Presentamos Azure AI Foundry Labs: Un centro para las últimas investigaciones y experimentos de IA en Microsoft

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​The post Presentamos Azure AI Foundry Labs: Un centro para las últimas investigaciones y experimentos de IA en Microsoft appeared first on Source LATAM.  

AWS CodePipeline now offers a redesigned console experience that helps you monitor and troubleshoot your pipeline releases more effectively.

The new horizontal pipeline view displays stages and actions from left to right, results in a stronger visual hierarchy, which helps you to better locate and understand stage and action execution status. This visual update also makes it easier for you to focus on the key information, and find what you are looking for more effectively while preserving the familiar and consistent experience of the current CodePipeline console. The new layout also optimizes information density by reducing unused space, leading to more pipeline release information visible on the screen, which improves the experience to serve pipelines with a large number of stages and actions.

This feature is available in all regions where AWS CodePipeline is supported, except the AWS GovCloud (US) Regions and the China Regions. For more information about AWS CodePipeline, visit our product page.

​AWS CodePipeline now offers a redesigned console experience that helps you monitor and troubleshoot your pipeline releases more effectively. The new horizontal pipeline view displays stages and actions from left to right, results in a stronger visual hierarchy, which helps you to better locate and understand stage and action execution status. This visual update also makes it easier for you to focus on the key information, and find what you are looking for more effectively while preserving the familiar and consistent experience of the current CodePipeline console. The new layout also optimizes information density by reducing unused space, leading to more pipeline release information visible on the screen, which improves the experience to serve pipelines with a large number of stages and actions. This feature is available in all regions where AWS CodePipeline is supported, except the AWS GovCloud (US) Regions and the China Regions. For more information about AWS CodePipeline, visit our product page.  

Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Spatial Patch Bundle (SPB) for the January 2025 Release Update (RU) for Oracle Database version 19c. This update delivers important fixes for Oracle Spatial and Graph functionality, helping ensure reliable and optimal performance for your spatial operations.

You can now create new DB instances or upgrade existing ones to engine version ‘19.0.0.0.ru-2025-01.spb-1.r1’. The SPB engine version will be visible in the AWS Console by selecting the «Spatial Patch Bundle Engine Versions» checkbox in the engine version selector, making it simple to identify and implement the latest spatial patches for your database environment.

To learn more about Oracle SPBs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes. For more information about the AWS Regions where Amazon RDS for Oracle is available, see the AWS Region table.
 

​Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Spatial Patch Bundle (SPB) for the January 2025 Release Update (RU) for Oracle Database version 19c. This update delivers important fixes for Oracle Spatial and Graph functionality, helping ensure reliable and optimal performance for your spatial operations. You can now create new DB instances or upgrade existing ones to engine version ‘19.0.0.0.ru-2025-01.spb-1.r1’. The SPB engine version will be visible in the AWS Console by selecting the «Spatial Patch Bundle Engine Versions» checkbox in the engine version selector, making it simple to identify and implement the latest spatial patches for your database environment. To learn more about Oracle SPBs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes. For more information about the AWS Regions where Amazon RDS for Oracle is available, see the AWS Region table.    

Amazon Bedrock Guardrails announces an increase in default service quota limits enabling you to scale your generative AI applications for higher traffic. Bedrock Guardrails provides configurable safeguards to filter undesirable and harmful content across different categories and prompt attacks, topic filters to define and disallow specific topics, sensitive information filters to redact personally identifiable information (PII), word filters to block specific words, and detect model hallucinations by detecting grounding and relevance of model responses as well as identify, correct, and explain factual claims in model responses using Automated Reasoning . These policies can be tailored to your specific use cases and responsible AI policies. Guardrails can be applied across any foundation model including those hosted with Amazon Bedrock, self-hosted models, and third-party models using the ApplyGuardrail API, providing a consistent user experience and standardizing safety and privacy controls.

Starting today, Bedrock Guardrails enables you to scale your generative AI applications for higher traffic loads with increased service quota limits that help process higher transactions per second (TPS) and higher text units per second (TUPS). With this increase, you can now process up to 50 calls per second using the ApplyGuardrail API, a 2x increase from the previous limit of 25 calls per second. Content filters, sensitive information filters, and word filters can now process up to 200 TUPS, a 8x increase from the previous limits of 25 TUPS.

