8/17/2022, 12:00:00 AM ~ 8/18/2022, 12:00:00 AM (UTC)

Recent Announcements

Announcing AWS Resilience Hub support for Elastic Load Balancing and Amazon Route 53 Application Recovery Controller

You can now use AWS Resilience Hub with Elastic Load Balancing (ELB) and Amazon Route 53 Application Recovery Controller readiness checks to help meet your application’s recovery objectives. Resilience Hub provides you with a single place to define, validate, and track the resilience of your applications so that you can avoid unnecessary downtime caused by software, infrastructure, or operational disruptions.

AWS Well-Architected Tool now available in AWS GovCloud (US) Regions

AWS is excited to announce that the AWS Well-Architected Tool is now available in AWS GovCloud (US) Regions. AWS GovCloud (US) is an isolated region designed to host sensitive data and regulated workloads in the cloud. The AWS Well-Architected Tool is used to help customers review the state of their applications and workloads against architectural best practices, and improve decision-making, minimize risks, and reduce costs. With this Region expansion, customers with specific regulatory and compliance requirements and AWS Partners in both the public and commercial sectors can now conduct self-service Well-Architected Reviews.

AWS Cost Anomaly Detection gets a simplified interface for anomaly exploration

Starting today, customers of AWS Cost Anomaly Detection will see a new interface in the console, where they view and analyze anomalies and their root causes. AWS Cost Anomaly Detection monitors customers’ spending patterns to detect and alert on anomalous (increased) spend, and to provide root cause analyses.

AWS Trusted Advisor Priority is now generally available for AWS Enterprise Support customers

AWS Trusted Advisor Priority is now generally available for AWS Enterprise Support customers, helping IT leaders focus on key cloud optimization opportunities through curated recommendations prioritized by their AWS account teams. AWS Trusted Advisor provides recommendations that help you follow AWS best practices across cost optimization, performance, security, reliability, and service quotas.

Amazon Rekognition Custom Labels now offers the ability to copy trained computer vision models across AWS accounts

Amazon Rekognition Custom Labels is an automated machine learning (AutoML) service that allows customers to build custom computer vision models to classify and identify objects in images that are specific and unique to their business. Custom Labels does not require customers to have any prior computer vision expertise or knowledge.

Amazon EKS announces cluster-level cost allocation tagging

Amazon Elastic Kubernetes Service (EKS) now makes it easier for customers to understand how their Amazon EC2 costs are driven by individual EKS clusters. Customers who choose to use multiple EKS clusters to segment their workloads to improve their resilience and/or security posture now get breakdowns of their EC2 costs by EKS cluster using AWS Cost and Usage reporting with minimal additional effort.

Announcing wildcard support in Amazon EKS Fargate Profile Selectors

Amazon Elastic Kubernetes Service (Amazon EKS) now allows you to more easily run workloads from various Kubernetes namespaces on AWS Fargate serverless compute with a single EKS Fargate Profile. Using Amazon EKS on AWS Fargate enables you to use Kubernetes without having to worry about compute infrastructure configuration and maintenance. Previously, you had to specify all the namespaces at the time you created the EKS Fargate Profile and were limited to a total of 5 namespace selectors or label pairs.

AWS Ground Station adds support for wideband Digital Intermediate Frequency in Africa (Cape Town), Europe (Ireland), and Asia Pacific (Singapore)

Amazon Web Services (AWS) announces expansion of wideband Digital Intermediate Frequency (DigIF) support for Software Defined Radios (SDRs) to enable customers to downlink more data in less time and reduce costs. AWS Ground Station regions Africa (Cape Town), Europe (Ireland), and Asia Pacific (Singapore) join the Middle East (Bahrain) region to offer customers a total of four locations where expanded support for SDRs is now available in Preview.

Amazon Lex now supports conditional branching for simplified dialog management

Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, you can quickly and easily build conversational bots (“chatbots”), virtual agents, and interactive voice response (IVR) systems. Today, we are excited to announce support for conditional branching capability so you can easily design conversations for your users. Instead of implementing custom code, you can add simple conditions directly to your Lex bot, and manage the conversation path dynamically based on user input and business knowledge.

Amazon Redshift announces federated SSO support with ease of use and security capabilities enhancements for Query Editor V2.

Amazon Redshift Query Editor v2 , a free web-based tool for data exploration and analysis using SQL, is now enhanced with additional ease of use and security capabilities. Amazon Redshift Query Editor v2 simplifies the process for admins and end-users to connect Amazon Redshift clusters using their Identity Provider(IdP). As an administrator, you now can integrate your Identity Provider(IdP) with Amazon AWS console to access the Query Editor v2 as a federated user. You need to configure your identity provider (IdP) to pass in database user and (optionally) database groups by adding specific principal tags as SAML attributes.

