Amazon OpenSearch Serverless now supports detailed audit logging of data plane requests via AWS CloudTrail. This feature enables customers to record user actions on their collections, helping meet compliance regulations, improve security posture, and provide evidence for security investigations. Customers can now track user activities such as authorization attempts, index modifications, and search queries.

Customers can use CloudTrail to configure filters for OpenSearch Serverless collections with read-only and write-only options, or use advanced event selectors for more granular control over logged data events. All OpenSearch Serverless data events are delivered to an Amazon S3 bucket and optionally to Amazon CloudWatch Events, creating a comprehensive audit trail. This enhanced visibility into when and who made API calls helps security and operations teams monitor data access and respond to events in real-time.

Once configured with CloudTrail, audit logs will be continuously streamed with no additional customer action required. Audit Logs will be continuously streamed to CloudTrail and can be further analyzed there.

Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation. 

 

​Amazon OpenSearch Serverless now supports detailed audit logging of data plane requests via AWS CloudTrail. This feature enables customers to record user actions on their collections, helping meet compliance regulations, improve security posture, and provide evidence for security investigations. Customers can now track user activities such as authorization attempts, index modifications, and search queries. Customers can use CloudTrail to configure filters for OpenSearch Serverless collections with read-only and write-only options, or use advanced event selectors for more granular control over logged data events. All OpenSearch Serverless data events are delivered to an Amazon S3 bucket and optionally to Amazon CloudWatch Events, creating a comprehensive audit trail. This enhanced visibility into when and who made API calls helps security and operations teams monitor data access and respond to events in real-time. Once configured with CloudTrail, audit logs will be continuously streamed with no additional customer action required. Audit Logs will be continuously streamed to CloudTrail and can be further analyzed there. Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation.   

Today, EC2 Auto Scaling is launching a new API, LaunchInstances, which gives customers more control and flexibility over how EC2 Auto Scaling provisions instances while providing instant feedback on capacity availability.

Customers use EC2 Auto Scaling for automated fleet management. With scaling policies, EC2 Auto Scaling can automatically add instances when demand spikes and remove them when traffic drops, ensuring customers’ applications always have the right amount of compute. EC2 Auto Scaling also offers the ability to monitor and replace unhealthy instances. In certain use cases, customers may want to specify exactly where EC2 Auto Scaling should launch additional instances and need immediate feedback on capacity availability. The new LaunchInstances API allows customers to precisely control where instances are launched by specifying an override for any Availability Zone and/or subnet in an Auto Scaling group, while providing immediate feedback on capacity availability. This synchronous operation gives customers real-time insight into scaling operations, enabling them to quickly implement alternative strategies if needed. For additional flexibility, the API includes optional asynchronous retries to help reach the desired capacity.

This feature is now available in US East (N. Virginia), US West (Oregon), Europe (Ireland), and Asia Pacific (Singapore), at no additional cost beyond standard EC2 and EBS usage. To get started, visit the AWS Command Line Interface (CLI) and the AWS SDKs. To learn more about this feature, visit the AWS documentation. 

 

​Today, EC2 Auto Scaling is launching a new API, LaunchInstances, which gives customers more control and flexibility over how EC2 Auto Scaling provisions instances while providing instant feedback on capacity availability. Customers use EC2 Auto Scaling for automated fleet management. With scaling policies, EC2 Auto Scaling can automatically add instances when demand spikes and remove them when traffic drops, ensuring customers’ applications always have the right amount of compute. EC2 Auto Scaling also offers the ability to monitor and replace unhealthy instances. In certain use cases, customers may want to specify exactly where EC2 Auto Scaling should launch additional instances and need immediate feedback on capacity availability. The new LaunchInstances API allows customers to precisely control where instances are launched by specifying an override for any Availability Zone and/or subnet in an Auto Scaling group, while providing immediate feedback on capacity availability. This synchronous operation gives customers real-time insight into scaling operations, enabling them to quickly implement alternative strategies if needed. For additional flexibility, the API includes optional asynchronous retries to help reach the desired capacity. This feature is now available in US East (N. Virginia), US West (Oregon), Europe (Ireland), and Asia Pacific (Singapore), at no additional cost beyond standard EC2 and EBS usage. To get started, visit the AWS Command Line Interface (CLI) and the AWS SDKs. To learn more about this feature, visit the AWS documentation.   