These limits are available in US East (N. Virginia) and US West (Oregon) AWS regions.

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

​Amazon Bedrock Guardrails announces an increase in default service quota limits enabling you to scale your generative AI applications for higher traffic. Bedrock Guardrails provides configurable safeguards to filter undesirable and harmful content across different categories and prompt attacks, topic filters to define and disallow specific topics, sensitive information filters to redact personally identifiable information (PII), word filters to block specific words, and detect model hallucinations by detecting grounding and relevance of model responses as well as identify, correct, and explain factual claims in model responses using Automated Reasoning . These policies can be tailored to your specific use cases and responsible AI policies. Guardrails can be applied across any foundation model including those hosted with Amazon Bedrock, self-hosted models, and third-party models using the ApplyGuardrail API, providing a consistent user experience and standardizing safety and privacy controls. Starting today, Bedrock Guardrails enables you to scale your generative AI applications for higher traffic loads with increased service quota limits that help process higher transactions per second (TPS) and higher text units per second (TUPS). With this increase, you can now process up to 50 calls per second using the ApplyGuardrail API, a 2x increase from the previous limit of 25 calls per second. Content filters, sensitive information filters, and word filters can now process up to 200 TUPS, a 8x increase from the previous limits of 25 TUPS. These limits are available in US East (N. Virginia) and US West (Oregon) AWS regions. To learn more, see the technical documentation and the Bedrock Guardrails product page.  

We are excited to announce that Amazon Location Service now supports AWS PrivateLink integration, enabling customers to establish private connectivity between their VPCs and Amazon Location Service without data ever traversing the public internet.

With this new capability, customers can now access Amazon Location Service APIs through private IP addresses within their VPC, significantly enhancing their security posture. This integration simplifies network architecture by eliminating the need for internet gateways, NAT devices, or public IP addresses, while helping customers meet strict regulatory and compliance requirements by keeping all traffic within the AWS network.

Setting up AWS PrivateLink for Amazon Location Service is straightforward. Customers can create interface VPC endpoints through the AWS Management Console or AWS Command Line Interface (AWS CLI) commands. Once configured, applications can immediately begin accessing Amazon Location Service APIs using private IP addresses, with all traffic remaining secure within the AWS network.

To learn more about using AWS PrivateLink with Amazon Location, see the Amazon Location Service developer guide.
 

​We are excited to announce that Amazon Location Service now supports AWS PrivateLink integration, enabling customers to establish private connectivity between their VPCs and Amazon Location Service without data ever traversing the public internet. With this new capability, customers can now access Amazon Location Service APIs through private IP addresses within their VPC, significantly enhancing their security posture. This integration simplifies network architecture by eliminating the need for internet gateways, NAT devices, or public IP addresses, while helping customers meet strict regulatory and compliance requirements by keeping all traffic within the AWS network. Setting up AWS PrivateLink for Amazon Location Service is straightforward. Customers can create interface VPC endpoints through the AWS Management Console or AWS Command Line Interface (AWS CLI) commands. Once configured, applications can immediately begin accessing Amazon Location Service APIs using private IP addresses, with all traffic remaining secure within the AWS network. To learn more about using AWS PrivateLink with Amazon Location, see the Amazon Location Service developer guide.    

Starting today, Amazon EC2 High Memory instances with 3TiB of memory (u-3tb1.56xlarge) is available in the Europe (Zurich) region. Customers can start using these new High Memory instances with On-Demand (OD) and Savings Plan purchase options.

Amazon EC2 High Memory instances are certified by SAP for running Business Suite on HANA, SAP S/4HANA, Data Mart Solutions on HANA, Business Warehouse on HANA, and SAP BW/4HANA in production environments. For details, see the Certified and Supported SAP HANA Hardware Directory.

For information on how to get started with your SAP HANA migration to EC2 High Memory instances, view the Migrating SAP HANA on AWS to an EC2 High Memory Instance documentation. To hear from Steven Jones, GM for SAP on AWS on what this launch means for our SAP customers, you can read his launch blog.
 

