Amazon Q in QuickSight is now generally available in Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Tokyo), Europe (Stockholm), Europe (Paris), Europe (Zurich) and US East (Ohio), adding to our existing regions: Asia Pacific (Mumbai), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), South America (São Paulo), US East (N. Virginia), and US West (Oregon).

This latest expansion brings the power of Generative Business Intelligence to more customers worldwide, enabling them to leverage natural language capabilities of Amazon Q to quickly extract insights from data, make better business decisions, and accelerate the work of business analysts.

With Amazon Q in QuickSight, users can generate documents, slide decks, and executive summaries explaining data and providing recommendations tailored to their business. The data Q&A experience empowers users to confidently answer questions of data, even those not covered by existing dashboards.

QuickSight Scenarios allows for guided step-by-step deeper exploration of past trends, future scenarios and modeling of solutions in natural language without the need of specialized skills. Scenarios is now generally available to QuickSight Pro users in Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (London), Europe (Paris), and US East (Ohio) in addition to existing regions : US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Europe (Ireland)

This launch expands availability of Amazon Q in QuickSight capabilities within existing QuickSight Regions, reducing latency to access services and helping customers meet data residency compliance.

Amazon Q in QuickSight is not trained on customer data, and its governance and data security features meet the most stringent requirements for enterprise and government customers.

To learn more visit the Amazon Q in QuickSight product page and try it FREE for 30-days.

 

​Amazon Q in QuickSight is now generally available in Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Tokyo), Europe (Stockholm), Europe (Paris), Europe (Zurich) and US East (Ohio), adding to our existing regions: Asia Pacific (Mumbai), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), South America (São Paulo), US East (N. Virginia), and US West (Oregon). This latest expansion brings the power of Generative Business Intelligence to more customers worldwide, enabling them to leverage natural language capabilities of Amazon Q to quickly extract insights from data, make better business decisions, and accelerate the work of business analysts. With Amazon Q in QuickSight, users can generate documents, slide decks, and executive summaries explaining data and providing recommendations tailored to their business. The data Q&A experience empowers users to confidently answer questions of data, even those not covered by existing dashboards. QuickSight Scenarios allows for guided step-by-step deeper exploration of past trends, future scenarios and modeling of solutions in natural language without the need of specialized skills. Scenarios is now generally available to QuickSight Pro users in Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (London), Europe (Paris), and US East (Ohio) in addition to existing regions : US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Europe (Ireland) This launch expands availability of Amazon Q in QuickSight capabilities within existing QuickSight Regions, reducing latency to access services and helping customers meet data residency compliance. Amazon Q in QuickSight is not trained on customer data, and its governance and data security features meet the most stringent requirements for enterprise and government customers. To learn more visit the Amazon Q in QuickSight product page and try it FREE for 30-days.  

AWS Config now supports 12 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources.

With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators.

You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available:

Resource Types

AWS::BackupGateway::Hypervisor

AWS::CloudFront::PublicKey

AWS::BCMDataExports::Export

AWS::EntityResolution::IdMappingWorkflow

AWS::CloudFormation::GuardHook

AWS::S3Tables::TableBucket

AWS::EntityResolution::SchemaMapping

AWS::IoT::DomainConfiguration

AWS::PCAConnectorAD::DirectoryRegistration

AWS::RDS::Integration

AWS::Bedrock::Guardrail

AWS::Bedrock::KnowledgeBase

To view the complete list of AWS Config supported resource types, see supported resource types page.

 

​AWS Config now supports 12 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources. With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators. You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available:

Resource Types

AWS::BackupGateway::Hypervisor

AWS::CloudFront::PublicKey

AWS::BCMDataExports::Export

AWS::EntityResolution::IdMappingWorkflow

AWS::CloudFormation::GuardHook

AWS::S3Tables::TableBucket

AWS::EntityResolution::SchemaMapping

AWS::IoT::DomainConfiguration

AWS::PCAConnectorAD::DirectoryRegistration

AWS::RDS::Integration

AWS::Bedrock::Guardrail

AWS::Bedrock::KnowledgeBase

To view the complete list of AWS Config supported resource types, see supported resource types page.  

Today, we’re announcing the integration of Amazon Neptune Analytics with Mem0, an open-source, agentic memory system purpose-built for generative AI (GenAI) applications. With this launch, customers can use Neptune as the graph store for memory retrieval and reasoning, enabling long-term memory for AI agents across richly connected graphs—powering more personalized and context-aware AI experiences.

This integration allows Mem0 users to store and query memory graphs at scale, unlocking advanced use cases where LLMs need to learn from each interaction, becoming more personalized and effective over time. It enables graph-native long-term memory for LLMs by using Neptune as an external memory store, improving response quality through multi-hop graph reasoning, and supporting hybrid retrieval across graph, vector, and keyword modalities.

