Amazon S3 Storage Lens provides organization-wide visibility into your storage usage and activity to help optimize costs, improve performance, and strengthen data protection. Today, we are adding three new capabilities to S3 Storage Lens that give you deeper insights into your S3 storage usage and application performance: performance metrics that provide insights into how your applications interact with S3 data, analytics for billions of prefixes in your buckets, and metrics export directly to S3 Tables for easier querying and analysis.

We are adding three specific types of performance metrics. Access pattern metrics identify inefficient requests, including those that are too small and create unnecessary network overhead. Request origin metrics, such as cross-Region request counts, show when applications access data across regions, impacting latency and costs. Object access count metrics reveal when applications frequently read a small subset of objects that could be optimized through caching or moving to high-performance storage.

We are expanding the prefix analytics in S3 Storage Lens to enable analyzing billions of prefixes per bucket, whereas previously metrics were limited to the largest prefixes that met minimum size and depth thresholds. This gives you visibility into storage usage and activity across all your prefixes. Finally, we are making it possible to export metrics directly to managed S3 Tables, making them immediately available for querying with AWS analytics services like Amazon QuickSight and enabling you to join this data with other AWS service data for deeper insights.

To get started, enable performance metrics or expanded prefixes in your S3 Storage Lens advanced metrics dashboard configuration. These capabilities are available in all AWS Regions, except for AWS China Regions and AWS GovCloud (US) Regions. You can enable metrics export to managed S3 Tables in both free and advanced dashboard configurations in AWS Regions where S3 Tables are available. To learn more, visit the S3 Storage Lens overview page, documentation, S3 pricing page, and read the AWS News Blog.

 

​Amazon S3 Storage Lens provides organization-wide visibility into your storage usage and activity to help optimize costs, improve performance, and strengthen data protection. Today, we are adding three new capabilities to S3 Storage Lens that give you deeper insights into your S3 storage usage and application performance: performance metrics that provide insights into how your applications interact with S3 data, analytics for billions of prefixes in your buckets, and metrics export directly to S3 Tables for easier querying and analysis. We are adding three specific types of performance metrics. Access pattern metrics identify inefficient requests, including those that are too small and create unnecessary network overhead. Request origin metrics, such as cross-Region request counts, show when applications access data across regions, impacting latency and costs. Object access count metrics reveal when applications frequently read a small subset of objects that could be optimized through caching or moving to high-performance storage. We are expanding the prefix analytics in S3 Storage Lens to enable analyzing billions of prefixes per bucket, whereas previously metrics were limited to the largest prefixes that met minimum size and depth thresholds. This gives you visibility into storage usage and activity across all your prefixes. Finally, we are making it possible to export metrics directly to managed S3 Tables, making them immediately available for querying with AWS analytics services like Amazon QuickSight and enabling you to join this data with other AWS service data for deeper insights. To get started, enable performance metrics or expanded prefixes in your S3 Storage Lens advanced metrics dashboard configuration. These capabilities are available in all AWS Regions, except for AWS China Regions and AWS GovCloud (US) Regions. You can enable metrics export to managed S3 Tables in both free and advanced dashboard configurations in AWS Regions where S3 Tables are available. To learn more, visit the S3 Storage Lens overview page, documentation, S3 pricing page, and read the AWS News Blog.  

Amazon Web Services is announcing the preview of Amazon EC2 X8i, next-generation Memory optimized instances. X8i instances are powered by custom Intel Xeon 6 processors delivering the highest performance and fastest memory among comparable Intel processors in the cloud. X8i instances offer 1.5x more memory capacity (up to 6TB) , and up to 3.4x more memory bandwidth compared to previous generation X2i instances.

X8i instances will be SAP-certified and deliver 46% higher SAPS compared to X2i instances, for mission-critical SAP workloads. X8i instances are a great choice for memory-intensive workloads, including in-memory databases and analytics, large-scale traditional databases, and Electronic Design Automation (EDA). X8i instances offer 35% higher performance than X2i instances with even higher gains for some workloads.

To learn more or request access to the X8i instances preview, visit the Amazon EC2 X8i page.

