You can now use AWS PrivateLink to privately access the Amazon RDS Application Programming Interface (Amazon RDS API) for Amazon RDS from your Amazon Virtual Private Cloud (Amazon VPC) without using public IPs, and without requiring the traffic to traverse across the Internet.
Amazon ECS announces AWS Copilot, a new CLI to deploy and operate containers in AWS
Today, Amazon Elastic Container Service (ECS) announced AWS Copilot, a command line interface tool that helps customers develop, release, and operate containerized applications on AWS. With a single command, AWS Copilot creates all infrastructure and artifacts required to run production-ready service on Amazon ECS and AWS Fargate, including task definitions, image repositories, and AWS resources like load balancers, deployment pipelines. With AWS Copilot, users can focus on developing their applications rather than setting up infrastructure.
AWS RoboMaker releases rosbag upload cloud extension for Robot Operating System (ROS)
AWS RoboMaker, a service that makes it easy to simulate and deploy robotics applications at cloud scale, today announced the S3 rosbag cloud extension for ROS Kinetic and Melodic distributions. This new cloud extension enables customers to easily configure and record data from robots as rosbags, and upload them to Amazon S3, which they can later use to analyze events, troubleshoot existing applications, and provide as inputs to AWS RoboMaker log-based simulation for regression testing.
Amazon Fraud Detector Preview launches normalized model scores
We are excited to announce the launch of normalized model scores in Amazon Fraud Detector (Preview). Customers use scores to sideline high risk events, while allowing low risk events to pass with no friction. Prior to this launch, score distributions could shift between models, forcing customers to manually analyze the distributions and update their business logic (e.g. rules) to account for these shifts.
Support for X-Forwarded-For (XFF) header is now available for AWS WAF
AWS WAF now supports inspecting the X-Forwarded-For (XFF), True-Client-IP, or other custom header that includes the originating IP address of a client connecting to your application through an HTTP proxy or a third-party CDN. With this feature, you can reference these headers to write rate-based rules, geographic match rules, or IP match rules, allowing you to take action on IPs that are found within these headers. Both IPv4 and IPv6 addresses are supported.
AWS IoT Core now supports multiple shadows for a single IoT device
AWS IoT Core is announcing a new feature called named shadow, which allows you to create multiple shadows for a single IoT device. A device’s shadow is a JSON document that is used to store and retrieve state information for a device.
AWS WAF Security Automations now supports WAFv2 API
We’re excited to announce that we’ve updated AWS WAF Security Automations, a reference implementation that makes it easier for customers to configure WAF rules to protect web applications running in AWS.
Amazon Comprehend launches real time Custom Entity Recognition
Amazon Comprehend now supports real time Custom Entity Recognition. You can use the real time Custom Entity Recognition to identify terms that are specific to your domain in real time. For example, you can instantly extract product names, financial entities or any term relevant to you from unstructured text documents. Prior to this launch, Custom Entity Recognition identified business-specific entities in text documents asynchronously. Now, customers can choose real time or asynchronous Custom Entity Recognition depending on their use case.
AWS IoT SiteWise is now generally available
Today, we are announcing the general availability of AWS IoT SiteWise, a managed service that makes it easy to collect data from your industrial equipment, model your physical assets, processes and facilities, quickly compute common industrial performance metrics, and create fully managed web applications to help analyze industrial equipment data, prevent costly equipment issues, and reduce production inefficiencies.
Amazon Forecast now supports resource tagging
Amazon Forecast is a fully managed service that uses machine learning (ML) to generate accurate forecasts without requiring any prior ML experience. Amazon Forecast can be used in a wide variety of use cases, including product demand forecasting, inventory planning, workforce planning and cloud infrastructure usage forecasting.