Amazon EC2 now supports up to the full EC2 instance bandwidth for inter-region VPC peering traffic and to AWS Direct Connect. Additionally, EC2 supports jumbo frames up to 8500 Bytes for cross region VPC peering. Before today, the egress bandwidth for EC2 instances was limited to 50% of the aggregate bandwidth limit for instances with 32 or more vCPUs, and 5 Gbps for smaller instances. Cross region peering supported up to 1500 bytes. Now, customers can send bandwidth from EC2 between regions or towards AWS Direct Connect at the full instance baseline specification or 5Gbps, whichever is greater and customers can use jumbo frames across regions for peered VPCs.

Customers transferring data between regions or from EC2 to their on-premises network via AWS Direct Connect now have access to the full instance bandwidth capabilities. Before today, customers sending traffic to any destination not in the same region had a lower bandwidth limit. With this change, the lower limit has been removed for destinations between AWS regions and to on-premises through AWS Direct Connect, allowing for faster transfers. Additionally, supporting jumbo frames for peering makes sending large volumes of data faster than before.

This capability is available in all AWS commercial regions, the AWS GovCloud (US) Regions, and the Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. Customers can take advantage of this capability without any additional changes. To learn more about EC2 bandwidth capabilities, please review our user guide.

 

​Amazon EC2 now supports up to the full EC2 instance bandwidth for inter-region VPC peering traffic and to AWS Direct Connect. Additionally, EC2 supports jumbo frames up to 8500 Bytes for cross region VPC peering. Before today, the egress bandwidth for EC2 instances was limited to 50% of the aggregate bandwidth limit for instances with 32 or more vCPUs, and 5 Gbps for smaller instances. Cross region peering supported up to 1500 bytes. Now, customers can send bandwidth from EC2 between regions or towards AWS Direct Connect at the full instance baseline specification or 5Gbps, whichever is greater and customers can use jumbo frames across regions for peered VPCs. Customers transferring data between regions or from EC2 to their on-premises network via AWS Direct Connect now have access to the full instance bandwidth capabilities. Before today, customers sending traffic to any destination not in the same region had a lower bandwidth limit. With this change, the lower limit has been removed for destinations between AWS regions and to on-premises through AWS Direct Connect, allowing for faster transfers. Additionally, supporting jumbo frames for peering makes sending large volumes of data faster than before. This capability is available in all AWS commercial regions, the AWS GovCloud (US) Regions, and the Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. Customers can take advantage of this capability without any additional changes. To learn more about EC2 bandwidth capabilities, please review our user guide.  

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and third-party sources. Amazon DataZone now supports metadata rules for data publishing workflows, in addition to existing support for subscription workflows. This enhancement allows organizations to enforce metadata standards consistently across both producer and consumer workflows. By standardizing metadata practices, organizations can improve compliance, enhance audit readiness, and streamline workflows for greater efficiency and control.

With metadata rules, domain owners can define mandatory metadata fields that data users must complete when publishing assets to the catalog or requesting access to data. For example, a financial services organization can require producers to classify data before publication, and consumers to provide project details and compliance evidence as part of an access request. Healthcare providers can use metadata rules to enforce metadata standards to align with patient data regulations.
Metadata rules also enable the creation of custom approval workflows for subscriptions to assets, using collected metadata to facilitate access decisions or auto-fulfillment—outside of Amazon DataZone.

To get started with metadata rules—

• Read the user guide for creating rules in the publishing workflow
• Read the user guide for creating rules in subscription requests

 

​Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and third-party sources. Amazon DataZone now supports metadata rules for data publishing workflows, in addition to existing support for subscription workflows. This enhancement allows organizations to enforce metadata standards consistently across both producer and consumer workflows. By standardizing metadata practices, organizations can improve compliance, enhance audit readiness, and streamline workflows for greater efficiency and control. With metadata rules, domain owners can define mandatory metadata fields that data users must complete when publishing assets to the catalog or requesting access to data. For example, a financial services organization can require producers to classify data before publication, and consumers to provide project details and compliance evidence as part of an access request. Healthcare providers can use metadata rules to enforce metadata standards to align with patient data regulations. Metadata rules also enable the creation of custom approval workflows for subscriptions to assets, using collected metadata to facilitate access decisions or auto-fulfillment—outside of Amazon DataZone. To get started with metadata rules—

Read the user guide for creating rules in the publishing workflow
Read the user guide for creating rules in subscription requests  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS US West (N. California) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.
 

