Today, AWS announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports AWS Neuron-powered instances with its Amazon Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS) AMIs. Customers using Bottlerocket AMIs can now deploy and manage machine learning inference and training workloads on AWS Neuron accelerated instance types, including Inf1, Inf2, Trn1, and Trn2. EKS customers can use these Bottlerocket AMIs with Karpenter version 1.2.2 and above.

This integration enables automated device management and scheduling capabilities while maintaining Bottlerocket’s focus on security and operational simplicity. Customers can leverage the standard Bottlerocket AMIs to deploy workloads on Neuron instances, with the ability to configure device ownership and resource allocation through familiar container orchestration interfaces.

Bottlerocket support for AWS Neuron-powered instances is available in all AWS Regions where Inf1, Inf2, Trn1, and Trn2 instances are offered. To get started, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.

 

​Today, AWS announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports AWS Neuron-powered instances with its Amazon Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS) AMIs. Customers using Bottlerocket AMIs can now deploy and manage machine learning inference and training workloads on AWS Neuron accelerated instance types, including Inf1, Inf2, Trn1, and Trn2. EKS customers can use these Bottlerocket AMIs with Karpenter version 1.2.2 and above. This integration enables automated device management and scheduling capabilities while maintaining Bottlerocket’s focus on security and operational simplicity. Customers can leverage the standard Bottlerocket AMIs to deploy workloads on Neuron instances, with the ability to configure device ownership and resource allocation through familiar container orchestration interfaces. Bottlerocket support for AWS Neuron-powered instances is available in all AWS Regions where Inf1, Inf2, Trn1, and Trn2 instances are offered. To get started, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.  

Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now provides a default bootstrap container image that simplifies system setup tasks, eliminating the need for most customers to maintain their own container images for initial configuration. Bootstrap containers are special-purpose containers that handle pre-startup operations such as directory creation, environment variable setup, and node-specific configurations before the main application containers start.

This enhancement allows customers to focus on their startup scripts rather than container image maintenance and regional availability. Previously, customers needed to create, maintain, and update their own container images while managing separate image repositories for each AWS Region. By using Bottlerocket’s default bootstrap container image, customers can specify their configuration tasks through simple user data, while the system automatically handles image updates. The default image is maintained by AWS, reducing operational overhead and improving system security.

The simplified bootstrap container configuration in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions. To learn more, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.
 

 

​Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now provides a default bootstrap container image that simplifies system setup tasks, eliminating the need for most customers to maintain their own container images for initial configuration. Bootstrap containers are special-purpose containers that handle pre-startup operations such as directory creation, environment variable setup, and node-specific configurations before the main application containers start. This enhancement allows customers to focus on their startup scripts rather than container image maintenance and regional availability. Previously, customers needed to create, maintain, and update their own container images while managing separate image repositories for each AWS Region. By using Bottlerocket’s default bootstrap container image, customers can specify their configuration tasks through simple user data, while the system automatically handles image updates. The default image is maintained by AWS, reducing operational overhead and improving system security. The simplified bootstrap container configuration in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions. To learn more, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.    

Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports NVIDIA’s Multi-Instance GPU (MIG) feature, enabling customers to partition NVIDIA GPUs into multiple GPU instances on Kubernetes nodes. This capability allows system administrators to maximize GPU resource utilization by running multiple workloads simultaneously on a single GPU while maintaining hardware-level isolation between workloads.

With MIG support, customers can optimize GPU resource allocation for workloads that don’t fully utilize the GPU’s compute capacity, such as machine learning inference tasks. Each GPU partition operates with complete hardware-level memory and fault isolation, providing workload separation and reliable performance.

NVIDIA Multi-Instance GPU support in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions where compatible NVIDIA GPU-enabled instances are offered. To learn more about MIG with the Bottlerocket NVIDIA variants, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.

