Amazon Neptune Analytics is now available in the Asia Pacific (Mumbai) Region. You can now create and manage Neptune Analytics graphs in the Asia Pacific (Mumbai) Region and run advanced graph analytics.

Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements Amazon Neptune Database, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that’s stored in Amazon S3.

To get started, you can create a new Neptune Analytics graphs using the AWS Management Console, or AWS CLI. For more information on pricing and region availability, refer to the Neptune pricing page.

 

​Amazon Neptune Analytics is now available in the Asia Pacific (Mumbai) Region. You can now create and manage Neptune Analytics graphs in the Asia Pacific (Mumbai) Region and run advanced graph analytics. Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements Amazon Neptune Database, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that’s stored in Amazon S3. To get started, you can create a new Neptune Analytics graphs using the AWS Management Console, or AWS CLI. For more information on pricing and region availability, refer to the Neptune pricing page.  

Starting today, AWS WAF’s Targeted Bot Control, Fraud, and DDoS Prevention Rule Group are available in the AWS Asia Pacific (Taipei), Asia Pacific (Bangkok), and Mexico (Central) regions. These features help customers to stay protected against sophisticated bots, application layer DDoS and account takeover attacks.

AWS WAF is a web application firewall that helps you protect your web application resources against common web exploits and bots that can affect availability, compromise security, or consume excessive resources.

To see the full list of regions where AWS WAF is currently available, visit the AWS Region Table. For more information about the service, visit the AWS WAF page. For more information about pricing, visit the AWS WAF Pricing page.

 

​Starting today, AWS WAF’s Targeted Bot Control, Fraud, and DDoS Prevention Rule Group are available in the AWS Asia Pacific (Taipei), Asia Pacific (Bangkok), and Mexico (Central) regions. These features help customers to stay protected against sophisticated bots, application layer DDoS and account takeover attacks.
AWS WAF is a web application firewall that helps you protect your web application resources against common web exploits and bots that can affect availability, compromise security, or consume excessive resources.
To see the full list of regions where AWS WAF is currently available, visit the AWS Region Table. For more information about the service, visit the AWS WAF page. For more information about pricing, visit the AWS WAF Pricing page.  

Amazon Relational Database Service (RDS) for Db2 now offers Reserved Instances with up to 47% cost savings compared to On-Demand prices. The option to use Reserved Instances is available for all supported instance types.

Amazon RDS for Db2 Reserved Instances provide size flexibility for both Bring Your Own License (BYOL) and Db2 license purchased through AWS Marketplace. With Reserved Instances size flexibility, the discounted rate for Reserved Instances automatically applies to usage of any size in the same instance family. For example, if you purchase a db.r7i.2xlarge Reserved Instance in US East (N. Virginia), the discounted rate of this Reserved Instance can automatically apply to 2 db.r7i.xlarge instances. For information on RDS Reserved Instances, refer to Reserved DB instances for Amazon RDS.

You can purchase Reserved Instances through the AWS Management Console, AWS CLI, or AWS SDK. For detailed pricing information and purchase options, refer to Amazon RDS for Db2 Pricing.

 

​Amazon Relational Database Service (RDS) for Db2 now offers Reserved Instances with up to 47% cost savings compared to On-Demand prices. The option to use Reserved Instances is available for all supported instance types. Amazon RDS for Db2 Reserved Instances provide size flexibility for both Bring Your Own License (BYOL) and Db2 license purchased through AWS Marketplace. With Reserved Instances size flexibility, the discounted rate for Reserved Instances automatically applies to usage of any size in the same instance family. For example, if you purchase a db.r7i.2xlarge Reserved Instance in US East (N. Virginia), the discounted rate of this Reserved Instance can automatically apply to 2 db.r7i.xlarge instances. For information on RDS Reserved Instances, refer to Reserved DB instances for Amazon RDS. You can purchase Reserved Instances through the AWS Management Console, AWS CLI, or AWS SDK. For detailed pricing information and purchase options, refer to Amazon RDS for Db2 Pricing.  

Today, AWS announces the general availability of new capabilities within AWS Billing and Cost Management that enable customers to manage their AWS spend across multiple organizations through a single AWS account. Customers can now share custom billing views containing cost management data with other AWS accounts outside their organization. Additionally, customers can combine multiple custom billing views to create new consolidated views. These features enable FinOps teams to create custom billing views containing cost management data for multiple organizations. These views can then be used to access cost management data across multiple organizations through Cost Explorer or set up budgets to monitor AWS costs.