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS US West (N. California) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.    

You can now use AWS PrivateLink to privately access Amazon ElastiCache from your Amazon Virtual Private Cloud (Amazon VPC). AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises networks, without exposing traffic to the public internet and securing your network traffic. The Amazon ElastiCache API supports AWS PrivateLink in AWS Asia Pacific (Jakarta) and Asia Pacific (Hyderabad) Regions.

To use AWS PrivateLink with Amazon ElastiCache, you create an interface VPC endpoint for Amazon ElastiCache in your VPC using the Amazon VPC console, AWS SDK, or AWS CLI. With an interface VPC endpoint, you can privately access the Amazon ElastiCache APIs from applications inside your Amazon VPC. You can also access the VPC endpoint from other VPCs using VPC Peering or your on-premises environments using AWS VPN or AWS Direct Connect. To learn more, read the documentation, or get started in the Amazon VPC Console.

 

​You can now use AWS PrivateLink to privately access Amazon ElastiCache from your Amazon Virtual Private Cloud (Amazon VPC). AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises networks, without exposing traffic to the public internet and securing your network traffic. The Amazon ElastiCache API supports AWS PrivateLink in AWS Asia Pacific (Jakarta) and Asia Pacific (Hyderabad) Regions. To use AWS PrivateLink with Amazon ElastiCache, you create an interface VPC endpoint for Amazon ElastiCache in your VPC using the Amazon VPC console, AWS SDK, or AWS CLI. With an interface VPC endpoint, you can privately access the Amazon ElastiCache APIs from applications inside your Amazon VPC. You can also access the VPC endpoint from other VPCs using VPC Peering or your on-premises environments using AWS VPN or AWS Direct Connect. To learn more, read the documentation, or get started in the Amazon VPC Console.  

You can now use Amazon EBS gp3 and io1 volumes in AWS Dedicated Local Zones. Dedicated Local Zones are a type of AWS infrastructure that are fully managed by AWS, built for exclusive use by you or your community, and placed in a location or data center specified by you to help you comply with regulatory requirements. In Dedicated Local Zones, these volumes are purpose-built to store data in a specific data perimeter, helping to support your data isolation and data residency use cases.

The latest generation of General Purpose SSD volumes (gp3) enable customers to provision performance independently of storage capacity, providing up to 20% lower price point per GB than existing gp2 volumes. Provisioned IOPS SSD (io1) volumes are designed to meet the needs of I/O-intensive and latency-sensitive transactional workloads like databases.

You can manage gp3 and io1 volumes using the AWS Management Console, the AWS Command Line Interface (CLI), or the AWS SDKs. For more information on gp3 and io1 volumes, see the product overview page.
 

 

​You can now use Amazon EBS gp3 and io1 volumes in AWS Dedicated Local Zones. Dedicated Local Zones are a type of AWS infrastructure that are fully managed by AWS, built for exclusive use by you or your community, and placed in a location or data center specified by you to help you comply with regulatory requirements. In Dedicated Local Zones, these volumes are purpose-built to store data in a specific data perimeter, helping to support your data isolation and data residency use cases. The latest generation of General Purpose SSD volumes (gp3) enable customers to provision performance independently of storage capacity, providing up to 20% lower price point per GB than existing gp2 volumes. Provisioned IOPS SSD (io1) volumes are designed to meet the needs of I/O-intensive and latency-sensitive transactional workloads like databases. You can manage gp3 and io1 volumes using the AWS Management Console, the AWS Command Line Interface (CLI), or the AWS SDKs. For more information on gp3 and io1 volumes, see the product overview page.    

Starting today, you can build, train, and deploy machine learning (ML) models in Mexico (Central).

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 Mexico (Central). 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.    

AWS CodeBuild now supports an enhanced S3 caching experience. You can now define custom cache keys for more granular cache management and improved cache persistence across your builds. You can also share the cache keys across projects to use a common dependency cache to speed up your builds. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment.

Additionally, CodeBuild added support for fallback keys, which allows partial matches when an exact cache key is not found. This capability enables efficient caching sharing between similar builds, such as builds with common dependencies, without needing to rebuild everything. You can also specify an optional action to skip the cache save or restore step for a more flexible cache management.

These caching enhancements are available in all AWS Regions where CodeBuild is offered. To learn more, please visit our documentation. To get started with CodeBuild, visit the AWS CodeBuild product page.

