Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M6id instances are available in US West (N. California) Region. These instances are powered by 3rd generation Intel Xeon Scalable Ice Lake processors with an all-core turbo frequency of 3.5 GHz and up to 7.6 TB of local NVMe-based SSD block-level storage.

M6id instances are built on AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor, which delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security. Customers can take advantage of access to high-speed, low-latency local storage to scale performance of applications such data logging, distributed web-scale in-memory caches, in-memory databases, and real-time big data analytics.

These instances are generally available today in the US East (Ohio, N. Virginia), US West (Oregon, N. California), Canada West (Calgary), Canada (Central), Mexico (Central), South America (Sao Paulo), Asia Pacific (Tokyo, Sydney, Seoul, Singapore, Malaysia, Mumbai, Thailand), Europe (Zurich, Ireland, Frankfurt, London), Israel (Tel Aviv) Regions.

Customers can purchase the new instances via Savings Plans, Reserved, On-Demand, and Spot instances. To get started, visit AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit our product page for M6id.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M6id instances are available in US West (N. California) Region. These instances are powered by 3rd generation Intel Xeon Scalable Ice Lake processors with an all-core turbo frequency of 3.5 GHz and up to 7.6 TB of local NVMe-based SSD block-level storage. M6id instances are built on AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor, which delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security. Customers can take advantage of access to high-speed, low-latency local storage to scale performance of applications such data logging, distributed web-scale in-memory caches, in-memory databases, and real-time big data analytics. These instances are generally available today in the US East (Ohio, N. Virginia), US West (Oregon, N. California), Canada West (Calgary), Canada (Central), Mexico (Central), South America (Sao Paulo), Asia Pacific (Tokyo, Sydney, Seoul, Singapore, Malaysia, Mumbai, Thailand), Europe (Zurich, Ireland, Frankfurt, London), Israel (Tel Aviv) Regions. Customers can purchase the new instances via Savings Plans, Reserved, On-Demand, and Spot instances. To get started, visit AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit our product page for M6id.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R6id instances are available in Europe (Spain) Region. These instances are powered by 3rd generation Intel Xeon Scalable Ice Lake processors with an all-core turbo frequency of 3.5 GHz and up to 7.6 TB of local NVMe-based SSD block-level storage. R6id instances are built on AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor, which delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security. Customers can take advantage of access to high-speed, low-latency local storage to scale performance of applications such data logging, distributed web-scale in-memory caches, in-memory databases, and real-time big data analytics.

These instances are generally available today in the US East (Ohio, N.Virginia), US West (Oregon), Canada West (Calgary), Mexico (Central), Asia Pacific (Malaysia, Mumbai, Seoul, Singapore, Sydney, Thailand, Tokyo), Europe (Frankfurt, Ireland, London, Spain), Israel (Tel Aviv), and AWS GovCloud (US-West) Regions.

Customers can purchase the new instances via Savings Plans, Reserved, On-Demand, and Spot instances. To learn more, see Amazon R6id instances. To get started, visit AWS Command Line Interface (CLI), and AWS SDKs.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R6id instances are available in Europe (Spain) Region. These instances are powered by 3rd generation Intel Xeon Scalable Ice Lake processors with an all-core turbo frequency of 3.5 GHz and up to 7.6 TB of local NVMe-based SSD block-level storage. R6id instances are built on AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor, which delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security. Customers can take advantage of access to high-speed, low-latency local storage to scale performance of applications such data logging, distributed web-scale in-memory caches, in-memory databases, and real-time big data analytics. These instances are generally available today in the US East (Ohio, N.Virginia), US West (Oregon), Canada West (Calgary), Mexico (Central), Asia Pacific (Malaysia, Mumbai, Seoul, Singapore, Sydney, Thailand, Tokyo), Europe (Frankfurt, Ireland, London, Spain), Israel (Tel Aviv), and AWS GovCloud (US-West) Regions. Customers can purchase the new instances via Savings Plans, Reserved, On-Demand, and Spot instances. To learn more, see Amazon R6id instances. To get started, visit AWS Command Line Interface (CLI), and AWS SDKs.  

Amazon Lex now allows you to disable automatic intent switching during slot elicitation using request attributes. This new capability gives you more control over conversation flows by preventing unintended switches between intents while gathering required information from users. The feature helps maintain focused conversations and reduces the likelihood of interrupting the process.

This enhancement is particularly valuable for complex conversational flows where completing the current interaction is crucial before allowing transitions to other intents. By setting certain attributes, you can ensure that your bot stays focused on collecting all necessary slots, or conformations for the current intent, even if the user’s utterance matches another intent with higher confidence. This helps create more predictable and controlled conversation experiences, especially in scenarios like multi-step form filling or sequential information gathering.

This feature is supported for all Lex supported languages and is available in all AWS Regions where Amazon Lex operates.

