9/30/2024, 12:00:00 AM ~ 10/1/2024, 12:00:00 AM (UTC)

Recent Announcements

AWS Announces AWS re:Post Agent, a generative AI-powered virtual assistant

AWS re:Post launches re:Post Agent, a generative AI-powered assistant that’s designed to enhance customer interactions by offering intelligent and near real-time responses on re:Post. re:Post Agent provides the first response to questions in the re:Post community. Cloud developers can now get general technical guidance faster to successfully build and operate their cloud workloads.\n With re:Post Agent, you have a generative AI companion augmented by the community that expands the available AWS knowledge. Community experts can earn points to build their reputation status by reviewing answers from re:Post Agent. Visit AWS re:Post to collaborate with re:Post Agent and experience the power of generative AI-driven technical guidance.

Amazon AppStream 2.0 increases application settings storage limit

Amazon AppStream 2.0 has expanded the default size limit for application settings persistence from 1GB to 5GB. This increase allows end users to store more application data and settings with no manual intervention and without impacting the performance or session setup time.\n Application settings persistence allows users’ customizations and configurations to persist across sessions. When enabled, AppStream 2.0 automatically saves changes to a Virtual Hard Disk (VHD) stored in an S3 bucket unique to your account and AWS Region. This helps in enhancing the user experience by enabling users to resume work where they left off. With expanded default storage size and performance improvements, AppStream 2.0 makes it easier than ever for end users to retain their application data, settings, and customizations across sessions. The VHD syncs efficiently even for multi-gigabyte files due to optimizations in data syncing and access times. This feature is available at no additional cost in all regions where Amazon AppStream 2.0 is available. AppStream 2.0 offers pay-as-you go pricing. To get started with AppStream 2.0, see Getting Started with Amazon AppStream 2.0. To enable this feature for your users, you must use an AppStream 2.0 image that uses AppStream 2.0 agent released on or after September 18, 2024 or your image is using Managed AppStream 2.0 image updates released on or after September 20, 2024.

Amazon EventBridge announces new event delivery latency metric for Event Buses

Amazon EventBridge Event Bus now provides an end-to-end event delivery latency metric in Amazon CloudWatch that tracks the duration between event ingestion and successful delivery to the targets on your Event Bus. This new IngestionToInvocationSuccessLatency allows you to now detect and respond to event processing delays caused by under-performing, under-scaled, or unresponsive targets.\n Amazon EventBridge Event Bus is a serverless event router that enables you to create highly scalable event-driven applications by routing events between your own applications, third-party SaaS applications, and other AWS services. You can set up rules to determine where to send your events, allowing for applications to react to changes in your systems as they occur. With the new IngestionToInvocationSuccessLatency metric you can now better monitor and understand event delivery latency to your targets, increasing the observability of your event-driven architecture. Support for the new end-to-end latency metric for Event Buses is now available in all commercial AWS Regions. To learn more about the new IngestionToInvocationSuccessLatency metric for Amazon EventBridge Event Buses, please read our blog post and documentation.

Launch Amazon CloudWatch Internet Monitor from Amazon Network Load Balancer console

By adding your Network Load Balancer (NLB) to a monitor, you can gain improved visibility into your application’s internet performance and availability using Amazon CloudWatch Internet Monitor. You can now create or associate a monitor for an NLB directly when you create an NLB in the AWS Management console. You can create a monitor for the load balancer, or add the load balancer to an existing monitor, directly from the Integrations tab on the console.\n With a monitor, you can get detailed metrics about your application’s internet traffic that goes through a load balancer, with the ability to drill down into specific locations and internet service providers (ISPs). You also get health event alerts for internet issues that affect your application customers, and can review specific recommendations for improving the internet performance and availability for your application. After you create a monitor, you can customize it at any time by visiting the Internet Monitor console in Amazon CloudWatch. To learn more about how you can use and customize a monitor, see the Internet Monitor user guide documentation.