​Starting today, Amazon EC2 High Memory instances with 3TiB of memory (u-3tb1.56xlarge) is available in the Europe (Zurich) region. Customers can start using these new High Memory instances with On-Demand (OD) and Savings Plan purchase options. Amazon EC2 High Memory instances are certified by SAP for running Business Suite on HANA, SAP S/4HANA, Data Mart Solutions on HANA, Business Warehouse on HANA, and SAP BW/4HANA in production environments. For details, see the Certified and Supported SAP HANA Hardware Directory. For information on how to get started with your SAP HANA migration to EC2 High Memory instances, view the Migrating SAP HANA on AWS to an EC2 High Memory Instance documentation. To hear from Steven Jones, GM for SAP on AWS on what this launch means for our SAP customers, you can read his launch blog.    

CloudWatch Database Insights announces support of databases hosted on Amazon Relational Database Service (RDS). Database Insights is a database observability solution that provides a curated experience designed for DevOps engineers, application developers, and database administrators (DBAs) to expedite database troubleshooting and gain a holistic view into their database fleet health.

Database Insights consolidates logs and metrics from your applications, your databases, and the operating systems on which they run into a unified view in the console. Using its pre-built dashboards, recommended alarms, and automated telemetry collection, you can monitor the health of your database fleets and use a guided troubleshooting experience to drill down to individual instances for root-cause analysis. Application developers can correlate the impact of database dependencies with the performance and availability of their business-critical applications. This is because they can drill down from the context of their application performance view in Amazon CloudWatch Application Signals to the specific dependent database in Database Insights.

You can get started with Database Insights by enabling it on your RDS databases using the RDS service console, AWS APIs, and SDKs. Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis.

Database Insights is available in all public AWS Regions and applies a new vCPU-based pricing – see pricing page for details. For further information, visit the Database Insights documentation.

​CloudWatch Database Insights announces support of databases hosted on Amazon Relational Database Service (RDS). Database Insights is a database observability solution that provides a curated experience designed for DevOps engineers, application developers, and database administrators (DBAs) to expedite database troubleshooting and gain a holistic view into their database fleet health. Database Insights consolidates logs and metrics from your applications, your databases, and the operating systems on which they run into a unified view in the console. Using its pre-built dashboards, recommended alarms, and automated telemetry collection, you can monitor the health of your database fleets and use a guided troubleshooting experience to drill down to individual instances for root-cause analysis. Application developers can correlate the impact of database dependencies with the performance and availability of their business-critical applications. This is because they can drill down from the context of their application performance view in Amazon CloudWatch Application Signals to the specific dependent database in Database Insights. You can get started with Database Insights by enabling it on your RDS databases using the RDS service console, AWS APIs, and SDKs. Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. Database Insights is available in all public AWS Regions and applies a new vCPU-based pricing – see pricing page for details. For further information, visit the Database Insights documentation.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in the AWS GovCloud (US-East) Region.

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

C7gd instances are now available in the following AWS regions: US East (N. Virginia, Ohio), US West (Oregon, N. California), Europe (Spain, Stockholm, Ireland, Frankfurt), Asia Pacific (Tokyo, Mumbai, Singapore, Sydney, Malaysia) and AWS GovCloud (US-East).
 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in the AWS GovCloud (US-East) Region. These Graviton3-based instances with DDR5 memory are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud. C7gd instances are now available in the following AWS regions: US East (N. Virginia, Ohio), US West (Oregon, N. California), Europe (Spain, Stockholm, Ireland, Frankfurt), Asia Pacific (Tokyo, Mumbai, Singapore, Sydney, Malaysia) and AWS GovCloud (US-East).    

AWS WAF enhances Service Quotas capabilities, enabling organizations to proactively monitor and manage quotas for their cloud deployments.