Amazon Relational Database Service (RDS) now supports R8gd and M8gd database instances for Optimized Reads on Amazon Aurora PostgreSQL and RDS for PostgreSQL, MySQL, and MariaDB. R8gd and M8gd database instances offer improved price-performance. For example, Optimized Reads on R8gd instances deliver up to 165% better throughput and up to 120% better price-performance over R6g instances for Aurora PostgreSQL.

Optimized Reads uses local NVMe-based SSD block storage available on these instances to store ephemeral data, such as temporary tables, reducing data access to/from network-based storage and improving read latency and throughput. The result is improved query performance for complex queries and faster index rebuild operations. Aurora PostgreSQL Optimized Reads instances using the I/O-Optimized configuration additionally use the local storage to extend their caching capacity. Database pages that are evicted from the in-memory buffer cache are cached in local storage to speed subsequent retrieval of that data.

Customers can get started with Optimized Reads through the AWS Management Console, CLI, and SDK by modifying their existing Aurora and RDS databases or creating a new database using R8gd or M8gd instances. These instances are available in the US East (N. Virginia, Ohio), US West (Oregon), Europe (Spain, Frankfurt), and Asia Pacific (Tokyo) Regions. For complete information on pricing and regional availability, please refer to the pricing page. For information on specific engine versions that support these DB instance types, please see the Aurora and RDS documentation.

 

​Amazon Relational Database Service (RDS) now supports R8gd and M8gd database instances for Optimized Reads on Amazon Aurora PostgreSQL and RDS for PostgreSQL, MySQL, and MariaDB. R8gd and M8gd database instances offer improved price-performance. For example, Optimized Reads on R8gd instances deliver up to 165% better throughput and up to 120% better price-performance over R6g instances for Aurora PostgreSQL. Optimized Reads uses local NVMe-based SSD block storage available on these instances to store ephemeral data, such as temporary tables, reducing data access to/from network-based storage and improving read latency and throughput. The result is improved query performance for complex queries and faster index rebuild operations. Aurora PostgreSQL Optimized Reads instances using the I/O-Optimized configuration additionally use the local storage to extend their caching capacity. Database pages that are evicted from the in-memory buffer cache are cached in local storage to speed subsequent retrieval of that data. Customers can get started with Optimized Reads through the AWS Management Console, CLI, and SDK by modifying their existing Aurora and RDS databases or creating a new database using R8gd or M8gd instances. These instances are available in the US East (N. Virginia, Ohio), US West (Oregon), Europe (Spain, Frankfurt), and Asia Pacific (Tokyo) Regions. For complete information on pricing and regional availability, please refer to the pricing page. For information on specific engine versions that support these DB instance types, please see the Aurora and RDS documentation.  

AWS Builder Center now provides access to the catalog of AWS Workshops, offering step-by-step instructions crafted by AWS experts that explain how to deploy and use AWS services effectively. These workshops cover a wide range of AWS services and use cases, allowing builders to follow guided tutorials within their own AWS accounts. Workshops are designed for builders of all skill levels to gain practical experience and develop solutions tailored to their specific business needs using AWS services.

The AWS Workshops Catalog features hundreds of workshops with advanced filtering capabilities to quickly find relevant content by category (Machine Learning, Security, Serverless), AWS service (EC2, Lambda, S3), and complexity level (100-Beginner through 400-Expert). Real-time search with partial matching across workshop titles, descriptions, services, and categories helps surface the most relevant content. Catalog content automatically localized based on your Builder Center language preference.

Builders can navigate to the Workshops catalog at builder.aws.com/build/workshops and filter by specific needs—whether you have 1 hour or 8 hours, are a beginner or expert, or want to focus on specific services like Amazon Bedrock and SageMaker. Seamless navigation from Builder Center discovery to the full workshops experience enables hands-on, step-by-step guided learning in your own AWS account.

You can begin exploring Workshops in AWS Builder Center immediately with a free Builder ID. To get started with Workshops, visit AWS Builder Center.