With the new custom billing view capabilities, you can create consolidated views of cost management data spanning multiple organizations that can be accessed using AWS Cost Explorer and AWS Budgets, allowing you to monitor, analyze, and forecast spending patterns across multiple organizations. This helps customers operating multiple subsidiaries or business units as separate organizations on AWS manage their AWS spend through a single AWS account.

Support for custom billing views containing cost management data for multiple organizations is available in all AWS Regions, excluding AWS GovCloud Regions and the AWS China Regions. To get started with custom billing views, visit Billing View within the Cost Management Preferences page in the AWS Billing and Cost Management console and create a new custom billing view. To get started visit the Billing View user guide.

 

​Today, AWS announces the general availability of new capabilities within AWS Billing and Cost Management that enable customers to manage their AWS spend across multiple organizations through a single AWS account. Customers can now share custom billing views containing cost management data with other AWS accounts outside their organization. Additionally, customers can combine multiple custom billing views to create new consolidated views. These features enable FinOps teams to create custom billing views containing cost management data for multiple organizations. These views can then be used to access cost management data across multiple organizations through Cost Explorer or set up budgets to monitor AWS costs.
With the new custom billing view capabilities, you can create consolidated views of cost management data spanning multiple organizations that can be accessed using AWS Cost Explorer and AWS Budgets, allowing you to monitor, analyze, and forecast spending patterns across multiple organizations. This helps customers operating multiple subsidiaries or business units as separate organizations on AWS manage their AWS spend through a single AWS account.
Support for custom billing views containing cost management data for multiple organizations is available in all AWS Regions, excluding AWS GovCloud Regions and the AWS China Regions. To get started with custom billing views, visit Billing View within the Cost Management Preferences page in the AWS Billing and Cost Management console and create a new custom billing view. To get started visit the Billing View user guide.  

Amazon Redshift Concurrency Scaling is now available in the AWS Africa (Cape Town), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Osaka), Asia Pacific (Thailand), Europe (Milan), Middle East (Bahrain), Mexico (Central) and AWS GovCloud (US-West) regions. With the Amazon Redshift Concurrency Scaling feature, you can now support thousands of concurrent users and concurrent queries, with consistently fast query performance.

Amazon Redshift Concurrency Scaling elastically scales query processing power to provide consistently fast performance for hundreds of concurrent queries. Concurrency Scaling resources are added to your Redshift cluster transparently in seconds, allowing for increased concurrency to process queries with minimal wait time. Amazon Redshift customers with an active Redshift cluster earn up to one hour of free Concurrency Scaling credits, which is sufficient for the concurrency needs of most customers. Concurrency scaling enables you to specify usage control, providing customers with predictable month-to-month costs, even during periods of fluctuating analytical demand.

To enable Amazon Redshift Concurrency Scaling, set the Concurrency Scaling Mode to Auto in your Amazon Web Services Management Console. You can allocate Concurrency Scaling usage to specific user groups and workloads, control the number of Concurrency Scaling clusters that can be used, and monitor Amazon CloudWatch performance and usage metrics.

To learn more about concurrency scaling including regional-availability, see our documentation and pricing page.

 

​Amazon Redshift Concurrency Scaling is now available in the AWS Africa (Cape Town), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Osaka), Asia Pacific (Thailand), Europe (Milan), Middle East (Bahrain), Mexico (Central) and AWS GovCloud (US-West) regions. With the Amazon Redshift Concurrency Scaling feature, you can now support thousands of concurrent users and concurrent queries, with consistently fast query performance. Amazon Redshift Concurrency Scaling elastically scales query processing power to provide consistently fast performance for hundreds of concurrent queries. Concurrency Scaling resources are added to your Redshift cluster transparently in seconds, allowing for increased concurrency to process queries with minimal wait time. Amazon Redshift customers with an active Redshift cluster earn up to one hour of free Concurrency Scaling credits, which is sufficient for the concurrency needs of most customers. Concurrency scaling enables you to specify usage control, providing customers with predictable month-to-month costs, even during periods of fluctuating analytical demand. To enable Amazon Redshift Concurrency Scaling, set the Concurrency Scaling Mode to Auto in your Amazon Web Services Management Console. You can allocate Concurrency Scaling usage to specific user groups and workloads, control the number of Concurrency Scaling clusters that can be used, and monitor Amazon CloudWatch performance and usage metrics. To learn more about concurrency scaling including regional-availability, see our documentation and pricing page.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8gn instances, powered by the latest-generation AWS Graviton4 processors, are available in the AWS Region Europe (Frankfurt, Stockholm), Asia Pacific (Singapore). The new instances provide up to 30% better compute performance than Graviton3-based Amazon EC2 C7gn instances. Amazon EC2 C8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network optimized EC2 instances.