Amazon Inspector enhances engine for Lambda standard scanning

Today, Amazon Inspector announced an upgrade to the engine powering its Lambda standard scanning. This upgrade will provide you with a more comprehensive view of the vulnerabilities in the third-party dependencies used in your Lambda functions and associated Lambda layers in your environment. With the launch of this enhanced scanning engine, you will benefit from these capabilities without any disruption to your existing workflows. Existing customers can expect to see some findings closed as the new engine re-evaluates your existing resources to better assess risks, while also surfacing new vulnerabilities.\n Amazon Inspector is a vulnerability management service that continually scans AWS workloads including Amazon EC2 instances, container images, and AWS Lambda functions for software vulnerabilities, code vulnerabilities, and unintended network exposure across your entire AWS organization.

This improved version of Lambda standard scanning is available in all commercial and AWS GovCloud (US) Regions where Amazon Inspector is available. To learn more and get started with continual vulnerability scanning of your workloads, visit:

Getting started with Amazon Inspector

Amazon Inspector free trial

AWS CloudShell extends most recent capabilities to all commercial Regions

AWS CloudShell now supports Amazon Virtual Private Cloud (VPC) support, improved environment start times, and support for Docker environments in all commercial Regions where CloudShell is live. Previously, these features were only available in a limited set of CloudShell’s live commercial Regions. These features increase the productivity of CloudShell customers and enable a consistent experience across all CloudShell commercial Regions.\n CloudShell VPC support allows you to create CloudShell environments in a VPC, which enables you to use CloudShell securely within the same subnet as other resources in your VPC without the need for additional network configuration. Start times have been improved, enabling customers to begin using CloudShell more quickly. With the Docker integration, CloudShell users can initialize Docker containers on demand and connect to them to prototype or deploy Docker based resources with AWS CDK Toolkit. These features are now supported in all AWS Commercial Regions where AWS CloudShell is available today. For more information about the AWS Regions where AWS CloudShell is available, see the AWS Region table. Learn more about these expanded capabilities in the CloudShell Documentation, including specific entries on VPC Support and the Docker integration.

Amazon Aurora supports PostgreSQL 16.4, 15.8, 14.13, 13.16, and 12.20

Amazon Aurora PostgreSQL-Compatible Edition now supports PostgreSQL versions 16.4, 15.8, 14.13, 13.16, and 12.20. These releases contain product improvements and bug fixes made by the PostgreSQL community, along with Aurora-specific security and feature improvements. These releases also contain new Babelfish’s features and improvements. As a reminder, Amazon Aurora PostgreSQL 12 end of standard support is February 29, 2025. You can either upgrade to a newer major version or continue to run Amazon Aurora PostgreSQL 12 past the end of standard support date with RDS Extended Support.\n These releases are available in all commercial AWS regions and AWS GovCloud (US) Regions, except China regions. You can initiate a minor version upgrade by modifying your DB cluster. Please review the Aurora documentation to learn more. To learn which versions support each feature, head to our feature parity page. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.

Amazon Bedrock Model Evaluation now available in the AWS GovCloud (US-West) Region

Model Evaluation on Amazon Bedrock allows you to evaluate, compare, and select the best foundation models for your use case. Amazon Bedrock offers a choice of automatic evaluation and human evaluation. You can use automatic evaluation with predefined algorithms for metrics such as accuracy, robustness, and toxicity. Model evaluation provides built-in curated datasets or you can bring your own datasets.\n Amazon Bedrock’s interactive interface guides you through model evaluation. You simply choose automatic evaluation, select the task type and metrics, and upload your prompt dataset. Amazon Bedrock then runs evaluations and generates a report, so you can easily understand how the model performed against the metrics you selected, and choose the right one for your use case. Using this report in conjunction with the cost and latency metrics from the Amazon Bedrock, you can select the model with the required quality, cost, and latency tradeoff. Model Evaluation on Amazon Bedrock is now Generally Available in AWS GovCloud (US-West) in addition to many commercial regions. To learn more about Model Evaluation on Amazon Bedrock, see the Amazon Bedrock developer experience web page. To get started, sign in to Amazon Bedrock on the AWS Management Console or use the Amazon Bedrock APIs.

