easier to control and manage how their automated systems interact with each other. Customers can now add custom attributes directly in access tokens, reducing the complexity of authorization logic needed in their application code. For example, customers can customize access tokens with claims that allow an app client for a reporting system to only read data while allowing an app client for a data processing service to both read and modify data. This allows customers to streamline authentication by embedding custom authorization attributes directly into access tokens during the token issuance process. Access token customization for M2M authorization is available to Amazon Cognito customers using Essentials or Plus tiers in all AWS Regions where Cognito is available, except the AWS GovCloud (US) Regions. To learn more, refer to the developer guide.    

CloudWatch RUM, which provides real-time monitoring into web application performance by tracking user interactions, now supports resource based policies that simplify access for data ingestion to RUM. With resource-based policies, you can specify which Identity and Access Management (IAM) principals have access to ingest data to your RUM app monitors— effectively which clients can write data to RUM. This would also allow you to ingest data at higher volume and gives you greater control over data ingress in RUM.

Using resource based policies allows you to manage ingestion access to your app monitor without using Amazon Cognito to assume an IAM role, and AWS Security Token Service (STS) to obtain security credentials to write data to CloudWatch RUM. This is beneficial for high throughput use cases where a high volume of requests may be subject to Cognito’s quota limits leading to throttling and potentially failure in ingesting data to RUM. With a public resource policy, no such limits apply. Anyone can send data to CloudWatch RUM including unauthenticated users and clients. In addition, you can use AWS Global context keys to use these policies to block certain IPs or disable clients sending data to RUM. You can configure these policies on the AWS console or via code using AWS CloudFormation.

These enhancements are available in all regions where CloudWatch RUM is available at no additional cost to users.

See documentation to know more about the feature, or see user guide to learn how to configure resource based policies for CloudWatch RUM.
 

 

​CloudWatch RUM, which provides real-time monitoring into web application performance by tracking user interactions, now supports resource based policies that simplify access for data ingestion to RUM. With resource-based policies, you can specify which Identity and Access Management (IAM) principals have access to ingest data to your RUM app monitors— effectively which clients can write data to RUM. This would also allow you to ingest data at higher volume and gives you greater control over data ingress in RUM. Using resource based policies allows you to manage ingestion access to your app monitor without using Amazon Cognito to assume an IAM role, and AWS Security Token Service (STS) to obtain security credentials to write data to CloudWatch RUM. This is beneficial for high throughput use cases where a high volume of requests may be subject to Cognito’s quota limits leading to throttling and potentially failure in ingesting data to RUM. With a public resource policy, no such limits apply. Anyone can send data to CloudWatch RUM including unauthenticated users and clients. In addition, you can use AWS Global context keys to use these policies to block certain IPs or disable clients sending data to RUM. You can configure these policies on the AWS console or via code using AWS CloudFormation. These enhancements are available in all regions where CloudWatch RUM is available at no additional cost to users. See documentation to know more about the feature, or see user guide to learn how to configure resource based policies for CloudWatch RUM.    

AWS CodeBuild managed images now support Node 22, Python 3.13, and Go 1.23. These new runtime versions are available in Linux x86, Arm, Windows and macOS platforms. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment.

For CodeBuild managed images based on Linux, you can specify a runtime of your choice in the runtime-versions section of your buildspec file. You can select specific major and minor versions supported by CodeBuild, or define a custom runtime version. Additionally with this release, we added commonly used tools that are available in GitHub Actions environments to better support customers using CodeBuild as a self-hosted runner option.

The updated images are available in all regions where CodeBuild is offered. For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page.

To learn more about docker images and runtime versions provided by CodeBuild, please visit our documentation or our image repository. To learn more about how to get started with CodeBuild, visit the AWS CodeBuild product page.
 

 

​AWS CodeBuild managed images now support Node 22, Python 3.13, and Go 1.23. These new runtime versions are available in Linux x86, Arm, Windows and macOS platforms. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment. For CodeBuild managed images based on Linux, you can specify a runtime of your choice in the runtime-versions section of your buildspec file. You can select specific major and minor versions supported by CodeBuild, or define a custom runtime version. Additionally with this release, we added commonly used tools that are available in GitHub Actions environments to better support customers using CodeBuild as a self-hosted runner option. The updated images are available in all regions where CodeBuild is offered. For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page. To learn more about docker images and runtime versions provided by CodeBuild, please visit our documentation or our image repository. To learn more about how to get started with CodeBuild, visit the AWS CodeBuild product page.    

Customers can use regional processing profiles for Amazon Nova understanding models (Amazon Nova Lite, Amazon Nova Micro, and Amazon Nova Pro) in Europe (Stockholm).

Amazon Bedrock is a fully managed service that offers a choice of high-performing large language models (LLMs) and other FMs from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities customers need to build generative AI applications with security, privacy, and responsible AI built in. These capabilities help you build tailored applications for multiple use cases across different industries, helping organizations unlock sustained growth from generative AI while ensuring customer trust and data governance.

To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.