Take advantage of the enhanced networking capabilities of C8gn to scale performance and throughput, while optimizing the cost of running network-intensive workloads such as network virtual appliances, data analytics, CPU-based artificial intelligence and machine learning (AI/ML) inference.

For increased scalability, C8gn instances offer instance sizes up to 48xlarge, up to 384 GiB of memory, and up to 60 Gbps of bandwidth to Amazon Elastic Block Store (EBS). C8gn instances support Elastic Fabric Adapter (EFA) networking on the 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes, which enables lower latency and improved cluster performance for workloads deployed on tightly coupled clusters.

C8gn instances are available in the following AWS Regions: US East (N. Virginia), US West (Oregon, N.California), Europe (Frankfurt, Stockholm), Asia Pacific (Singapore)

To learn more, see Amazon C8gn Instances. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8gn instances, powered by the latest-generation AWS Graviton4 processors, are available in the AWS Region Europe (Frankfurt, Stockholm), Asia Pacific (Singapore). The new instances provide up to 30% better compute performance than Graviton3-based Amazon EC2 C7gn instances. Amazon EC2 C8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network optimized EC2 instances. Take advantage of the enhanced networking capabilities of C8gn to scale performance and throughput, while optimizing the cost of running network-intensive workloads such as network virtual appliances, data analytics, CPU-based artificial intelligence and machine learning (AI/ML) inference. For increased scalability, C8gn instances offer instance sizes up to 48xlarge, up to 384 GiB of memory, and up to 60 Gbps of bandwidth to Amazon Elastic Block Store (EBS). C8gn instances support Elastic Fabric Adapter (EFA) networking on the 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes, which enables lower latency and improved cluster performance for workloads deployed on tightly coupled clusters. C8gn instances are available in the following AWS Regions: US East (N. Virginia), US West (Oregon, N.California), Europe (Frankfurt, Stockholm), Asia Pacific (Singapore) To learn more, see Amazon C8gn Instances. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.  

AWS Network Firewall, a managed service that makes it easy to deploy essential network protections for your Amazon VPCs, now provides enhanced default rules to handle TLS client hellos, and HTTP requests split across multiple packets. This update introduces new application layer drop and alert established default stateful actions, enabling customers to maintain security controls while supporting modern TLS implementations and large HTTP requests.

These enhancements help customers implement robust security policies without writing complex custom rules. Security teams can now effectively inspect and filter traffic where key information is segmented across multiple packets, while maintaining visibility through detailed logging options, making it easier to secure applications using modern protocols and encryption standards.

This capability is available in all AWS Regions where AWS Network Firewall is supported.

To learn more, refer to AWS Network Firewall service documentation.

 

​AWS Network Firewall, a managed service that makes it easy to deploy essential network protections for your Amazon VPCs, now provides enhanced default rules to handle TLS client hellos, and HTTP requests split across multiple packets. This update introduces new application layer drop and alert established default stateful actions, enabling customers to maintain security controls while supporting modern TLS implementations and large HTTP requests. These enhancements help customers implement robust security policies without writing complex custom rules. Security teams can now effectively inspect and filter traffic where key information is segmented across multiple packets, while maintaining visibility through detailed logging options, making it easier to secure applications using modern protocols and encryption standards. This capability is available in all AWS Regions where AWS Network Firewall is supported. To learn more, refer to AWS Network Firewall service documentation.  

Amazon RDS for PostgreSQL 18.0 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest PostgreSQL features while leveraging the benefits of a fully managed database service. This preview environment provides you a sandbox where you can test applications and explore new PostgreSQL 18.0 capabilities before they become generally available.

PostgreSQL 18.0 includes «skip scan» support for multicolumn B-tree indexes and improves WHERE clause handling for OR and IN conditions. It introduces parallel Generalized Inverted Index (GIN) builds and updates join operations. It now supports Universally Unique Identifiers Version 7 (UUIDv7), which combines timestamp-based ordering with traditional UUID uniqueness to boost performance in high-throughput distributed systems. Observability improvements show buffer usage counts and index lookups during query execution, along with per-connection I/O utilization metric. Please refer to the RDS PostgreSQL release documentation for more details.

Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment.

Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.

 

​Amazon RDS for PostgreSQL 18.0 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest PostgreSQL features while leveraging the benefits of a fully managed database service. This preview environment provides you a sandbox where you can test applications and explore new PostgreSQL 18.0 capabilities before they become generally available.
PostgreSQL 18.0 includes «skip scan» support for multicolumn B-tree indexes and improves WHERE clause handling for OR and IN conditions. It introduces parallel Generalized Inverted Index (GIN) builds and updates join operations. It now supports Universally Unique Identifiers Version 7 (UUIDv7), which combines timestamp-based ordering with traditional UUID uniqueness to boost performance in high-throughput distributed systems. Observability improvements show buffer usage counts and index lookups during query execution, along with per-connection I/O utilization metric. Please refer to the RDS PostgreSQL release documentation for more details.
Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment.
Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.  

