12/26/2024, 12:00:00 AM ~ 12/27/2024, 12:00:00 AM (UTC)
Recent Announcements
Amazon EKS introduces programmatic access to Kubernetes version availability
Amazon Elastic Kubernetes Service (EKS) now lets you programmatically access availability of Kubernetes versions. This simplifies how you can discover and select available versions before creating or upgrading clusters.\n Kubernetes evolves rapidly, introducing three minor version releases each year with new features, design updates, and bug fixes. EKS provides standard support for each minor version for 14 months after release. After standard support ends, the version enters a 12-month extended support period. EKS stops supporting Kubernetes versions 26 months after their release. With this launch, you can now programmatically retrieve Kubernetes version metadata, including support status and dates. You can also discover the EKS platform version and default Kubernetes version EKS will use when creating new clusters. This feature is now generally available in all commercial AWS regions and the AWS GovCloud (US) Regions. To get started, see the EKS user guide and API specification.
Amazon EC2 Im4gn Instances are now available in Europe (Spain) region
Starting today, Amazon EC2 Im4gn Instances are available in Europe (Spain) region. Im4gn instances are built on the AWS Nitro System and are powered by AWS Graviton2 processors. They feature up to 30TB of instance storage with the 2nd Generation AWS Nitro SSDs that are custom-designed by AWS to maximize the storage performance of I/O intensive workloads such as SQL/NoSQL databases, search engines, distributed file systems and data analytics which continuously read and write from the SSDs in a sustained manner. AWS Nitro SSDs enable up to 60% lower latency and up to 75% reduced latency variability in Im4gn instances compared to the third generation of storage optimized instances. These instances maximize the number of transactions processed per second (TPS) for I/O intensive workloads such as relational databases (e.g. MySQL, MariaDB, PostgreSQL), and NoSQL databases (KeyDB, ScyllaDB, Cassandra) which have medium-large size data sets and can benefit from high compute performance and high network throughput. They are also an ideal fit for search engines, and data analytics workloads requiring fast access to data sets on local storage.\n The Im4gn instances also feature up to 100 Gbps networking and support for Elastic Fabric Adapter (EFA) for applications requiring high levels of inter-node communication. Get started with Im4gn instances by visiting the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. To learn more, visit the Im4gn instances page.
Amazon ECR expands registry policy to all ECR actions
Today, Amazon Elastic Container Registry (Amazon ECR) announces registry policy v2 which now supports managing IAM permissions for all ECR API actions. This new registry policy makes it easier for customers to control usage of ECR capabilities within their accounts.\n ECR registry policy allows customers to control usage of ECR private registries by granting permissions to perform registry-level actions to an AWS IAM principal. Registry policy version 1 (v1), only supported three actions: ReplicateImage, BatchImportUpstreamImage, and CreateRepository. Now, the new registry policy version 2 (v2) supports every ECR action. Using registry policy v2 makes it easier for customers to control permissions across all repositories in an ECR registry, allowing them to improve their security posture and save time versus configuring permissions individually across multiple repositories. ECR registry policy v2 is now available for all ECR registries in all AWS commercial regions. You can migrate from registry policy v1 to v2 using the ECR management console or with the new ECR put-account-setting API. New ECR accounts will automatically use registry policy v2. To learn more about ECR’s registry policy and permissions, see our documentation.
Llama 3.3 70B now available on AWS via Amazon SageMaker JumpStart
AWS customers can now access the Llama 3.3 70B model from Meta through Amazon SageMaker JumpStart. The Llama 3.3 70B model balances high performance with computational efficiency. It also delivers output quality comparable to larger Llama versions while requiring significantly fewer resources, making it an excellent choice for cost-effective AI deployments.\n Llama 3.3 70B features an enhanced attention mechanism that substantially reduces inference costs. Trained on approximately 15 trillion tokens, including web-sourced content and synthetic examples, the model underwent extensive supervised fine-tuning and Reinforcement Learning from Human Feedback (RLHF). This approach aligns outputs more closely with human preferences while maintaining high performance standards. According to Meta, this efficiency gain translates to nearly five times more cost-effective inference operations, making it an attractive option for production deployments. Customers can deploy Llama 3.3 70B through the SageMaker JumpStart user interface or programmatically using the SageMaker Python SDK. SageMaker AI’s advanced inference capabilities help optimize both performance and cost efficiency for your deployments, allowing you to take full advantage of Llama 3.3 70B’s inherent efficiency while benefiting from a streamlined deployment process. The Llama 3.3 70B model is available in all AWS Regions where Amazon SageMaker AI is available. To learn more about deploying Llama 3.3 70B on Amazon SageMaker JumpStart, see the documentation or read the blog.