Mem0 is a self-improving memory layer that powers personalized, cost-efficient GenAI experiences. To learn more about the Neptune–Mem0 integration, visit the User Guide.

 

​Today, we’re announcing the integration of Amazon Neptune Analytics with Mem0, an open-source, agentic memory system purpose-built for generative AI (GenAI) applications. With this launch, customers can use Neptune as the graph store for memory retrieval and reasoning, enabling long-term memory for AI agents across richly connected graphs—powering more personalized and context-aware AI experiences. This integration allows Mem0 users to store and query memory graphs at scale, unlocking advanced use cases where LLMs need to learn from each interaction, becoming more personalized and effective over time. It enables graph-native long-term memory for LLMs by using Neptune as an external memory store, improving response quality through multi-hop graph reasoning, and supporting hybrid retrieval across graph, vector, and keyword modalities. Mem0 is a self-improving memory layer that powers personalized, cost-efficient GenAI experiences. To learn more about the Neptune–Mem0 integration, visit the User Guide.  

Starting today, you can build, train, and deploy machine learning (ML) models in Asia Pacific (Taipei).

Amazon SageMaker AI is a fully managed platform that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker AI removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models.

To learn more and get started, see SageMaker AI documentation and pricing page.

 

​Starting today, you can build, train, and deploy machine learning (ML) models in Asia Pacific (Taipei).
Amazon SageMaker AI is a fully managed platform that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker AI removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models.
To learn more and get started, see SageMaker AI documentation and pricing page.  

Customers that use Amazon Simple Notification Service (Amazon SNS) in the Mexico (Central) Region can now send text messages (SMS) to subscribers in more than 200 countries and territories.

With this launch, customers using SNS in the Mexico (Central) Region can send SMS messages via AWS End User Messaging. Amazon SNS is a fully managed pub/sub messaging service that enables message delivery to multiple endpoints including AWS Lambda, Amazon SQS, Amazon Data Firehose, mobile devices, and email.

Amazon SNS now supports the ability to send SMS in 30 AWS Regions.

More information:

• To learn more about sending SMS messages with SNS, visit Mobile text messaging (SMS).
• For the list of supported countries and regions, visit SMS Supported Regions and Countries.

 

​Customers that use Amazon Simple Notification Service (Amazon SNS) in the Mexico (Central) Region can now send text messages (SMS) to subscribers in more than 200 countries and territories. With this launch, customers using SNS in the Mexico (Central) Region can send SMS messages via AWS End User Messaging. Amazon SNS is a fully managed pub/sub messaging service that enables message delivery to multiple endpoints including AWS Lambda, Amazon SQS, Amazon Data Firehose, mobile devices, and email. Amazon SNS now supports the ability to send SMS in 30 AWS Regions. More information:

To learn more about sending SMS messages with SNS, visit Mobile text messaging (SMS).
For the list of supported countries and regions, visit SMS Supported Regions and Countries.  

Today, as we announce general availability of Oracle Database@AWS, we are launching a set of new AWS Networking capabilities that allow customers to easily build enterprise applications and services using Oracle Database@AWS. With this launch, customers can seamlessly connect their Oracle Database@AWS (ODB) networks with VPCs and on-premises networks and can establish secure access to AWS services natively from their ODB networks.

First, customers want to easily connect their Oracle Exadata database workloads in the ODB network to applications in VPCs and on-premises networks. Customers can use the integration with AWS Transit Gateway – to simplify connectivity at scale, AWS Cloud WAN – to connect global networks, and Amazon VPC Lattice – for secure service-to-service connectivity, to simplify their hybrid network connectivity with minimal networking changes. Second, customers want the ability to publish their database backups to their S3 buckets. With native connectivity between the ODB network and AWS services, powered by Amazon VPC Lattice, customers can set up private and secure access from the ODB network to Amazon S3. Last, customers want to maintain robust security and resource isolation, by launching their Oracle Exadata database and applications in different AWS accounts, while peering them for low-latency connectivity. Customer can now use the AWS RAM integration for cross-account peering support. These integrations enable customers to migrate and run production workloads on Oracle Exadata Database Service and Oracle Autonomous Database on Dedicated Exadata infrastructure within AWS.

Oracle Database@AWS networking capabilities are available in US East (N. Virginia) and US West (Oregon) AWS Regions. To get started, customers can use the AWS Management Console to provision and manage their Oracle Database@AWS resources. To learn more about the networking capabilities, see the blog, and documentation. For pricing, see product page per integration.