Amazon EC2 P4d Instances now available in AWS GovCloud (US) Region

We are excited to announce the availability of Amazon EC2 P4d instances in the AWS GovCloud (US) Region. P4d instances are optimized for applications in Machine Learning (ML) and High Performance Computing (HPC).

AWS App Mesh adds support for multiple listeners

AWS App Mesh adds support for multiple listeners, allowing you to run applications with several open ports in a mesh. This enables you to control and secure inbound and outbound traffic for different application ports, as well as to collect port-specific metrics for this traffic. AWS App Mesh is a service mesh that provides application-level networking to make it easier for your services to communicate with each other across multiple types of compute infrastructure. AWS App Mesh standardizes how your services communicate, giving you end-to-end visibility and options to tune for high-availability of your applications.

AWS Lambda now supports custom Consumer Group IDs for Amazon MSK and Self-Managed Kafka as event sources

AWS Lambda now supports custom Consumer Group IDs when using Amazon Managed Streaming for Apache Kafka (MSK) or Self-Managed Kafka as an event source. Kafka uses Consumer Group IDs to identify consumer membership and record consumer checkpoints. Using a custom Consumer Group ID is ideal for customers with workloads that require disaster recovery or fail‑over support.

Amazon EC2 High Memory instances are now available in US East (Ohio), South America (Sao Paulo) and Asia Pacific (Sydney) regions

Starting today, Amazon EC2 High Memory instances with 12TB of memory (u-12tb1.112xlarge) are available in the US East (Ohio) region. Additionally, high memory instances with 6TB of memory (u-6tb1.56xlarge, u-6tb1.112xlarge) are now available in the South America (Sao Paulo) region and instances with 3TB of memory (u-3tb1.56xlarge) are now available in the South America (Sao Paulo) and Asia Pacific (Sydney) regions.

Amazon Aurora now supports Internet Protocol Version 6 (IPv6)

Amazon Aurora now offers customers the option to use Internet Protocol version 6 (IPv6) addresses in their Amazon Virtual Private Cloud (VPC) on new and existing Amazon Aurora instances. Customers moving to IPv6 can simplify their network stack by running their databases on a network that supports both IPv4 and IPv6.

Amazon SageMaker Canvas enables faster onboarding with automatic data import from local disk

Amazon SageMaker Canvas now enables faster onboarding allowing users to import data from their local disk automatically, without additional steps. SageMaker Canvas is a visual point-and-click interface that enables business analysts to generate accurate ML predictions on their own — without requiring any machine learning experience or having to write a single line of code. SageMaker Canvas makes it easy to access and combine data from a variety of sources, automatically clean data, and build ML models to generate accurate predictions with a few clicks.

Amazon OpenSearch Service now provides improved visibility into validation errors during blue/green deployments

Amazon OpenSearch Service now provides improved visibility into validation failures during domain updates. You can monitor the progress of a domain update, which could involve a blue/green deployment, from the OpenSearch Service console, or through the configuration APIs. OpenSearch Service will publish any validation failure events to Amazon EventBridge. You can also view these validation events in the Notifications tab of the OpenSearch Service console.

AWS App Mesh introduces configurable Envoy access log format

AWS App Mesh introduces support for customizable Envoy access log format for Virtual Nodes and Virtual Gateways. It enables you to diagnose your services with customized logging focusing on specific aspects that are important to you. AWS App Mesh is a service mesh that provides application-level networking to make it easier for your services to communicate with each other across multiple types of compute infrastructure. AWS App Mesh standardizes how your services communicate, giving you end-to-end visibility and options to tune for high-availability of your applications.

Amazon SageMaker Pipelines now supports the testing of machine learning workflows in your local environment

SageMaker Pipelines is a tool that helps you build machine learning pipelines that take advantage of direct SageMaker integration. SageMaker Pipelines now supports creating and testing pipelines in your local machine (e.g. your computer). With this launch, you can test your Sagemaker Pipelines scripts and parameters compatibility locally before running them in on SageMaker in the cloud. Sagemaker Pipelines Local Mode supports the following steps: processing, training, transform, model, condition, and fail. These steps give you the flexibility to define various entities in your machine learning workflow. Using Pipelines local mode, you can quickly and efficiently debug errors in the scripts and pipeline definition. You can seamlessly switch your workflows from local mode to Sagemaker’s managed environment by updating the session.

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