 

​AWS Builder Center now provides access to the catalog of AWS Workshops, offering step-by-step instructions crafted by AWS experts that explain how to deploy and use AWS services effectively. These workshops cover a wide range of AWS services and use cases, allowing builders to follow guided tutorials within their own AWS accounts. Workshops are designed for builders of all skill levels to gain practical experience and develop solutions tailored to their specific business needs using AWS services.
The AWS Workshops Catalog features hundreds of workshops with advanced filtering capabilities to quickly find relevant content by category (Machine Learning, Security, Serverless), AWS service (EC2, Lambda, S3), and complexity level (100-Beginner through 400-Expert). Real-time search with partial matching across workshop titles, descriptions, services, and categories helps surface the most relevant content. Catalog content automatically localized based on your Builder Center language preference.
Builders can navigate to the Workshops catalog at builder.aws.com/build/workshops and filter by specific needs—whether you have 1 hour or 8 hours, are a beginner or expert, or want to focus on specific services like Amazon Bedrock and SageMaker. Seamless navigation from Builder Center discovery to the full workshops experience enables hands-on, step-by-step guided learning in your own AWS account.
You can begin exploring Workshops in AWS Builder Center immediately with a free Builder ID. To get started with Workshops, visit AWS Builder Center.  

Amazon Web Services (AWS) is launching flat-rate pricing plans with no overages for website delivery and security. The flat-rate plans, available with Amazon CloudFront, combine global content delivery with AWS WAF, DDoS protection, Amazon Route 53 DNS, Amazon CloudWatch Logs ingestion, and serverless edge compute into a simple monthly price with no overage charges. Each plan also includes monthly Amazon S3 storage credits to help offset your storage costs.

CloudFront flat-rate plans allow you to deliver your websites and applications without calculating costs across multiple AWS services. You won’t face the risk of overage charges, even if your website or application goes viral or faces a DDoS attack. Security features like WAF and DDoS protection are enabled by default, and additional configurations are simple to set up. When you serve your AWS applications through CloudFront instead of directly to the internet, your flat-rate plan covers the data transfer costs between your applications and your viewers for a simple monthly price without the worry of overages. This simplified pricing model is available alongside pay-as-you-go pricing for each CloudFront distribution, giving you the flexibility to choose the right pricing model and feature set for each application.

Plans are available in Free ($0/month), Pro ($15/month), Business ($200/month), and Premium ($1,000/month) tiers for new and existing CloudFront distributions. Select the plan tier with the features and usage allowances matching your application’s needs. To learn more, refer to the Launch Blog, Plans and Pricing, or CloudFront Developer Guide. To get started, visit the CloudFront console.

 

​Amazon Web Services (AWS) is launching flat-rate pricing plans with no overages for website delivery and security. The flat-rate plans, available with Amazon CloudFront, combine global content delivery with AWS WAF, DDoS protection, Amazon Route 53 DNS, Amazon CloudWatch Logs ingestion, and serverless edge compute into a simple monthly price with no overage charges. Each plan also includes monthly Amazon S3 storage credits to help offset your storage costs. CloudFront flat-rate plans allow you to deliver your websites and applications without calculating costs across multiple AWS services. You won’t face the risk of overage charges, even if your website or application goes viral or faces a DDoS attack. Security features like WAF and DDoS protection are enabled by default, and additional configurations are simple to set up. When you serve your AWS applications through CloudFront instead of directly to the internet, your flat-rate plan covers the data transfer costs between your applications and your viewers for a simple monthly price without the worry of overages. This simplified pricing model is available alongside pay-as-you-go pricing for each CloudFront distribution, giving you the flexibility to choose the right pricing model and feature set for each application. Plans are available in Free ($0/month), Pro ($15/month), Business ($200/month), and Premium ($1,000/month) tiers for new and existing CloudFront distributions. Select the plan tier with the features and usage allowances matching your application’s needs. To learn more, refer to the Launch Blog, Plans and Pricing, or CloudFront Developer Guide. To get started, visit the CloudFront console.  

AWS Transfer Family Terraform module now supports deployment of automated malware scanning workflows for files transferred using Transfer Family resources. This release streamlines centralized provisioning of threat detection workflows using Amazon GuardDuty S3 Protection, helping you meet data security requirements by identifying potential threats in transferred files.