 

​AWS CodeBuild now supports an enhanced S3 caching experience. You can now define custom cache keys for more granular cache management and improved cache persistence across your builds. You can also share the cache keys across projects to use a common dependency cache to speed up your builds. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment. Additionally, CodeBuild added support for fallback keys, which allows partial matches when an exact cache key is not found. This capability enables efficient caching sharing between similar builds, such as builds with common dependencies, without needing to rebuild everything. You can also specify an optional action to skip the cache save or restore step for a more flexible cache management. These caching enhancements are available in all AWS Regions where CodeBuild is offered. To learn more, please visit our documentation. To get started with CodeBuild, visit the AWS CodeBuild product page.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8g instances are available in AWS Asia Pacific (Tokyo) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 C8g instances are built for compute-intensive workloads, such as high performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning (ML) inference, and ad serving. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon C7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. C8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

To learn more, see Amazon EC2 C8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.
 

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8g instances are available in AWS Asia Pacific (Tokyo) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 C8g instances are built for compute-intensive workloads, such as high performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning (ML) inference, and ad serving. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon C7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. C8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 C8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.    

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

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 (Thailand). 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.    

Amazon GameLift Servers now supports Amazon EC2 5th through 8th generation instances, offering enhanced price-performance, efficiency, and flexibility for game server hosting. This update allows developers to leverage the latest advancements in EC2 compute, memory, and networking across three main instance families:

1. General Purpose (M-series): Balanced CPU, memory, and networking for a wide range of game workloads.
2. Compute Optimized (C-series): High-performance compute instances with a 2:1 memory ratio, ideal for CPU-intensive game servers.
3. Memory Optimized (R-Series): Optimized for high-memory workloads with an 8:1 memory ratio, supporting complex simulations and large player sessions.

Each new EC2 generation brings significant improvements:

• 5th Gen: Proven reliability with Intel processors with balanced performance
• 6th Gen: Includes AWS Graviton2 ARM-based options alongside Intel and AMD variants offering enhanced price-performance efficiency.
• 7th Gen: The latest evolution featuring DDR5 memory, enhanced networking, and offering significant performance gains over previous generations.
• 8th Gen: Cutting-edge AWS Graviton4 and Intel Xeon-based instances for demanding workloads

Customers can also choose variants with local storage (d), enhanced networking (n), and different processor architectures (Intel, AMD, Graviton – i/a/g).

This update empowers developers with greater flexibility, scalability, and cost efficiency to optimize game server performance. Customers can now seamlessly transition workloads to newer EC2 generations, leveraging AWS’s continuous innovation for building, scaling, and operating multiplayer games globally.

These next-generation instances are available in Amazon GameLift Servers supported regions, except AWS China. For more information on launching fleets with next-generation EC2 instances, visit the Amazon GameLift Servers documentation and EC2 Instance Types overview.

 

​Amazon GameLift Servers now supports Amazon EC2 5th through 8th generation instances, offering enhanced price-performance, efficiency, and flexibility for game server hosting. This update allows developers to leverage the latest advancements in EC2 compute, memory, and networking across three main instance families:

General Purpose (M-series): Balanced CPU, memory, and networking for a wide range of game workloads.
Compute Optimized (C-series): High-performance compute instances with a 2:1 memory ratio, ideal for CPU-intensive game servers.
Memory Optimized (R-Series): Optimized for high-memory workloads with an 8:1 memory ratio, supporting complex simulations and large player sessions.

Each new EC2 generation brings significant improvements:

5th Gen: Proven reliability with Intel processors with balanced performance
6th Gen: Includes AWS Graviton2 ARM-based options alongside Intel and AMD variants offering enhanced price-performance efficiency.
7th Gen: The latest evolution featuring DDR5 memory, enhanced networking, and offering significant performance gains over previous generations.
8th Gen: Cutting-edge AWS Graviton4 and Intel Xeon-based instances for demanding workloads

Customers can also choose variants with local storage (d), enhanced networking (n), and different processor architectures (Intel, AMD, Graviton – i/a/g). This update empowers developers with greater flexibility, scalability, and cost efficiency to optimize game server performance. Customers can now seamlessly transition workloads to newer EC2 generations, leveraging AWS’s continuous innovation for building, scaling, and operating multiplayer games globally. These next-generation instances are available in Amazon GameLift Servers supported regions, except AWS China. For more information on launching fleets with next-generation EC2 instances, visit the Amazon GameLift Servers documentation and EC2 Instance Types overview.