 

​Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports NVIDIA’s Multi-Instance GPU (MIG) feature, enabling customers to partition NVIDIA GPUs into multiple GPU instances on Kubernetes nodes. This capability allows system administrators to maximize GPU resource utilization by running multiple workloads simultaneously on a single GPU while maintaining hardware-level isolation between workloads. With MIG support, customers can optimize GPU resource allocation for workloads that don’t fully utilize the GPU’s compute capacity, such as machine learning inference tasks. Each GPU partition operates with complete hardware-level memory and fault isolation, providing workload separation and reliable performance. NVIDIA Multi-Instance GPU support in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions where compatible NVIDIA GPU-enabled instances are offered. To learn more about MIG with the Bottlerocket NVIDIA variants, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.  

Starting today, Amazon Elastic Kubernetes Service (EKS) enables default envelope encryption for all Kubernetes API data in EKS clusters running Kubernetes version 1.28 or higher. This provides a managed, default experience that implements defense-in-depth for your Kubernetes applications. Using AWS Key Management Service (KMS) with Kubernetes KMS provider v2, EKS now provides an additional layer of security with an AWS owned, KMS encryption key or the option of bringing your own key.

Previously, Amazon EKS provided optional envelope encryption with Kubernetes KMS provider v1. Now this is a default configuration for all objects in the Kubernetes API. By default, AWS owns the keys used for envelope encryption. You can alternatively create or import externally generated keys to AWS KMS for use in your cluster’s managed Kubernetes control plane. If you have an existing customer managed key (CMK) in KMS that was previously used to envelope encrypt your Kubernetes Secrets, this same key will now be used for envelope encryption of the additional Kubernetes API data types in your cluster.

Default envelope encryption in Amazon EKS is automatically enabled for all EKS clusters running Kubernetes version 1.28 or higher, and doesn’t require any action from customers. This feature is available at no additional charge in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, visit the Amazon EKS documentation.

 

​Starting today, Amazon Elastic Kubernetes Service (EKS) enables default envelope encryption for all Kubernetes API data in EKS clusters running Kubernetes version 1.28 or higher. This provides a managed, default experience that implements defense-in-depth for your Kubernetes applications. Using AWS Key Management Service (KMS) with Kubernetes KMS provider v2, EKS now provides an additional layer of security with an AWS owned, KMS encryption key or the option of bringing your own key. Previously, Amazon EKS provided optional envelope encryption with Kubernetes KMS provider v1. Now this is a default configuration for all objects in the Kubernetes API. By default, AWS owns the keys used for envelope encryption. You can alternatively create or import externally generated keys to AWS KMS for use in your cluster’s managed Kubernetes control plane. If you have an existing customer managed key (CMK) in KMS that was previously used to envelope encrypt your Kubernetes Secrets, this same key will now be used for envelope encryption of the additional Kubernetes API data types in your cluster. Default envelope encryption in Amazon EKS is automatically enabled for all EKS clusters running Kubernetes version 1.28 or higher, and doesn’t require any action from customers. This feature is available at no additional charge in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, visit the Amazon EKS documentation.  

Amazon Connect now offers the ability to target up to 4 different combinations of agent proficiencies per routing step. By using up to 3 OR conditions, routing will try to match a contact with 4 different types of agents and increase the possibility of finding a suitable match. For example, if the back-up for a niche banking skills consists of agents trained on account management, registration, and tax then after an initial search for balance transfer agents you can attempt a match across all four types of agents at the same time.

This feature is available in all AWS regions where Amazon Connect is offered. To learn more about routing criteria, see the Amazon Connect Administrator Guide. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website.

 

​Amazon Connect now offers the ability to target up to 4 different combinations of agent proficiencies per routing step. By using up to 3 OR conditions, routing will try to match a contact with 4 different types of agents and increase the possibility of finding a suitable match. For example, if the back-up for a niche banking skills consists of agents trained on account management, registration, and tax then after an initial search for balance transfer agents you can attempt a match across all four types of agents at the same time. This feature is available in all AWS regions where Amazon Connect is offered. To learn more about routing criteria, see the Amazon Connect Administrator Guide. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in AWS Europe (Ireland) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. 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 M7g 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. M8g 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 M8g 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) M8g instances are available in AWS Europe (Ireland) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. 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 M7g 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. M8g 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 M8g 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 use AWS WAF in the AWS Asia Pacific (Thailand) and AWS Mexico (Central) Region.