AWS Transfer Family provides fully managed file transfers over SFTP, AS2, FTPS, FTP, and web browser-
based interfaces for AWS storage services. Using the new module, you can programmatically provision workflows to scan incoming files, dynamically route files based on scan results, and generate threat notifications, in a single deployment. You can granularly implement threat detection for specific S3 prefixes while preserving folder structures post scanning, and ensure that only verified clean files reach your business applications and data lakes. This eliminates the overhead and risks associated with manual configurations, and provides a scalable deployment option for data security compliance.

Customers can get started by using the new module from the Terraform Registry. To learn more about Transfer Family, visit the product page and user guide. To see all the regions where Transfer Family is available, visit the AWS Region table.

 

​AWS Transfer Family Terraform module now supports deployment of automated malware scanning workflows for files transferred using Transfer Family resources. This release streamlines centralized provisioning of threat detection workflows using Amazon GuardDuty S3 Protection, helping you meet data security requirements by identifying potential threats in transferred files. AWS Transfer Family provides fully managed file transfers over SFTP, AS2, FTPS, FTP, and web browser- based interfaces for AWS storage services. Using the new module, you can programmatically provision workflows to scan incoming files, dynamically route files based on scan results, and generate threat notifications, in a single deployment. You can granularly implement threat detection for specific S3 prefixes while preserving folder structures post scanning, and ensure that only verified clean files reach your business applications and data lakes. This eliminates the overhead and risks associated with manual configurations, and provides a scalable deployment option for data security compliance. Customers can get started by using the new module from the Terraform Registry. To learn more about Transfer Family, visit the product page and user guide. To see all the regions where Transfer Family is available, visit the AWS Region table.  

Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in AWS Asia Pacific (Melbourne, Mumbai, Osaka), Middle East (UAE) regions. Powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, these instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances.

I7i instances are ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access small to medium size datasets (multi-TBs). I7i instances support torn write prevention feature with up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks.

I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth.
To learn more, visit the I7i instances page.

 

​Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in AWS Asia Pacific (Melbourne, Mumbai, Osaka), Middle East (UAE) regions. Powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, these instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances. I7i instances are ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access small to medium size datasets (multi-TBs). I7i instances support torn write prevention feature with up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks. I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.  

Amazon Web Services (AWS) is announcing starting today, Amazon EC2 I7ie instances are now available in Asia Pacific (Singapore) region. Designed for large storage I/O intensive workloads, I7ie instances are powered by 5th Gen Intel Xeon Processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over existing I3en instances. I7ie instances offer up to 120TB local NVMe storage density for storage optimized instances and offer up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, I7ie instances deliver up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances.

I7ie are high density storage optimized instances, ideal for workloads requiring fast local storage with high random read/write performance at very low latency consistency to access large data sets. These instances are available in 9 different virtual sizes and deliver up to 100Gbps of network bandwidth and 60Gbps of bandwidth for Amazon Elastic Block Store (EBS).

To learn more, visit the I7ie instances page.

 

​Amazon Web Services (AWS) is announcing starting today, Amazon EC2 I7ie instances are now available in Asia Pacific (Singapore) region. Designed for large storage I/O intensive workloads, I7ie instances are powered by 5th Gen Intel Xeon Processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over existing I3en instances. I7ie instances offer up to 120TB local NVMe storage density for storage optimized instances and offer up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, I7ie instances deliver up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances. I7ie are high density storage optimized instances, ideal for workloads requiring fast local storage with high random read/write performance at very low latency consistency to access large data sets. These instances are available in 9 different virtual sizes and deliver up to 100Gbps of network bandwidth and 60Gbps of bandwidth for Amazon Elastic Block Store (EBS). To learn more, visit the I7ie instances page.  

Amazon Redshift announces support for the SUPER data type in databases with case insensitive collation, enabling analytics on semi-structured and nested data in these databases. Using the SUPER data type with PartiQL in Amazon Redshift, you can perform advanced analytics that combine structured SQL data (such as string, numeric, and timestamp) with the semi-structured SUPER data (such as JSON) with flexibility and ease-of-use.