 

​Amazon Web Services is announcing the preview of Amazon EC2 X8i, next-generation Memory optimized instances. X8i instances are powered by custom Intel Xeon 6 processors delivering the highest performance and fastest memory among comparable Intel processors in the cloud. X8i instances offer 1.5x more memory capacity (up to 6TB) , and up to 3.4x more memory bandwidth compared to previous generation X2i instances. X8i instances will be SAP-certified and deliver 46% higher SAPS compared to X2i instances, for mission-critical SAP workloads. X8i instances are a great choice for memory-intensive workloads, including in-memory databases and analytics, large-scale traditional databases, and Electronic Design Automation (EDA). X8i instances offer 35% higher performance than X2i instances with even higher gains for some workloads. To learn more or request access to the X8i instances preview, visit the Amazon EC2 X8i page.  

AWS announces further enhancements to Amazon GuardDuty Extended Threat Detection with new capabilities to detect multistage attacks targeting Amazon Elastic Compute Cloud (Amazon EC2) instances and Amazon Elastic Container Service (Amazon ECS) clusters running on AWS Fargate or Amazon EC2. GuardDuty Extended Threat Detection uses artificial intelligence and machine learning algorithms trained at AWS scale to automatically correlate security signals and detect critical threats. It analyzes multiple security signals across network activity, process runtime behavior, malware execution, and AWS API activity over extended periods to detect sophisticated attack patterns that might otherwise go unnoticed.

With this launch, GuardDuty introduces two new critical-severity findings: AttackSequence:EC2/CompromisedInstanceGroup and AttackSequence:ECS/CompromisedCluster. These findings provide attack sequence information, allowing you to spend less time on initial analysis and more time responding to critical threats, minimizing business impact. For example, GuardDuty can identify suspicious processes followed by persistence attempts, crypto-mining activities, and reverse shell creation, representing these related events as a single, critical-severity finding. Each finding includes a detailed summary, events timeline, mapping to MITRE ATT&CK® tactics and techniques, and remediation recommendations.

While GuardDuty Extended Threat Detection is automatically enabled for GuardDuty customers at no additional cost, its detection comprehensiveness depends on your enabled GuardDuty protection plans. To improve attack sequence coverage and threat analysis of Amazon EC2 instances, enable Runtime Monitoring for EC2. To enable detection of compromised ECS clusters, enable Runtime Monitoring for Fargate or EC2 depending on your infrastructure type.

To get started, enable GuardDuty protection plans via the Console or API. New GuardDuty customers can start with a 30-day free trial, and existing customers who haven’t used Runtime Monitoring can also try it free for 30 days. For additional information, visit the blog post and Amazon Guard Duty product page.

 

​AWS announces further enhancements to Amazon GuardDuty Extended Threat Detection with new capabilities to detect multistage attacks targeting Amazon Elastic Compute Cloud (Amazon EC2) instances and Amazon Elastic Container Service (Amazon ECS) clusters running on AWS Fargate or Amazon EC2. GuardDuty Extended Threat Detection uses artificial intelligence and machine learning algorithms trained at AWS scale to automatically correlate security signals and detect critical threats. It analyzes multiple security signals across network activity, process runtime behavior, malware execution, and AWS API activity over extended periods to detect sophisticated attack patterns that might otherwise go unnoticed. With this launch, GuardDuty introduces two new critical-severity findings: AttackSequence:EC2/CompromisedInstanceGroup and AttackSequence:ECS/CompromisedCluster. These findings provide attack sequence information, allowing you to spend less time on initial analysis and more time responding to critical threats, minimizing business impact. For example, GuardDuty can identify suspicious processes followed by persistence attempts, crypto-mining activities, and reverse shell creation, representing these related events as a single, critical-severity finding. Each finding includes a detailed summary, events timeline, mapping to MITRE ATT&CK® tactics and techniques, and remediation recommendations. While GuardDuty Extended Threat Detection is automatically enabled for GuardDuty customers at no additional cost, its detection comprehensiveness depends on your enabled GuardDuty protection plans. To improve attack sequence coverage and threat analysis of Amazon EC2 instances, enable Runtime Monitoring for EC2. To enable detection of compromised ECS clusters, enable Runtime Monitoring for Fargate or EC2 depending on your infrastructure type. To get started, enable GuardDuty protection plans via the Console or API. New GuardDuty customers can start with a 30-day free trial, and existing customers who haven’t used Runtime Monitoring can also try it free for 30 days. For additional information, visit the blog post and Amazon Guard Duty product page.  