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. Please note that only core AWS WAF features like AWS Managed Rules and rules are currently available in these new regions. For more information about the service, visit the AWS WAF page. AWS WAF pricing may vary between regions. For more information about pricing, visit the AWS WAF Pricing page.

 

​Starting today, you can use AWS WAF in the AWS Asia Pacific (Thailand) and AWS Mexico (Central) Region. 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. Please note that only core AWS WAF features like AWS Managed Rules and rules are currently available in these new regions. For more information about the service, visit the AWS WAF page. AWS WAF pricing may vary between regions. For more information about pricing, visit the AWS WAF Pricing page.  

Amazon Nova Pro foundation model now supports latency-optimized inference in preview on Amazon Bedrock, enabling faster response times and improved responsiveness for generative AI applications. Latency-optimized inference speeds up response times for latency-sensitive applications, improving the end-user experience and giving developers more flexibility to optimize performance for their use case. Accessing these capabilities requires no additional setup or model fine-tuning, allowing for immediate enhancement of existing applications with faster response times.

Latency optimized inference for Amazon Nova Pro is available via cross-region inference in US West (Oregon), US East (Virginia), and US East (Ohio) regions. Learn more about Amazon Nova foundation models at the AWS News Blog, the Amazon Nova product page, or the Amazon Nova user guide. Learn more about latency optimized inference on Bedrock in documentation. You can get started with Amazon Nova foundation models in Amazon Bedrock from the Amazon Bedrock console.

 

​Amazon Nova Pro foundation model now supports latency-optimized inference in preview on Amazon Bedrock, enabling faster response times and improved responsiveness for generative AI applications. Latency-optimized inference speeds up response times for latency-sensitive applications, improving the end-user experience and giving developers more flexibility to optimize performance for their use case. Accessing these capabilities requires no additional setup or model fine-tuning, allowing for immediate enhancement of existing applications with faster response times. Latency optimized inference for Amazon Nova Pro is available via cross-region inference in US West (Oregon), US East (Virginia), and US East (Ohio) regions. Learn more about Amazon Nova foundation models at the AWS News Blog, the Amazon Nova product page, or the Amazon Nova user guide. Learn more about latency optimized inference on Bedrock in documentation. You can get started with Amazon Nova foundation models in Amazon Bedrock from the Amazon Bedrock console.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8g instances are available in AWS Asia Pacific (Mumbai) 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 (Mumbai) 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) M7g instances are available in the AWS Europe (Zurich) region. These instances are powered by AWS Graviton3 processors that provide up to 25% better compute performance compared to AWS Graviton2 processors, and built on top of the the AWS Nitro System, a collection of AWS designed innovations that deliver efficient, flexible, and secure cloud services with isolated multi-tenancy, private networking, and fast local storage.

Amazon EC2 Graviton3 instances also use up to 60% less energy to reduce your cloud carbon footprint for the same performance than comparable EC2 instances. For increased scalability, these instances are available in 9 different instance sizes, including bare metal, and offer up to 30 Gbps networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (EBS).

To learn more, see Amazon EC2 M7g. 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) M7g instances are available in the AWS Europe (Zurich) region. These instances are powered by AWS Graviton3 processors that provide up to 25% better compute performance compared to AWS Graviton2 processors, and built on top of the the AWS Nitro System, a collection of AWS designed innovations that deliver efficient, flexible, and secure cloud services with isolated multi-tenancy, private networking, and fast local storage. Amazon EC2 Graviton3 instances also use up to 60% less energy to reduce your cloud carbon footprint for the same performance than comparable EC2 instances. For increased scalability, these instances are available in 9 different instance sizes, including bare metal, and offer up to 30 Gbps networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (EBS). To learn more, see Amazon EC2 M7g. 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.