 

​Today, as we announce general availability of Oracle Database@AWS, we are launching a set of new AWS Networking capabilities that allow customers to easily build enterprise applications and services using Oracle Database@AWS. With this launch, customers can seamlessly connect their Oracle Database@AWS (ODB) networks with VPCs and on-premises networks and can establish secure access to AWS services natively from their ODB networks. First, customers want to easily connect their Oracle Exadata database workloads in the ODB network to applications in VPCs and on-premises networks. Customers can use the integration with AWS Transit Gateway – to simplify connectivity at scale, AWS Cloud WAN – to connect global networks, and Amazon VPC Lattice – for secure service-to-service connectivity, to simplify their hybrid network connectivity with minimal networking changes. Second, customers want the ability to publish their database backups to their S3 buckets. With native connectivity between the ODB network and AWS services, powered by Amazon VPC Lattice, customers can set up private and secure access from the ODB network to Amazon S3. Last, customers want to maintain robust security and resource isolation, by launching their Oracle Exadata database and applications in different AWS accounts, while peering them for low-latency connectivity. Customer can now use the AWS RAM integration for cross-account peering support. These integrations enable customers to migrate and run production workloads on Oracle Exadata Database Service and Oracle Autonomous Database on Dedicated Exadata infrastructure within AWS. Oracle Database@AWS networking capabilities are available in US East (N. Virginia) and US West (Oregon) AWS Regions. To get started, customers can use the AWS Management Console to provision and manage their Oracle Database@AWS resources. To learn more about the networking capabilities, see the blog, and documentation. For pricing, see product page per integration.  

With VPC Lattice support for Oracle Database@AWS (ODB) you can now connect your applications in VPCs and on-premises to your ODB network. You can also leverage VPC Lattice to privately and securely access Amazon S3 and Amazon Redshift from your Oracle Exadata workloads.

With this launch, your ODB databases can easily connect to AWS services, HTTP APIs and TCP applications, across thousands of VPCs and on-premises, without the need to setup complex networking. VPC Lattice simplifies network management and provides centralized visibility. You can also use ODB managed integrations (powered by VPC Lattice) to privately and securely access Amazon S3 and Amazon Redshift. With a few clicks, you can enable OCI managed backup of your ODB databases to Amazon S3, or configure your own Amazon S3 backup. Additionally, the Zero-ETL integration connects ODB databases to Amazon Redshift to analyze data across multiple databases.

VPC Lattice support is available in all AWS Regions where Oracle Database@AWS is generally available.

To get started, use the AWS Management Console to provision Oracle Database@AWS resources. You can use the AWS CLI, SDK or AWS Management Console to configure VPC Lattice resources. To learn more, please read the launch blog, Amazon VPC Lattice and Oracle Database@AWS documentation.

 

​With VPC Lattice support for Oracle Database@AWS (ODB) you can now connect your applications in VPCs and on-premises to your ODB network. You can also leverage VPC Lattice to privately and securely access Amazon S3 and Amazon Redshift from your Oracle Exadata workloads. With this launch, your ODB databases can easily connect to AWS services, HTTP APIs and TCP applications, across thousands of VPCs and on-premises, without the need to setup complex networking. VPC Lattice simplifies network management and provides centralized visibility. You can also use ODB managed integrations (powered by VPC Lattice) to privately and securely access Amazon S3 and Amazon Redshift. With a few clicks, you can enable OCI managed backup of your ODB databases to Amazon S3, or configure your own Amazon S3 backup. Additionally, the Zero-ETL integration connects ODB databases to Amazon Redshift to analyze data across multiple databases. VPC Lattice support is available in all AWS Regions where Oracle Database@AWS is generally available. To get started, use the AWS Management Console to provision Oracle Database@AWS resources. You can use the AWS CLI, SDK or AWS Management Console to configure VPC Lattice resources. To learn more, please read the launch blog, Amazon VPC Lattice and Oracle Database@AWS documentation.  

Today, AWS launches AWS Parallel Computing Service (PCS) in the AWS Europe (London) region, enabling you to easily build and manage High Performance Computing (HPC) clusters using the Slurm workload manager.

AWS PCS is a managed service that makes it easier for you to run and scale your high performance computing (HPC) workloads and build scientific and engineering models on AWS using Slurm. You can use AWS PCS to build complete, elastic environments that integrate compute, storage, networking, and visualization tools. AWS PCS simplifies cluster operations with managed updates and built-in observability features, helping to remove the burden of maintenance. You can work in a familiar environment, focusing on your research and innovation instead of worrying about infrastructure.

To get started, visit the AWS PCS page and the AWS PCS documentation.

 

​Today, AWS launches AWS Parallel Computing Service (PCS) in the AWS Europe (London) region, enabling you to easily build and manage High Performance Computing (HPC) clusters using the Slurm workload manager. AWS PCS is a managed service that makes it easier for you to run and scale your high performance computing (HPC) workloads and build scientific and engineering models on AWS using Slurm. You can use AWS PCS to build complete, elastic environments that integrate compute, storage, networking, and visualization tools. AWS PCS simplifies cluster operations with managed updates and built-in observability features, helping to remove the burden of maintenance. You can work in a familiar environment, focusing on your research and innovation instead of worrying about infrastructure. To get started, visit the AWS PCS page and the AWS PCS documentation.  