Today, AWS announces Database Savings Plans, a new flexible pricing model that helps you save up to 35% in exchange for a commitment to a consistent amount of usage (measured in $/hour) over a one-year term with no upfront payment.

Database Savings Plans automatically apply to eligible serverless and provisioned instance usage regardless of supported engine, instance family, size, deployment option, or AWS Region. For example, with Database Savings Plans, you can change between Aurora db.r7g and db.r8g instances, shift a workload from EU (Ireland) to US (Ohio), modernize from Amazon RDS for Oracle to Amazon Aurora PostgreSQL or from RDS to Amazon DynamoDB and still benefit from discounted pricing offered by Database Savings Plans.

Database Savings Plans will be available starting today in all AWS Regions, except China Regions, with support for Amazon Aurora, Amazon RDS, Amazon DynamoDB, Amazon ElastiCache, Amazon DocumentDB (with MongoDB compatibility), Amazon Neptune, Amazon Keyspaces (for Apache Cassandra), Amazon Timestream, and AWS Database Migration Service (DMS).

You can get started with Database Savings Plans from the AWS Billing and Cost Management Console or by using the AWS CLI. To realize the largest savings, you can make a commitment to Savings Plans by using purchase recommendations provided in the console. For a more customized analysis, you can use the Savings Plans Purchase Analyzer to estimate potential cost savings for custom purchase scenarios. For more information, visit the Database Savings Plans pricing page and the AWS Savings Plans FAQs.

 

​Today, AWS announces Database Savings Plans, a new flexible pricing model that helps you save up to 35% in exchange for a commitment to a consistent amount of usage (measured in $/hour) over a one-year term with no upfront payment. Database Savings Plans automatically apply to eligible serverless and provisioned instance usage regardless of supported engine, instance family, size, deployment option, or AWS Region. For example, with Database Savings Plans, you can change between Aurora db.r7g and db.r8g instances, shift a workload from EU (Ireland) to US (Ohio), modernize from Amazon RDS for Oracle to Amazon Aurora PostgreSQL or from RDS to Amazon DynamoDB and still benefit from discounted pricing offered by Database Savings Plans. Database Savings Plans will be available starting today in all AWS Regions, except China Regions, with support for Amazon Aurora, Amazon RDS, Amazon DynamoDB, Amazon ElastiCache, Amazon DocumentDB (with MongoDB compatibility), Amazon Neptune, Amazon Keyspaces (for Apache Cassandra), Amazon Timestream, and AWS Database Migration Service (DMS). You can get started with Database Savings Plans from the AWS Billing and Cost Management Console or by using the AWS CLI. To realize the largest savings, you can make a commitment to Savings Plans by using purchase recommendations provided in the console. For a more customized analysis, you can use the Savings Plans Purchase Analyzer to estimate potential cost savings for custom purchase scenarios. For more information, visit the Database Savings Plans pricing page and the AWS Savings Plans FAQs.  

AWS launches the preview of Amazon EC2 C8ine instances, powered by custom sixth-generation Intel Xeon Scalable processors (Granite Rapids) and the latest AWS Nitro v6 card. These instances are designed specifically for dataplane packet processing workloads.

Amazon EC2 C8ine instance configurations can deliver up to 2.5 times higher packet performance per vCPU versus prior generation C6in instances. They can offer up to 2x higher network bandwidth through internet gateways and up to 3x more Elastic Network Interface (ENI) compared to existing C6in network optimized instances. They are ideal for packet processing workloads requiring high performance at small packet sizes. These workloads include security virtual appliances, firewalls, load balancers, DDoS protection systems, and Telco 5G UPF applications.

These instances are available for preview upon request through your AWS account team. Connect with your account representatives to signup.

