7/25/2024, 12:00:00 AM ~ 7/26/2024, 12:00:00 AM (UTC)

Recent Announcements

AWS IAM Identity Center is now available in the Canada West (Calgary) AWS Region

You can now deploy AWS IAM Identity Center in the Canada West (Calgary) AWS Region. With the addition of this AWS Region, IAM Identity Center is now available in 33 AWS Regions globally.\n IAM Identity Center is the recommended service for managing workforce access to AWS applications and multiple AWS accounts. Use IAM Identity Center with your existing identity source or create a new directory, and manage workforce access to part or all of your AWS environment. With IAM Identity Center, you can manage and audit user access more easily and consistently, your workforce has single sign-on access and unified experience across AWS services, and your data owners can authorize and log data access by user. IAM Identity Center is available to you at no additional cost.

Amazon SageMaker launches faster auto-scaling for Generative AI models

We are excited to announce a new capability in Amazon SageMaker Inference that helps customers reduce the time it takes for their Generative AI models to scale automatically. They can now use sub-minute metrics and significantly reduce overall scaling latency for AI models. Using this enhancement customers can improve the responsiveness of their Generative AI applications as demand fluctuates.\n With this capability customers get two new high resolution CloudWatch metrics - ConcurrentRequestsPerModel and ConcurrentRequestsPerModelCopy - that enable faster autoscaling. These metrics are emitted at a 10 second interval and provide a more accurate representation of the load on the endpoint by tracking the actual concurrency or number of in-flight inference requests being processed by the model. Customers can create auto-scaling policies using these high-resolution metrics to scale their models deployed on SageMaker endpoints. Amazon SageMaker will start adding new instances or model copies in under a minute when thresholds defined in these auto-scaling policies are reached. This allows customers to optimize performance and cost-efficiency for their inference workloads on SageMaker. This new capability is accessible on accelerator instance families (g4dn, g5, g6, p2, p3, p4d, p4de, p5, inf1, inf2, trn1n, trn1) in all AWS regions where Amazon SageMaker Inference is available, except China and the AWS GovCloud (US) Regions. To learn more, see AWS ML blog and visit our documentation.

Amazon GameLift now supports AWS Nigeria Local Zone

Today, we are excited to announce the general availability (GA) of an update to Amazon GameLift that expands support to the AWS Nigeria region Local Zone, which increases coverage for game developers, while providing seamless, low-latency gameplay experiences for players. With this update, game developers can tap into the Nigeria Local Zone to reach players across the continent of Africa.\n AWS Local Zones are a type of infrastructure deployment that extends AWS Regions to place compute, storage, database, and other AWS services at the edge of the cloud near large population, industry, and information technology (IT) centers—enabling developers to deploy games that require single-digit millisecond latency closer to end users or on-premises data centers. With the latest update developers can now:

Deploy your game to a Nigeria Local Zone Fleet location.

Update a queue with a Fleet location in the Nigeria Local Zone.

Match players into games sessions in Nigeria Local Zone locations.

To get started, visit the Amazon GameLift documentation to see a complete list of regions. Amazon GameLift is available in regions: US East (Ohio and N. Virginia), US West (N. California and Oregon), Africa (Cape Town), Asia Pacific (Hong Kong, Mumbai, Seoul, Singapore, Sydney, Osaka, and Tokyo), Canada (Central), Europe (Frankfurt, Ireland, London, Milan, Paris, and Stockholm), Middle East (Bahrain), South America (São Paulo), AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and now available in 9 Local Zones in Chicago, Houston, Dallas, Kansas City, Denver, Atlanta, Los Angeles, Phoenix, and Nigeria.

AWS HealthImaging announces enhanced copy and update capabilities

AWS HealthImaging adds new copy and update capabilities, making it easier than ever to manage your medical imaging data. With this launch, you can more efficiently organize, combine, and update your medical imaging data to support common clinical and research workflows.\n This launch offers enhanced capabilities for modifying DICOM data, and simplifies resolving metadata inconsistencies. You can now copy one or more DICOM instances, making it easier organize your instances by imaging Study and Series. It is now easier to update metadata, including Study, Series, and SOP Instance UIDs, so you can keep data current as new patient information becomes available. This launch also gives you the ability to modify private DICOM metadata elements. Lastly, you can now revert metadata to a prior version with a single action. Together, these enhancements simplify workflows for improving the quality and consistency of your medical imaging data, throughout it’s lifecycle. AWS HealthImaging is now generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more, see Modifying image sets in the AWS HealthImaging Developer Guide.

Amazon ECR repository creation templates are now generally available

Amazon Elastic Container Registry (ECR) is announcing the general availability of repository creation templates, which allow customers to specify initial configuration for repositories that are automatically created by ECR via pull through cache and replication. ECR customers can specify configuration for these repositories, including encryption settings, lifecycle policies, and repository permissions. This enables customers to define custom configurations and assign them as defaults for various use cases within their registries.\n Repository creation templates can specify configuration for all repository settings including resource-based access policies, tag immutability, encryption, and lifecycle policies. Each template contains a customer specified prefix which is used to match new repositories to a specific template. As new repositories are created by ECR, the configuration is applied automatically. This enables customers to control which configuration is applied to new repositories created via pull through cache and replication, and customize default creation settings.