 

​Customers can use regional processing profiles for Amazon Nova understanding models (Amazon Nova Lite, Amazon Nova Micro, and Amazon Nova Pro) in Europe (Stockholm).
Amazon Bedrock is a fully managed service that offers a choice of high-performing large language models (LLMs) and other FMs from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities customers need to build generative AI applications with security, privacy, and responsible AI built in. These capabilities help you build tailored applications for multiple use cases across different industries, helping organizations unlock sustained growth from generative AI while ensuring customer trust and data governance. To get started, visit the Amazon Bedrock page and see the Amazon Bedrock documentation for more details.  

Amazon QuickSight is now available in the AWS GovCloud (US-East) Region. AWS GovCloud (US) Regions are isolated AWS Regions designed to host sensitive data and regulated workloads in the cloud, assisting customers who have United States federal, state, or local government compliance requirements.

Amazon QuickSight is a fast, scalable, and fully managed Business Intelligence service that lets you easily create and publish interactive dashboards across your organization. QuickSight dashboards can be authored on any modern web browser with no clients to install or manage; dashboards can be shared with 10s of 1000s of users without the need to provision or manage any infrastructure. QuickSight dashboards can also be seamlessly embedded into your applications, portals, and websites to provide rich, interactive analytics for end-users.

With this launch, QuickSight expands to 22 regions, including: US East (Ohio and N. Virginia), US West (Oregon), Europe (Stockholm, Paris, Frankfurt, Ireland, London, Milan and Zurich), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Beijing, Tokyo and Jakarta), Canada (Central), South America (São Paulo), Africa (Cape Town) and AWS GovCloud (US-East, US-West).

To learn more about Amazon QuickSight, please see our product page, documentation and available regions here.

 

​Amazon QuickSight is now available in the AWS GovCloud (US-East) Region. AWS GovCloud (US) Regions are isolated AWS Regions designed to host sensitive data and regulated workloads in the cloud, assisting customers who have United States federal, state, or local government compliance requirements. Amazon QuickSight is a fast, scalable, and fully managed Business Intelligence service that lets you easily create and publish interactive dashboards across your organization. QuickSight dashboards can be authored on any modern web browser with no clients to install or manage; dashboards can be shared with 10s of 1000s of users without the need to provision or manage any infrastructure. QuickSight dashboards can also be seamlessly embedded into your applications, portals, and websites to provide rich, interactive analytics for end-users. With this launch, QuickSight expands to 22 regions, including: US East (Ohio and N. Virginia), US West (Oregon), Europe (Stockholm, Paris, Frankfurt, Ireland, London, Milan and Zurich), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Beijing, Tokyo and Jakarta), Canada (Central), South America (São Paulo), Africa (Cape Town) and AWS GovCloud (US-East, US-West). To learn more about Amazon QuickSight, please see our product page, documentation and available regions here.  

Today, we are announcing the general availability of Amazon Bedrock Data Automation (BDA), a feature of Amazon Bedrock that enables developers to automate the generation of valuable insights from unstructured multimodal content such as documents, images, video, and audio to build GenAI-based applications. By leveraging BDA, developers can reduce development time and effort, making it easier to build intelligent document processing, media analysis, and other multimodal data-centric automation solutions. BDA can be used as a standalone feature or as a parser in Amazon Knowledge Bases RAG workflows. Further, Amazon Q Business now uses BDA to process multimodal assets and deliver insights.

In this GA release, we improved document accuracy across a variety of document types, enhanced scene-level and full video summarization accuracy, added support for detection of 35,000+ company logos in images and videos, and added support for AWS cross-region inference to optimize routing across regions within your geography to maximize throughput. BDA also added a number of security, governance, and manageability capabilities such as AWS Key Management Service (KMS) Customer Managed Keys (CMKs) support for encryption, AWS PrivateLink to connect directly to the BDA APIs in your virtual private cloud (VPC) instead of connecting over the internet, and tagging of BDA resources and jobs to track costs and enforce tag-based access policies in Amazon Identity and Access Management (IAM).

Amazon Bedrock Data Automation is now generally available in the US West (Oregon) and US East (N. Virginia) AWS Regions.

To learn more, visit the Bedrock Data Automation page.

 

​Today, we are announcing the general availability of Amazon Bedrock Data Automation (BDA), a feature of Amazon Bedrock that enables developers to automate the generation of valuable insights from unstructured multimodal content such as documents, images, video, and audio to build GenAI-based applications. By leveraging BDA, developers can reduce development time and effort, making it easier to build intelligent document processing, media analysis, and other multimodal data-centric automation solutions. BDA can be used as a standalone feature or as a parser in Amazon Knowledge Bases RAG workflows. Further, Amazon Q Business now uses BDA to process multimodal assets and deliver insights. In this GA release, we improved document accuracy across a variety of document types, enhanced scene-level and full video summarization accuracy, added support for detection of 35,000+ company logos in images and videos, and added support for AWS cross-region inference to optimize routing across regions within your geography to maximize throughput. BDA also added a number of security, governance, and manageability capabilities such as AWS Key Management Service (KMS) Customer Managed Keys (CMKs) support for encryption, AWS PrivateLink to connect directly to the BDA APIs in your virtual private cloud (VPC) instead of connecting over the internet, and tagging of BDA resources and jobs to track costs and enforce tag-based access policies in Amazon Identity and Access Management (IAM). Amazon Bedrock Data Automation is now generally available in the US West (Oregon) and US East (N. Virginia) AWS Regions. To learn more, visit the Bedrock Data Automation page.