 

​AWS launches the preview of Amazon EC2 C8ine instances, powered by custom sixth-generation Intel Xeon Scalable processors (Granite Rapids) and the latest AWS Nitro v6 card. These instances are designed specifically for dataplane packet processing workloads. Amazon EC2 C8ine instance configurations can deliver up to 2.5 times higher packet performance per vCPU versus prior generation C6in instances. They can offer up to 2x higher network bandwidth through internet gateways and up to 3x more Elastic Network Interface (ENI) compared to existing C6in network optimized instances. They are ideal for packet processing workloads requiring high performance at small packet sizes. These workloads include security virtual appliances, firewalls, load balancers, DDoS protection systems, and Telco 5G UPF applications. These instances are available for preview upon request through your AWS account team. Connect with your account representatives to signup.  

AWS announces the general availability of Amazon Elastic Compute Cloud (Amazon EC2) Trn3 UltraServers powered by our fourth–generation AI chip Trainium3, our first 3nm AWS AI chip purpose-built to deliver the best token economics for next-generation agentic, reasoning, and video generation applications.

Each AWS Trainium3 chip provides 2.52 petaflops (PFLOPs) of FP8 compute, increases the memory capacity by 1.5x and bandwidth by 1.7x over Trainium2 to 144 GB of HBM3e memory, and 4.9 TB/s of memory bandwidth. Trainium3 is designed for both dense and expert-parallel workloads with advanced data types (MXFP8 and MXFP4) and improved memory-to-compute balance for real-time, multimodal, and reasoning tasks.

Trn3 UltraServers can scale up to 144 Trainium3 chips (362 FP8 PFLOPs total) and are available in EC2 UltraClusters 3.0 to scale to hundreds of thousands of chips. A fully configured Trn3 UltraServer delivers up to 20.7 TB of HBM3e and 706 TB/s of aggregate memory bandwidth. The next-generation Trn3 UltraServer, feature the NeuronSwitch-v1, an all-to-all fabric that doubles interchip interconnect bandwidth over Trn2 UltraServer.

Trn3 delivers up to 4.4x higher performance, 3.9x higher memory bandwidth and 4x better performance/watt compared to our Trn2 UltraServers, providing the best price-performance for training and serving frontier-scale models, including reinforcement learning, Mixture-of-Experts (MoE), reasoning, and long-context architectures. On Amazon Bedrock, Trainium3 is our fastest accelerator, delivering up to 3× faster performance than Trainium2 with over 5× higher output tokens per megawatt at similar latency per user.

New Trn3 UltraServers are built for AI researchers and powered by the AWS Neuron SDK, to unlock breakthrough performance. With native PyTorch integration, developers can train and deploy without changing a single line of model code. For AI performance engineers, we’ve enabled deeper access to Trainium3 so they can fine-tune performance, customize kernels, and push models even further. Because innovation thrives on openness, we are committed to engaging with our developers through open-source tools and resources.

 

​AWS announces the general availability of Amazon Elastic Compute Cloud (Amazon EC2) Trn3 UltraServers powered by our fourth–generation AI chip Trainium3, our first 3nm AWS AI chip purpose-built to deliver the best token economics for next-generation agentic, reasoning, and video generation applications. Each AWS Trainium3 chip provides 2.52 petaflops (PFLOPs) of FP8 compute, increases the memory capacity by 1.5x and bandwidth by 1.7x over Trainium2 to 144 GB of HBM3e memory, and 4.9 TB/s of memory bandwidth. Trainium3 is designed for both dense and expert-parallel workloads with advanced data types (MXFP8 and MXFP4) and improved memory-to-compute balance for real-time, multimodal, and reasoning tasks. Trn3 UltraServers can scale up to 144 Trainium3 chips (362 FP8 PFLOPs total) and are available in EC2 UltraClusters 3.0 to scale to hundreds of thousands of chips. A fully configured Trn3 UltraServer delivers up to 20.7 TB of HBM3e and 706 TB/s of aggregate memory bandwidth. The next-generation Trn3 UltraServer, feature the NeuronSwitch-v1, an all-to-all fabric that doubles interchip interconnect bandwidth over Trn2 UltraServer. Trn3 delivers up to 4.4x higher performance, 3.9x higher memory bandwidth and 4x better performance/watt compared to our Trn2 UltraServers, providing the best price-performance for training and serving frontier-scale models, including reinforcement learning, Mixture-of-Experts (MoE), reasoning, and long-context architectures. On Amazon Bedrock, Trainium3 is our fastest accelerator, delivering up to 3× faster performance than Trainium2 with over 5× higher output tokens per megawatt at similar latency per user. New Trn3 UltraServers are built for AI researchers and powered by the AWS Neuron SDK, to unlock breakthrough performance. With native PyTorch integration, developers can train and deploy without changing a single line of model code. For AI performance engineers, we’ve enabled deeper access to Trainium3 so they can fine-tune performance, customize kernels, and push models even further. Because innovation thrives on openness, we are committed to engaging with our developers through open-source tools and resources.  