To learn more about controlling intent switching behavior, please reference the Lex V2 Developer Guide.

 

​Amazon Lex now allows you to disable automatic intent switching during slot elicitation using request attributes. This new capability gives you more control over conversation flows by preventing unintended switches between intents while gathering required information from users. The feature helps maintain focused conversations and reduces the likelihood of interrupting the process. This enhancement is particularly valuable for complex conversational flows where completing the current interaction is crucial before allowing transitions to other intents. By setting certain attributes, you can ensure that your bot stays focused on collecting all necessary slots, or conformations for the current intent, even if the user’s utterance matches another intent with higher confidence. This helps create more predictable and controlled conversation experiences, especially in scenarios like multi-step form filling or sequential information gathering. This feature is supported for all Lex supported languages and is available in all AWS Regions where Amazon Lex operates. To learn more about controlling intent switching behavior, please reference the Lex V2 Developer Guide.  

AWS Transfer Family announces new configuration options for SFTP connectors, providing you more flexibility and performance when connecting with remote SFTP servers. These enhancements include support for OpenSSH key format for authentication, ability to discover remote server’s host key for validating server identity, and ability to perform concurrent remote operations for improved transfer performance.

SFTP connectors provide a fully managed and low-code capability to copy files between remote SFTP servers and Amazon S3. You can now authenticate connections to remote servers using OpenSSH keys, in addition to the existing option of using PEM-formatted keys. Your connectors can now scan the remote servers for their public host keys that are used to validate the host identity, eliminating the need for manual retrieval of this information from server administrators. To improve transfer performance, connectors can now create up to five parallel connections with remote servers. These enhancements provide you greater control when connecting with remote SFTP servers to execute file operations.

The new configuration options for SFTP connectors are available in all AWS Regions where the Transfer Family is available. To learn more about SFTP connectors, visit the documentation. To get started with Transfer Family’s SFTP offerings, take the self-paced SFTP workshop.
 

 

​AWS Transfer Family announces new configuration options for SFTP connectors, providing you more flexibility and performance when connecting with remote SFTP servers. These enhancements include support for OpenSSH key format for authentication, ability to discover remote server’s host key for validating server identity, and ability to perform concurrent remote operations for improved transfer performance. SFTP connectors provide a fully managed and low-code capability to copy files between remote SFTP servers and Amazon S3. You can now authenticate connections to remote servers using OpenSSH keys, in addition to the existing option of using PEM-formatted keys. Your connectors can now scan the remote servers for their public host keys that are used to validate the host identity, eliminating the need for manual retrieval of this information from server administrators. To improve transfer performance, connectors can now create up to five parallel connections with remote servers. These enhancements provide you greater control when connecting with remote SFTP servers to execute file operations. The new configuration options for SFTP connectors are available in all AWS Regions where the Transfer Family is available. To learn more about SFTP connectors, visit the documentation. To get started with Transfer Family’s SFTP offerings, take the self-paced SFTP workshop.    

Starting today, customers can use Amazon Managed Service for Apache Flink in the Mexico (Central) Region to build real-time stream processing applications.

Amazon Managed Service for Apache Flink makes it easier to transform and analyze streaming data in real time with Apache Flink. Apache Flink is an open source framework and engine for processing data streams. Amazon Managed Service for Apache Flink reduces the complexity of building and managing Apache Flink applications and integrates with Amazon Managed Streaming for Apache Kafka (Amazon MSK), Amazon Kinesis Data Streams, Amazon OpenSearch Service, Amazon DynamoDB streams, Amazon Simple Storage Service (Amazon S3), custom integrations, and more using built-in connectors.

You can learn more about Amazon Managed Service for Apache Flink here. For Amazon Managed Service for Apache Flink region availability, refer to the AWS Region Table.
 

 

​Starting today, customers can use Amazon Managed Service for Apache Flink in the Mexico (Central) Region to build real-time stream processing applications. Amazon Managed Service for Apache Flink makes it easier to transform and analyze streaming data in real time with Apache Flink. Apache Flink is an open source framework and engine for processing data streams. Amazon Managed Service for Apache Flink reduces the complexity of building and managing Apache Flink applications and integrates with Amazon Managed Streaming for Apache Kafka (Amazon MSK), Amazon Kinesis Data Streams, Amazon OpenSearch Service, Amazon DynamoDB streams, Amazon Simple Storage Service (Amazon S3), custom integrations, and more using built-in connectors. You can learn more about Amazon Managed Service for Apache Flink here. For Amazon Managed Service for Apache Flink region availability, refer to the AWS Region Table.    

Amazon SageMaker Catalog, part of the next generation of Amazon SageMaker, now supports enhanced search capabilities with exact-match and partial-match functionality for technical identifiers such as column and table names. This feature allows users to perform precise searches by enclosing terms within a qualifier such as double quotes (» «), helping them quickly locate assets with exact or partial technical names. For example, analysts can find specific columns faster, stewards can validate assets using naming patterns like «audit_», and engineers can identify temporary tables with prefixes like «temp_».