AWS Step Functions now supports Customer Managed Keys

AWS Step Functions now supports the use of Customer Managed Keys with AWS Key Management Service (AWS KMS) to encrypt Step Functions State Machine and Activity resources. This new capability enables you to encrypt your workflow definitions and execution data using your own encryption keys.\n AWS Step Functions is a visual workflow service capable of orchestrating over 12,000+ API actions from over 220 AWS services to build distributed applications and data processing workloads. With support for Customer Managed Keys, you have more fine-grained security control over your workflow data, making it easier to meet your organization’s regulatory and compliance requirements. You can also audit and track usage of your encryption keys with AWS CloudTrail. To learn more about using Customer Managed Keys with AWS Step Functions, visit AWS Step Functions documentation and AWS KMS documentation.

CloudWatch RUM PutRumEvents API now supports data event logging in AWS CloudTrail

CloudWatch RUM, which helps you perform real user monitoring by collecting client-side data of application performance and user interactions in real time, now supports AWS CloudTrail data event logging for PutRumEvents API, enabling enhanced data visibility for governance, compliance, and operational auditing.\n Each data item collected using RUM web client or “app monitor“ is considered a RUM event and is sent to CloudWatch RUM using the PutRumEvents API. Now, CloudTrail logs would provide a comprehensive audit trail of PutRumEvents API calls, helping troubleshoot issues by providing insights into request parameters, source IP addresses, and timestamps. These logs can be used to gain visibility into your request activity, and archive it in a secure, highly available, and durable S3 data store. Using this you can identify throttling exceptions when API calls exceed the limit on account or when permission to send data is denied to the RUM app monitor on failing authentication. These logs can also be leveraged for Security Information and Event Management (SIEM) solutions to comply with audit and compliance requirements. You can enable AWS CloudTrail data events logging for CloudWatch RUM in all AWS Regions where CloudWatch RUM is available. Get started with CloudTrail event logging for CloudWatch RUM by using the CloudTrail console, AWS CLI, or AWS SDKs. For pricing information, visit the CloudTrail pricing page. Click here to see all RUM APIs logged in CloudTrail, and see the CloudWatch RUM user guide to learn more.

AWS Clean Rooms launches new capabilities for entity resolution, ML modeling, privacy, and analysis controls

Today, AWS Clean Rooms announces four new enhancements: the general availability of AWS Entity Resolution on Clean Rooms, additional privacy controls for data analyses, a feature to configure which collaborators receive analyses results, and the ability to generate seed data for lookalike modeling using SQL. These capabilities help you improve data matching, and give you increased control and flexibility for data collaborations.\n AWS Entity Resolution is now natively integrated within AWS Clean Rooms to help you and your partners more easily prepare and match related customer records. Using rule-based or data service provider-based matching can help you improve data matching for enhanced advertising campaign planning, targeting, and measurement. For example, an advertiser can match records with a media publisher using rule-based matching, or with a data service provider such as LiveRamp to understand overlapping audiences. Enhanced privacy and analysis controls give you greater flexibility to support multiple use cases in a collaboration. You can now disallow specific output columns from custom SQL data analyses for increased data protection, and you can easily choose which collaborator receives analyses results. Additionally, you can now use a SQL query as the seed data source for lookalike modeling in AWS Clean Rooms ML. AWS Clean Rooms helps companies and their partners more easily analyze and collaborate on their collective datasets—without sharing or copying one another’s underlying data. AWS Clean Rooms is generally available in these AWS Regions. To learn more, visit the AWS Entity Resolution on AWS Clean Rooms blog.

Announcing 24 months support for Amazon EMR

Today, Amazon EMR announces 24 month support for Amazon EMR release versions. Amazon EMR aims to get the latest open-source versions of its Core Engines and Open Table Formats into your hands within 90 days from their upstream release. This extended support period gives customers peace of mind and a predictable timeline for budgeting, testing, and transitioning workloads.\n During this 24 month period, Amazon EMR will provide support and fixes for critical issues related to security, bugs, and data corruption, subject to the availability of fixes. Standard Support covers eligible components under recommended configurations. Amazon EMR intends to deploy fixes to the latest patch, minor or major versions as soon as fixes are available, and within 90 day timeframe of being verified by Amazon EMR. Amazon EMR will apply the fixes automatically whenever you launch a new EMR on EC2 cluster, a new EMR on EKS container, or a new Serverless job, so that you can benefit from the latest patches. Clusters past their 24 months support period will remain accessible even after the support period ends. To offer you with additional time to migrate from older releases, Amazon EMR will maintain existing levels of support for all releases for at least 12 months from today. After this period, Standard Support will be available for all eligible releases, on all deployment models – EMR on EC2, EMR on EKS and Serverless, in all regions where Amazon EMR operates, at no additional cost. To learn more about what’s included with support and how support works, please read the documentation.

Amazon EC2 D3en instances are now available in Asia Pacific (Jakarta) region

Starting today, Amazon EC2 D3en instances, the latest generation of the dense HDD-storage instances, are available in the Asia Pacific (Jakarta) region. D3en instances are ideal for workloads including distributed / clustered file systems, big data and analytics, and high capacity data lakes. With D3en instances, you can easily migrate from previous-generation D2 instances or on-premises infrastructure to a platform optimized for dense HDD storage workloads.\n Amazon EC2 D3en instances are built on the AWS Nitro System, a collection of AWS-designed hardware and software innovations that enable the delivery of private networking, and efficient, flexible, and secure cloud services with isolated multi-tenancy. D3en instances offer up to 336 TB of local HDD storage. These instances also offer up to 75 Gbps of network bandwidth, and up to 7 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To get started with D3en instances, visit the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. To learn more, visit the EC2 D3en instances page.

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