AWS WAF is a web application firewall that helps protect your web applications or APIs against common web exploits and bots that may affect availability, compromise security, or consume excessive resources. By leveraging AWS Service Quotas, you can quickly understand your applied service quota values for these WAF resources and request increases when needed. This enhanced integration brings three key benefits. First, you can now monitor the current utilization of your account-level quotas for WAF resources such as web ACLs, rule groups, and IP sets in the Service Quotas console. Second, certain service quota increase requests will now be auto-approved, enabling customers to access higher quotas faster. For example, smaller increases are usually automatically approved while larger requests are submitted to AWS Support. Lastly, you can now create Amazon CloudWatch alarms to notify you when your utilization of a given quota exceeds a configurable threshold. This enables you to better adapt your utilization based on your applied quota values and automate your quota increase requests.

You can access AWS Service Quotas through the AWS console, AWS APIs, and CLI. Integration with AWS Service Quotas is available in all AWS regions where AWS WAF is offered. You can learn more about AWS WAF by visiting Developer Guide.
 

​AWS WAF enhances Service Quotas capabilities, enabling organizations to proactively monitor and manage quotas for their cloud deployments. AWS WAF is a web application firewall that helps protect your web applications or APIs against common web exploits and bots that may affect availability, compromise security, or consume excessive resources. By leveraging AWS Service Quotas, you can quickly understand your applied service quota values for these WAF resources and request increases when needed. This enhanced integration brings three key benefits. First, you can now monitor the current utilization of your account-level quotas for WAF resources such as web ACLs, rule groups, and IP sets in the Service Quotas console. Second, certain service quota increase requests will now be auto-approved, enabling customers to access higher quotas faster. For example, smaller increases are usually automatically approved while larger requests are submitted to AWS Support. Lastly, you can now create Amazon CloudWatch alarms to notify you when your utilization of a given quota exceeds a configurable threshold. This enables you to better adapt your utilization based on your applied quota values and automate your quota increase requests. You can access AWS Service Quotas through the AWS console, AWS APIs, and CLI. Integration with AWS Service Quotas is available in all AWS regions where AWS WAF is offered. You can learn more about AWS WAF by visiting Developer Guide.    

Amazon Verified Permissions now supports the same JSON format for entity and context data, as the Cedar SDK. Developers can use this simpler format for authorization requests. This aligns the Amazon Verified Permissions API more closely with the open source Cedar SDK, and simplifies moving from the SDK to Amazon Verified Permissions or vice versa.

Amazon Verified Permissions is a permissions management and fine-grained authorization service for the applications that you build. Using Cedar, an expressive and analyzable open-source policy language, developers and admins can define policy-based access controls using roles and attributes for more granular, context-aware access control. For example, an HR application might call Amazon Verified Permissions (AVP) to determine if Alice is permitted to access Bob’s performance evaluation, given that she is in the HR Managers group. Customers can use Cedar JSON format to pass entity data describing the principal (Alice) and the resource (Bob’s performance evaluation).

This change is available in all AWS regions supported by Amazon Verified Permissions. The service will continue to support the old format, and so the change does not break existing application integrations. To learn more about using the Cedar JSON format, see Cedar JSON entity in the Cedar user guide and the Verified Permissions user guide. To learn more about Amazon Verified Permissions, visit the product page. For more information visit the Verified Permissions product page.
 

​Amazon Verified Permissions now supports the same JSON format for entity and context data, as the Cedar SDK. Developers can use this simpler format for authorization requests. This aligns the Amazon Verified Permissions API more closely with the open source Cedar SDK, and simplifies moving from the SDK to Amazon Verified Permissions or vice versa. Amazon Verified Permissions is a permissions management and fine-grained authorization service for the applications that you build. Using Cedar, an expressive and analyzable open-source policy language, developers and admins can define policy-based access controls using roles and attributes for more granular, context-aware access control. For example, an HR application might call Amazon Verified Permissions (AVP) to determine if Alice is permitted to access Bob’s performance evaluation, given that she is in the HR Managers group. Customers can use Cedar JSON format to pass entity data describing the principal (Alice) and the resource (Bob’s performance evaluation). This change is available in all AWS regions supported by Amazon Verified Permissions. The service will continue to support the old format, and so the change does not break existing application integrations. To learn more about using the Cedar JSON format, see Cedar JSON entity in the Cedar user guide and the Verified Permissions user guide. To learn more about Amazon Verified Permissions, visit the product page. For more information visit the Verified Permissions product page.