Building on SageMaker Catalog’s existing keyword and semantic search, this enhancement is designed for organizations managing large-scale data catalogs with complex naming conventions. For example, searching for «customer_id» returns only those assets with an exact match, while a query like «sales_» returns assets such as sales_summary and sales_data_2024. These capabilities help users quickly locate technical assets, improve data governance by reducing errors, and enhance collaboration.

Check out the product documentation to learn more about how to set up metadata rules for subscription and publishing workflows.

 

​Amazon SageMaker Catalog, part of the next generation of Amazon SageMaker, now supports enhanced search capabilities with exact-match and partial-match functionality for technical identifiers such as column and table names. This feature allows users to perform precise searches by enclosing terms within a qualifier such as double quotes (» «), helping them quickly locate assets with exact or partial technical names. For example, analysts can find specific columns faster, stewards can validate assets using naming patterns like «audit_», and engineers can identify temporary tables with prefixes like «temp_».
Building on SageMaker Catalog’s existing keyword and semantic search, this enhancement is designed for organizations managing large-scale data catalogs with complex naming conventions. For example, searching for «customer_id» returns only those assets with an exact match, while a query like «sales_» returns assets such as sales_summary and sales_data_2024. These capabilities help users quickly locate technical assets, improve data governance by reducing errors, and enhance collaboration. Check out the product documentation to learn more about how to set up metadata rules for subscription and publishing workflows.  

Anthropic’s Claude 3.7 Sonnet hybrid reasoning model, their most intelligent model to date, is now available through cross-region inference on Bedrock in Europe (Ireland), Europe (Paris), Europe (Frankfurt), and Europe (Stockholm). Claude 3.7 Sonnet represents a significant advancement in AI capabilities, offering both quick responses and extended, step-by-step thinking made visible to the user. This new model includes strong improvements in coding and brings enhanced performance across various tasks, like instruction following, math, and physics.

Claude 3.7 Sonnet introduces a unique approach to AI reasoning by integrating it seamlessly with other capabilities. Unlike traditional models that separate quick responses from those requiring deeper thought, Claude 3.7 Sonnet allows users to toggle between standard and extended thinking modes. In standard mode, it functions as an upgraded version of Claude 3.5 Sonnet. In extended thinking mode, it employs self-reflection to achieve improved results across a wide range of tasks. Amazon Bedrock customers can adjust how long the model thinks, offering a flexible trade-off between speed and answer quality. Additionally, users can control the reasoning budget by specifying a token limit, enabling more precise cost management.

Claude 3.7 Sonnet is also available on Amazon Bedrock in the US East (N. Virginia), US East (Ohio), and US West (Oregon) regions. To get started, visit the Amazon Bedrock console. Integrate it into your applications using the Amazon Bedrock API or SDK. For more information, see the AWS News Blog and Claude in Amazon Bedrock.

 

​Anthropic’s Claude 3.7 Sonnet hybrid reasoning model, their most intelligent model to date, is now available through cross-region inference on Bedrock in Europe (Ireland), Europe (Paris), Europe (Frankfurt), and Europe (Stockholm). Claude 3.7 Sonnet represents a significant advancement in AI capabilities, offering both quick responses and extended, step-by-step thinking made visible to the user. This new model includes strong improvements in coding and brings enhanced performance across various tasks, like instruction following, math, and physics. Claude 3.7 Sonnet introduces a unique approach to AI reasoning by integrating it seamlessly with other capabilities. Unlike traditional models that separate quick responses from those requiring deeper thought, Claude 3.7 Sonnet allows users to toggle between standard and extended thinking modes. In standard mode, it functions as an upgraded version of Claude 3.5 Sonnet. In extended thinking mode, it employs self-reflection to achieve improved results across a wide range of tasks. Amazon Bedrock customers can adjust how long the model thinks, offering a flexible trade-off between speed and answer quality. Additionally, users can control the reasoning budget by specifying a token limit, enabling more precise cost management. Claude 3.7 Sonnet is also available on Amazon Bedrock in the US East (N. Virginia), US East (Ohio), and US West (Oregon) regions. To get started, visit the Amazon Bedrock console. Integrate it into your applications using the Amazon Bedrock API or SDK. For more information, see the AWS News Blog and Claude in Amazon Bedrock.  

Cost Optimization Hub now supports DynamoDB and MemoryDB reservation recommendations. You can filter and aggregate recommendations across both services, making it easier to identify the highest cost-saving opportunities for DynamoDB and MemoryDB.