Allowed AMIs, the Amazon EC2 account-wide setting that enables you to limit the discovery and use of Amazon Machine Images (AMIs) within your Amazon Web Services accounts, adds support for four new parameters — marketplace codes, deprecation time, creation date and AMI names.

Previously, you could specify accounts or owner aliases that you trust in your Allowed AMIs setting. Starting today, you can use the four new parameters to define additional criteria to further reduce risk of inadvertently launching instances with non-compliant or unauthorized AMIs. Marketplace codes can be provided to limit the use of Marketplace AMIs, the deprecation time and creation date parameters can be used to limit the use of outdated AMIs, and AMI name parameter can be used to restrict usage to AMIs with specific naming pattern. You can also leverage Declarative Policies to configure these parameters to perform AMI governance across your organization.

These additional parameters are now supported in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US). To learn more, please visit the documentation.

 

​Allowed AMIs, the Amazon EC2 account-wide setting that enables you to limit the discovery and use of Amazon Machine Images (AMIs) within your Amazon Web Services accounts, adds support for four new parameters — marketplace codes, deprecation time, creation date and AMI names. Previously, you could specify accounts or owner aliases that you trust in your Allowed AMIs setting. Starting today, you can use the four new parameters to define additional criteria to further reduce risk of inadvertently launching instances with non-compliant or unauthorized AMIs. Marketplace codes can be provided to limit the use of Marketplace AMIs, the deprecation time and creation date parameters can be used to limit the use of outdated AMIs, and AMI name parameter can be used to restrict usage to AMIs with specific naming pattern. You can also leverage Declarative Policies to configure these parameters to perform AMI governance across your organization. These additional parameters are now supported in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US). To learn more, please visit the documentation.  

Amazon Bedrock AgentCore Runtime, Browser, and Code Interpreter services now support Amazon Virtual Private Cloud (VPC) connectivity, AWS PrivateLink, AWS CloudFormation, and resource tagging, enabling developers to deploy AI agents with enhanced enterprise security and infrastructure automation capabilities. AgentCore Runtime enables you to deploy and scale dynamic AI agents securely using any framework, protocol, or model. AgentCore Browser enables web-based interactions such as form filling, data extraction, and QA testing, while AgentCore Code Interpreter provides secure execution of agent-generated code.

With VPC support, you can now securely connect AgentCore Runtime, Browser, and Code Interpreter services to private resources such as databases, internal APIs, and services within your VPC without internet exposure. AWS PrivateLink provides private connectivity between your VPC and Amazon Bedrock AgentCore services, while CloudFormation support enables automated resource provisioning through infrastructure as code. Resource tagging allows you to implement comprehensive cost allocation, access control, and resource organization across your AgentCore deployments.

Amazon Bedrock AgentCore is currently in preview and available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Frankfurt).

To learn more, see Configuring VPC for AgentCore and Use Interface VPC endpoints (AWS PrivateLink) with AgentCore. For CloudFormation resources, visit the AgentCore CloudFormation Reference, and to get started with tagging, see the Tagging AgentCore resources.

 

​Amazon Bedrock AgentCore Runtime, Browser, and Code Interpreter services now support Amazon Virtual Private Cloud (VPC) connectivity, AWS PrivateLink, AWS CloudFormation, and resource tagging, enabling developers to deploy AI agents with enhanced enterprise security and infrastructure automation capabilities. AgentCore Runtime enables you to deploy and scale dynamic AI agents securely using any framework, protocol, or model. AgentCore Browser enables web-based interactions such as form filling, data extraction, and QA testing, while AgentCore Code Interpreter provides secure execution of agent-generated code. With VPC support, you can now securely connect AgentCore Runtime, Browser, and Code Interpreter services to private resources such as databases, internal APIs, and services within your VPC without internet exposure. AWS PrivateLink provides private connectivity between your VPC and Amazon Bedrock AgentCore services, while CloudFormation support enables automated resource provisioning through infrastructure as code. Resource tagging allows you to implement comprehensive cost allocation, access control, and resource organization across your AgentCore deployments. Amazon Bedrock AgentCore is currently in preview and available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Frankfurt). To learn more, see Configuring VPC for AgentCore and Use Interface VPC endpoints (AWS PrivateLink) with AgentCore. For CloudFormation resources, visit the AgentCore CloudFormation Reference, and to get started with tagging, see the Tagging AgentCore resources.