This enhancement allows you to leverage the SUPER data type for your structured and semi-structured data processing needs in databases with case-insensitive collation. Using the COLLATE function, you can now explicitly specify case sensitivity preferences for SUPER columns, providing greater flexibility in handling data with varying case patterns. This is particularly valuable when working with JSON documents, APIs, or application data where case consistency isn’t guaranteed. Whether you’re processing user-defined identifiers or integrating data from multiple sources, you can now perform complex queries across both case-sensitive and case-insensitive data without additional normalization overhead.

Amazon Redshift support for the SUPER data type in databases with case insensitive collation is available in all AWS Regions, including the AWS GovCloud (US) Regions, where Amazon Redshift is available. See AWS Region Table for more details. To learn more about the SUPER data type in databases with case insensitive collation, please visit our documentation.

 

​Amazon Redshift announces support for the SUPER data type in databases with case insensitive collation, enabling analytics on semi-structured and nested data in these databases. Using the SUPER data type with PartiQL in Amazon Redshift, you can perform advanced analytics that combine structured SQL data (such as string, numeric, and timestamp) with the semi-structured SUPER data (such as JSON) with flexibility and ease-of-use. This enhancement allows you to leverage the SUPER data type for your structured and semi-structured data processing needs in databases with case-insensitive collation. Using the COLLATE function, you can now explicitly specify case sensitivity preferences for SUPER columns, providing greater flexibility in handling data with varying case patterns. This is particularly valuable when working with JSON documents, APIs, or application data where case consistency isn’t guaranteed. Whether you’re processing user-defined identifiers or integrating data from multiple sources, you can now perform complex queries across both case-sensitive and case-insensitive data without additional normalization overhead. Amazon Redshift support for the SUPER data type in databases with case insensitive collation is available in all AWS Regions, including the AWS GovCloud (US) Regions, where Amazon Redshift is available. See AWS Region Table for more details. To learn more about the SUPER data type in databases with case insensitive collation, please visit our documentation.  

You can now use Amazon MSK Replicator to replicate streaming data across Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in Asia Pacific (Hyderabad) and Asia Pacific (Malaysia) Regions.

MSK Replicator is a feature of Amazon MSK that enables you to reliably replicate data across Amazon MSK clusters in different or the same AWS Region(s) in a few clicks. With MSK Replicator, you can easily build regionally resilient streaming applications for increased availability and business continuity. MSK Replicator provides automatic asynchronous replication across MSK clusters, eliminating the need to write custom code, manage infrastructure, or setup cross-region networking. MSK Replicator automatically scales the underlying resources so that you can replicate data on-demand without having to monitor or scale capacity. MSK Replicator also replicates the necessary Kafka metadata including topic configurations, Access Control Lists (ACLs), and consumer group offsets. If an unexpected event occurs in a region, you can failover to the other AWS Region and seamlessly resume processing.

With this launch, MSK Replicator is now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), South America (Sao Paulo), China (Beijing), China (Ningxia), Asia Pacific (Hyderabad), and Asia Pacific (Malaysia). You can get started with MSK Replicator from the Amazon MSK console or the Amazon CLI. To learn more, visit the MSK Replicator product page, pricing page, and documentation.

 

​You can now use Amazon MSK Replicator to replicate streaming data across Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in Asia Pacific (Hyderabad) and Asia Pacific (Malaysia) Regions. MSK Replicator is a feature of Amazon MSK that enables you to reliably replicate data across Amazon MSK clusters in different or the same AWS Region(s) in a few clicks. With MSK Replicator, you can easily build regionally resilient streaming applications for increased availability and business continuity. MSK Replicator provides automatic asynchronous replication across MSK clusters, eliminating the need to write custom code, manage infrastructure, or setup cross-region networking. MSK Replicator automatically scales the underlying resources so that you can replicate data on-demand without having to monitor or scale capacity. MSK Replicator also replicates the necessary Kafka metadata including topic configurations, Access Control Lists (ACLs), and consumer group offsets. If an unexpected event occurs in a region, you can failover to the other AWS Region and seamlessly resume processing. With this launch, MSK Replicator is now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), South America (Sao Paulo), China (Beijing), China (Ningxia), Asia Pacific (Hyderabad), and Asia Pacific (Malaysia). You can get started with MSK Replicator from the Amazon MSK console or the Amazon CLI. To learn more, visit the MSK Replicator product page, pricing page, and documentation.