Today, AWS announces two new Model Context Protocol (MCP) servers in the AWS Labs MCP open-source repository: CloudWatch MCP server and Application Signals MCP server. These servers enable AI agents to leverage comprehensive observability capabilities for automated troubleshooting and monitoring. The MCP servers allow AI assistants to analyze metrics, alarms, logs, traces, and service health data across your AWS environment to quickly identify and diagnose issues through simple conversational interfaces.

The MCP servers provide curated sets of tools designed specifically for operational troubleshooting scenarios. The CloudWatch MCP server supports alarm-based incident response, metric analysis, and log pattern detection, while the Application Signals MCP server enables service health monitoring through Service Level Objectives (SLOs), and automated root cause analysis using OpenTelemetry data. By leveraging the MCP standard, AI agents can perform complex troubleshooting workflows through natural language interactions, from analyzing alarm patterns, and metric anomalies to investigating service health issues and querying logs and traces. Rather than requiring developers to manually navigate multiple AWS consoles and APIs, these MCP servers enable AI agents to orchestrate these interactions intelligently while reducing the development times typically required for API integrations.

The CloudWatch MCP server can be used with CloudWatch in all AWS regions, and the Application Signals MCP server can be used in all regions where Application Signals is available.

To download and try out these open-source MCP servers locally with your AI-enabled IDE of choice, visit the AWS Labs MCP open-source repository.

 

​Today, AWS announces two new Model Context Protocol (MCP) servers in the AWS Labs MCP open-source repository: CloudWatch MCP server and Application Signals MCP server. These servers enable AI agents to leverage comprehensive observability capabilities for automated troubleshooting and monitoring. The MCP servers allow AI assistants to analyze metrics, alarms, logs, traces, and service health data across your AWS environment to quickly identify and diagnose issues through simple conversational interfaces. The MCP servers provide curated sets of tools designed specifically for operational troubleshooting scenarios. The CloudWatch MCP server supports alarm-based incident response, metric analysis, and log pattern detection, while the Application Signals MCP server enables service health monitoring through Service Level Objectives (SLOs), and automated root cause analysis using OpenTelemetry data. By leveraging the MCP standard, AI agents can perform complex troubleshooting workflows through natural language interactions, from analyzing alarm patterns, and metric anomalies to investigating service health issues and querying logs and traces. Rather than requiring developers to manually navigate multiple AWS consoles and APIs, these MCP servers enable AI agents to orchestrate these interactions intelligently while reducing the development times typically required for API integrations. The CloudWatch MCP server can be used with CloudWatch in all AWS regions, and the Application Signals MCP server can be used in all regions where Application Signals is available. To download and try out these open-source MCP servers locally with your AI-enabled IDE of choice, visit the AWS Labs MCP open-source repository.  

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports Cumulative Update (CU) 19 for Microsoft SQL Server 2022. This update is available for SQL Server Developer, Web, Standard, and Enterprise editions, and includes performance improvements, security fixes, and bug fixes. For more details about the improvements in this update, please review Microsoft KB5054531 release notes.

We recommend upgrading to this CU as it includes security fixes. You can upgrade with just a few clicks in the Amazon RDS Management Console or by using the AWS SDK or CLI. Learn more about upgrading your database instances from the Amazon RDS Custom User Guide.

This CU is available in all AWS Regions where Amazon RDS Custom for SQL Server is available.

RDS Custom is a managed database service that allows customization of the underlying operating system and database environment. RDS Custom for SQL Server supports two licensing models: License Included (LI) and Bring Your Own Media (BYOM). By using Bring Your Own Media (BYOM), customers can use their existing SQL Server licenses with Amazon RDS Custom for SQL Server. See Amazon RDS Custom Pricing for pricing details and regional availability.

 

​Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports Cumulative Update (CU) 19 for Microsoft SQL Server 2022. This update is available for SQL Server Developer, Web, Standard, and Enterprise editions, and includes performance improvements, security fixes, and bug fixes. For more details about the improvements in this update, please review Microsoft KB5054531 release notes. We recommend upgrading to this CU as it includes security fixes. You can upgrade with just a few clicks in the Amazon RDS Management Console or by using the AWS SDK or CLI. Learn more about upgrading your database instances from the Amazon RDS Custom User Guide. This CU is available in all AWS Regions where Amazon RDS Custom for SQL Server is available. RDS Custom is a managed database service that allows customization of the underlying operating system and database environment. RDS Custom for SQL Server supports two licensing models: License Included (LI) and Bring Your Own Media (BYOM). By using Bring Your Own Media (BYOM), customers can use their existing SQL Server licenses with Amazon RDS Custom for SQL Server. See Amazon RDS Custom Pricing for pricing details and regional availability.