Amazon S3 increased the maximum object size to 50 TB, a 10x increase from the previous 5 TB limit. This simplifies the processing of large objects such as high-resolution videos, seismic data files, AI training datasets and more. You can store 50 TB objects in all S3 storage classes and use them with all S3 features.

Optimize upload and download performance for your large objects by using the latest AWS Common Runtime (CRT) and S3 Transfer Manager in the AWS SDK. You can apply S3’s storage management capabilities to these objects. For example, use S3 Lifecycle to automatically archive infrequently accessed objects to S3 Glacier storage classes, or use S3 Replication to copy objects across AWS accounts or Regions.

Amazon S3 supports objects up to 50 TB in all AWS Regions. To learn more about working with large objects, visit the S3 User Guide. 

 

​Amazon S3 increased the maximum object size to 50 TB, a 10x increase from the previous 5 TB limit. This simplifies the processing of large objects such as high-resolution videos, seismic data files, AI training datasets and more. You can store 50 TB objects in all S3 storage classes and use them with all S3 features. Optimize upload and download performance for your large objects by using the latest AWS Common Runtime (CRT) and S3 Transfer Manager in the AWS SDK. You can apply S3’s storage management capabilities to these objects. For example, use S3 Lifecycle to automatically archive infrequently accessed objects to S3 Glacier storage classes, or use S3 Replication to copy objects across AWS accounts or Regions. Amazon S3 supports objects up to 50 TB in all AWS Regions. To learn more about working with large objects, visit the S3 User Guide.   

AWS announces Amazon EC2 X8aedz, next generation memory optimized instances, powered by 5th Gen AMD EPYC processors (formerly code named Turin). These instances offer the highest maximum CPU frequency, 5GHz in the cloud. They deliver up to 2x higher compute performance and 31% price-performance compared to previous generation X2iezn instances.

X8aedz instances are built using the latest sixth generation AWS Nitro Cards and are ideal for electronic design automation (EDA) workloads such as physical layout and physical verification jobs, and relational databases that benefit from high single-threaded processor performance and a large memory footprint. The combination of 5 GHz processors and local NVMe storage enables faster processing of memory-intensive backend EDA workloads such as floor planning, logic placement, clock tree synthesis (CTS), routing, and power/signal integrity analysis.

X8aedz instances feature a 32:1 ratio of memory to vCPU and are available in 8 sizes ranging from 2 to 96 vCPUs with 64 to 3,072 GiB of memory, including two bare metal variants, and up to 8 TB of local NVMe SSD storage.

X8aedz instances are now available in US West (Oregon) and Asia Pacific (Tokyo) regions. Customers can purchase X8aedz instances via Savings Plans, On-Demand instances, and Spot instances. To get started, sign in to the AWS Management Console. For more information visit the Amazon EC2 X8aedz instance page or AWS news blog.

