Amazon Cognito now supports recovery method prioritization, making it easier for developers to customize the flow users experience when they forget their passwords. Developers can specify whether they prefer that users receive a recovery code via SMS or email, and whether they would like to fall back to SMS or email if a verified phone number or email address is not available. This feature is available now in Amazon Cognito User Pools at no additional cost.
Amazon Aurora MySQL 5.7 Now Supports Zero-Downtime Patching
Amazon Aurora zero-downtime patching (ZDP), which attempts to preserve client connections through an engine patch, is now supported on Aurora MySQL engine release 2.07 and above. When ZDP executes successfully, application sessions are preserved and the database engine restarts while patching. Read the Aurora documentation to learn more.
Aurora Global Database Supports Multiple Secondary Regions
An Amazon Aurora Global Database is a single database that spans multiple AWS regions, enabling low latency global reads and disaster recovery from region-wide outages. With today’s launch, you can add as many as five secondary regions to your global cluster, expanding the reach of your database worldwide.
AWS launches Tag Policies
Tag Policies is a new feature that allows you to define rules on how tags can be used on AWS resources in your accounts in AWS Organizations. You can use Tag Policies to easily adopt a standardized approach for tagging AWS resources.
Amazon Aurora with MySQL and PostgreSQL Compatibility are now FedRAMP-High Compliant in AWS GovCloud (US)
Amazon Aurora with MySQL compatibility and Amazon Aurora with PostgreSQL compatibility in AWS GovCloud (US) Regions are now compliant with the Federal Risk and Authorization Management Program (FedRAMP) High baseline, which includes over 400 security controls.
AWS Lambda Supports Destinations for Asynchronous Invocations
AWS Lambda now supports Destinations for asynchronous invocations , a new feature that allows you to gain visibility to asynchronous invocation result and route the result to an AWS service without writing code
Amazon RDS for Oracle Now Supports Managed Disaster Recovery and Data Proximity with Cross-region Read Replicas
Starting today, Amazon Relational Database Service (RDS) for Oracle supports Cross-region Read Replicas with Oracle Active Data Guard. Amazon RDS for Oracle makes it easy to create physical standby DB instances in different AWS Regions from the primary DB instance. It fully manages the configuration of Active Data Guard, and replicates data over secured network connections between a primary DB instance and its replicas running across regions.
AWS Serverless Application Repository Adds Verified Author Badges for Application Publishers
Authors who publish serverless applications to the AWS Serverless Application Repository (SAR) and share them publicly can now receive Verified Author badges, enabling consumers to quickly and reliably know who you are. The Verified Author badge will appear next to your author name on your application’s detail card and detail page, and will deep-link to your Github profile.
Amazon ECS Service Events Now Available as CloudWatch Events
Amazon Elastic Container Service (ECS) now publishes ECS Service Action events to Amazon CloudWatch Events. CloudWatch Events delivers a near real-time stream of system events that describe changes in AWS resources. Using simple rules that you can quickly set up, you can match events and route them to one or more target functions or streams, including AWS Lambda for event processing with custom business logic, Amazon Simple Notification Service for automated notifications, or CloudWatch Logs for event logging.
Add ML predictions using Amazon SageMaker models in Amazon QuickSight
You can now preview Amazon QuickSight’s integration with Amazon SageMaker: a new feature that makes it faster, easier, and more cost effective for customers to augment their business data with ML predictions. With just a few clicks, business analysts, data engineers, and data scientists can perform machine learning inferencing in QuickSight to make decisions on new data. Using SageMaker models, popular use cases include predicting likelihood of customer churn, scoring leads conversion, and assessing credit risk for loan applications.