Amazon SES adds HTTPS open tracking for custom domains

Amazon Simple Email Service (SES) now supports HTTPS for tracking open and click events when using custom domains. Using HTTPS helps meet security compliance requirements and reduces the chances of email delivery issues with mailbox providers that reject non-secure links. The new feature provides the flexibility to configure HTTPS as mandatory for both open and click tracking, or make it optional based on the protocol of the links in your email.\n Previously, HTTPS was only available for click event tracking with custom domains. If you required HTTPS for tracking both open and clicks events, you were limited to the default tracking approach where the links in your emails were wrapped with an Amazon-provided domain that immediately redirected recipients to the intended destination. Now, you can secure the tracking of both open and click events while providing a trustworthy and branded experience for your recipients by using your own custom domain. This can help increase deliverability metrics and protect your sender reputation by isolating it from the reputation of other senders. You can enable HTTPS for open and click tracking with custom domains in all AWS Regions where Amazon SES is offered. To learn more, see the Amazon SES documentation for configuring custom domains for open and click tracking.

Amazon Redshift announces mTLS support for Amazon MSK

Amazon Redshift streaming ingestion already supports Amazon IAM authentication and with this announcement, we are now extending authentication methods with the addition of mutual transport layer security (mTLS) authentication between Amazon Redshift provisioned cluster or serverless workgroup and Amazon Managed Streaming for Apache Kafka (MSK) cluster or serverless.\n mTLS is an industry standard for authentication that provides the means for a server to authenticate a client it’s sending information to, and for the client to authenticate the server. The benefit of using mTLS is to provide a trusted authentication method that relies on each party (client & server) exchanging a certificate issued by mutually trusted certificate authorities. This is a common requirement for compliance reasons in a variety of applications in several industries, e.g., financial, retail, government and healthcare industries. mTLS authentication is available starting with Amazon Redshift patch 184 release in all AWS regions where Amazon Redshift and Amazon MSK are currently available. See AWS service availability by region for more information. To learn more about using mTLS authentication with Amazon Redshift streaming, please refer to the Amazon MSK and mTLS sub-sections of the Amazon Redshift streaming documentation.

Announcing sample-based partitioning for AWS HealthOmics variant stores

We are excited to announce that AWS HealthOmics variant stores are now optimized to improve sample based queries saving time and query costs for customers. AWS HealthOmics helps customers accelerate scientific breakthroughs by providing a fully managed service designed to handle bioinformatics and drug discovery workflows and storage at any scale. With this release, any new variant stores customer create will be automatically partitioned by the sample.\n This feature automatically partitions data loaded into a variant store by the sample information. Because of this partitioning, any analysis that includes sample level filtering no longer needs to scan the full set of data leading to a lower query cost and faster results. Sample based queries are common when using clinical outcome or phenotypic information to perform filtering. Sample partitioning is now supported for all new variant stores created in all regions where AWS HealthOmics is available: US East (N. Virginia), US West (Oregon), Europe (Frankfurt, Ireland, London), Asia Pacific (Singapore), and Israel (Tel Aviv). To get started using the variant store, see the AWS HealthOmics documentation.

Amazon Q in QuickSight now generates data stories that are personalized to users

Amazon Q in QuickSight announces personalization in data stories. A capability of Amazon Q in QuickSight, data stories helps users generate visually compelling documents and presentations that provide insights, highlight key findings, and recommend actionable next steps. With the addition of personalization to data stories, the generated narratives are tailored to the user and leverage employee location and job role to provide commentary that is more specific to the user’s organization.\n Amazon Q in QuickSight brings the power of Generative Business Intelligence to customers, enabling them to leverage natural language capabilities of Amazon Q to quickly extract insights from data, make better business decisions, and accelerate the work of business users. Personalization is automatically enabled for data stories and uses your organization’s employee profile data, without any additional setup. Amazon Q in QuickSight sources employee profile information from AWS IAM Identity Center that is connected to your organization’s identity provider. Personalization in data stories is initially available in the US East (N. Virginia) and US West (Oregon) AWS Regions. For more information, see Amazon QuickSight User Guide.

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