 

​AWS announces Amazon EC2 X8aedz, next generation memory optimized instances, powered by 5th Gen AMD EPYC processors (formerly code named Turin). These instances offer the highest maximum CPU frequency, 5GHz in the cloud. They deliver up to 2x higher compute performance and 31% price-performance compared to previous generation X2iezn instances. X8aedz instances are built using the latest sixth generation AWS Nitro Cards and are ideal for electronic design automation (EDA) workloads such as physical layout and physical verification jobs, and relational databases that benefit from high single-threaded processor performance and a large memory footprint. The combination of 5 GHz processors and local NVMe storage enables faster processing of memory-intensive backend EDA workloads such as floor planning, logic placement, clock tree synthesis (CTS), routing, and power/signal integrity analysis. X8aedz instances feature a 32:1 ratio of memory to vCPU and are available in 8 sizes ranging from 2 to 96 vCPUs with 64 to 3,072 GiB of memory, including two bare metal variants, and up to 8 TB of local NVMe SSD storage. X8aedz instances are now available in US West (Oregon) and Asia Pacific (Tokyo) regions. Customers can purchase X8aedz instances via Savings Plans, On-Demand instances, and Spot instances. To get started, sign in to the AWS Management Console. For more information visit the Amazon EC2 X8aedz instance page or AWS news blog.  

Today, AWS announces the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P6e-GB300 UltraServers. P6e-GB300 UltraServers, accelerated by NVIDIA GB300 NVL72, provide 1.5x GPU memory and 1.5x FP4 compute (without sparsity) compared to P6e-GB200. 

Customers can optimize performance for the most powerful models in production with P6e-GB300 for applications that require higher context and implement emerging inference techniques like reasoning and Agentic AI.

To get started with P6e-GB300 UltraServers, please contact your AWS sales representative.

To learn more about P6e UltraServers and instances, visit Amazon EC2 P6 instances.

 

​Today, AWS announces the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P6e-GB300 UltraServers. P6e-GB300 UltraServers, accelerated by NVIDIA GB300 NVL72, provide 1.5x GPU memory and 1.5x FP4 compute (without sparsity) compared to P6e-GB200. 
Customers can optimize performance for the most powerful models in production with P6e-GB300 for applications that require higher context and implement emerging inference techniques like reasoning and Agentic AI.
To get started with P6e-GB300 UltraServers, please contact your AWS sales representative.
To learn more about P6e UltraServers and instances, visit Amazon EC2 P6 instances.  

Amazon Relational Database Service (Amazon RDS) for SQL Server now offers Microsoft SQL Server 2022 Developer Edition. SQL Server Developer Edition is a free edition of SQL Server that contains all the features of Enterprise Edition and can be used in any non-production environment. This enables customers to build, test, and demonstrate applications using SQL Server while reducing costs and maintaining consistency with their production database configurations.

Previously, customers that created Amazon RDS for SQL Server instances for development and test environments had to use SQL Server Standard Edition or SQL Server Enterprise Edition, which resulted in additional database licensing costs for non-production usage. Now, customers can lower the cost of their Amazon RDS development and testing instances by using SQL Server Developer Edition. Furthermore, Amazon RDS for SQL Server features such as automated backups, automated software updates, monitoring, and encryption for development and testing purposes will work on Developer Edition.

The license for Microsoft SQL Server Developer Edition strictly limits its use to development and testing purposes. It cannot be used in a production environment, or for any commercial purposes that directly serve end-users. For more information, refer to the Amazon RDS for SQL Server User Guide. See Amazon RDS for SQL Server Pricing for pricing details and regional availability. 

 

​Amazon Relational Database Service (Amazon RDS) for SQL Server now offers Microsoft SQL Server 2022 Developer Edition. SQL Server Developer Edition is a free edition of SQL Server that contains all the features of Enterprise Edition and can be used in any non-production environment. This enables customers to build, test, and demonstrate applications using SQL Server while reducing costs and maintaining consistency with their production database configurations. Previously, customers that created Amazon RDS for SQL Server instances for development and test environments had to use SQL Server Standard Edition or SQL Server Enterprise Edition, which resulted in additional database licensing costs for non-production usage. Now, customers can lower the cost of their Amazon RDS development and testing instances by using SQL Server Developer Edition. Furthermore, Amazon RDS for SQL Server features such as automated backups, automated software updates, monitoring, and encryption for development and testing purposes will work on Developer Edition. The license for Microsoft SQL Server Developer Edition strictly limits its use to development and testing purposes. It cannot be used in a production environment, or for any commercial purposes that directly serve end-users. For more information, refer to the Amazon RDS for SQL Server User Guide. See Amazon RDS for SQL Server Pricing for pricing details and regional availability.