With this launch, you can view, consolidate, and prioritize reservation recommendations for DynamoDB and MemoryDB across your organization’s member accounts and AWS Regions through a single dashboard. Cost Optimization Hub’s comprehensive view enables you to see these recommendations as part of your total potential savings, helping you compare and prioritize them alongside other cost-saving opportunities.

DynamoDB and MemoryDB reservation recommendations are now available in Cost Optimization Hub across all AWS Regions where Cost Optimization Hub is supported.
 

 

​Cost Optimization Hub now supports DynamoDB and MemoryDB reservation recommendations. You can filter and aggregate recommendations across both services, making it easier to identify the highest cost-saving opportunities for DynamoDB and MemoryDB. With this launch, you can view, consolidate, and prioritize reservation recommendations for DynamoDB and MemoryDB across your organization’s member accounts and AWS Regions through a single dashboard. Cost Optimization Hub’s comprehensive view enables you to see these recommendations as part of your total potential savings, helping you compare and prioritize them alongside other cost-saving opportunities. DynamoDB and MemoryDB reservation recommendations are now available in Cost Optimization Hub across all AWS Regions where Cost Optimization Hub is supported.    

Amazon Relational Database Service (Amazon RDS) for Oracle now supports R6id and M6id instances. These instances offer up to 7.6 TB of NVMe-based local storage, making them well-suited for database workloads that require access to large amounts of intermediate data beyond the instance’s memory capacity. Customers can configure their Oracle database to use the local storage for temporary tablespace and Database Smart Flash Cache.

Operations such as sorts, hash joins, and aggregations can generate large amounts of intermediate data that doesn’t fit in memory and is stored in temporary tablespace. With R6id and M6id, Customers can place temporary tablespaces in the local storage instead of the Amazon EBS volume attached to their instance to reduce latency, improve throughput, and lower the provisioned IOPS.

Customers with Oracle Enterprise Edition license can configure Database Smart Flash Cache to use the local storage. When configured, Smart Flash Cache will use the local storage to keep frequently accessed data that doesn’t fit in memory and improve the read performance of the database.

You can launch the new instance in the Amazon RDS Management Console or using the AWS CLI. Refer Amazon RDS for Oracle Pricing for available instance configurations, pricing details, and region availability.

 

​Amazon Relational Database Service (Amazon RDS) for Oracle now supports R6id and M6id instances. These instances offer up to 7.6 TB of NVMe-based local storage, making them well-suited for database workloads that require access to large amounts of intermediate data beyond the instance’s memory capacity. Customers can configure their Oracle database to use the local storage for temporary tablespace and Database Smart Flash Cache. Operations such as sorts, hash joins, and aggregations can generate large amounts of intermediate data that doesn’t fit in memory and is stored in temporary tablespace. With R6id and M6id, Customers can place temporary tablespaces in the local storage instead of the Amazon EBS volume attached to their instance to reduce latency, improve throughput, and lower the provisioned IOPS. Customers with Oracle Enterprise Edition license can configure Database Smart Flash Cache to use the local storage. When configured, Smart Flash Cache will use the local storage to keep frequently accessed data that doesn’t fit in memory and improve the read performance of the database. You can launch the new instance in the Amazon RDS Management Console or using the AWS CLI. Refer Amazon RDS for Oracle Pricing for available instance configurations, pricing details, and region availability.  

We are excited to announce that Amazon SageMaker Studio now supports recovery mode, enabling users to regain access to their JupyterLab and Code Editor applications when configuration issues prevent normal startup.

Starting today, when users encounter application startup failures due to issues such as corrupted Conda configuration or insufficient storage space, they can launch their application in recovery mode on Studio UI or using AWS CLI. When configuration issues occur, users see a warning banner with the recommended solution and can choose to run their space in recovery mode. This simplified environment provides access to essential features like terminal and file explorer, allowing users to diagnose and fix configuration issues without administrator intervention. This functionality provides users with an important self-service mechanism, helping them minimize workspace downtime.

This feature is available in all AWS Regions where Amazon SageMaker Studio is currently available, excluding China Regions and GovCloud (US) Regions. To learn more, visit our documentation.

 

​We are excited to announce that Amazon SageMaker Studio now supports recovery mode, enabling users to regain access to their JupyterLab and Code Editor applications when configuration issues prevent normal startup. Starting today, when users encounter application startup failures due to issues such as corrupted Conda configuration or insufficient storage space, they can launch their application in recovery mode on Studio UI or using AWS CLI. When configuration issues occur, users see a warning banner with the recommended solution and can choose to run their space in recovery mode. This simplified environment provides access to essential features like terminal and file explorer, allowing users to diagnose and fix configuration issues without administrator intervention. This functionality provides users with an important self-service mechanism, helping them minimize workspace downtime. This feature is available in all AWS Regions where Amazon SageMaker Studio is currently available, excluding China Regions and GovCloud (US) Regions. To learn more, visit our documentation.