EMR Studio is an integrated development environment (IDE) that makes it easy for data scientists and data engineers to develop, visualize, and debug  big data and analytics applications written in R, Python, Scala, and PySpark. Today, we are excited to announce that EMR Studio is now available in the Europe (Paris), and South America (Sao Paulo) regions.

Amazon Cognito now offers a new console experience that makes it even easier for customers to manage Amazon Cognito user pools and add sign-in and sign-up functionality to their applications. Customers that wish to opt in to the new and streamlined experience can do so by navigating to the Amazon Cognito console.

Amazon Aurora MySQL-Compatible Edition now supports MySQL major version 8.0. MySQL 8.0 includes improved performance functionality from enhancements such as instant DDL to speed up the overall process of creating and loading a table and its associated indexes and SKIP LOCKED and NOWAIT options to avoid waiting for other transactions to release row locks. MySQL 8.0 adds developer productivity features such as window functions to more easily solve query problems and common table expressions to enable use of named temporary result sets. It also includes JSON functionality additions, new security capabilities, and more. MySQL 8.0 on Aurora MySQL-Compatible Edition supports popular Aurora features including Global Database, RDS Proxy, Performance Insights, and Parallel Query.

Starting November 9, 2021, Amazon Rekognition Image APIs pricing has been reduced by up to 38% in all 14 supported regions . This price reduction will automatically reflect in customer bills starting from November 2021.

Today, we are announcing the launch of AWS AppConfig Feature Flags, which will enable you to move faster and safer while releasing new features to your customers. Feature flags allow you to release features to your applications, independent of code deployments. Development teams often coordinate application feature releases along with a large-scale marketing event and are required to release features gradually to the users. Similarly, DevOps teams often respond to operational events by enabling existing functionality in their application. This launch enables Developers and DevOps teams to use AWS AppConfig to create and validate feature flag configuration data and deploy single or multiple features flags to their application in a monitored and controlled way. AWS AppConfig, a feature of AWS Systems Manager, is used as a best practice by thousands of teams within Amazon to deploy feature flags and application configuration changes to applications at run-time.

Today, we are announcing the launch of the Amazon Monitron Web App. The Web App joins the existing Amazon Monitron Android App and iOS App, giving customers more options for using Amazon Monitron. Customers can now use the Amazon Monitron Web App from their desktops, laptops or tablets to monitor equipment and receive reports on operating behavior and alerts to potential failures in those equipment. They can access the Web app in a browser by clicking on the Amazon Monitron project link that can be found on the Amazon Monitron console. To commission the sensors and gateways, users will still need the Amazon Monitron Android App or iOS App since the commissioning process requires their phone’s Near Field Communication (NFC) and Bluetooth (BT) capabilities.  

Amazon Elastic Container Service (Amazon ECS) now supports Amazon ECS Exec for workloads running on Windows operating systems. Amazon ECS Exec, launched in March 2021, makes it easier for customers to troubleshoot errors, collect diagnostic information, interact with processes in containers during development, or get “break-glass” access to containers to debug critical issues encountered in production.

Amazon S3 on Outposts now delivers strong read-after-write and list-after-write consistency for any storage request at no additional cost. 

AWS Glue DataBrew now provides customers the ability to mask Personally Identifiable Information (PII) data during data preparation. With just a few clicks, you can detect PII data as part of a data profiling job and gather statistics such as number of columns that may contain PII and potential categories, then use built-in data masking transformations including substitution, hashing, encryption, decryption, and more, all without writing any code. You can then use the cleaned and masked datasets downstream for analytics, reporting, and machine learning tasks. 

AWS Glue DataBrew now has native console integration with Amazon AppFlow, allowing users to connect to data from Salesforce, Zendesk, Slack, ServiceNow, and other Software-as-a-Service (SaaS) applications, as well as AWS services like Amazon S3 and Amazon Redshift. When creating a new dataset in DataBrew, you can now create a flow via Amazon AppFlow that loads data (by schedule, event, or on-demand) into Amazon S3. Once the flow has been established to Amazon S3, you can easily clean, normalize, and transform this data in DataBrew and join it with datasets from other data stores or SaaS applications. DataBrew also provides information about when your flow was last refreshed and allows you to trigger flows directly from the DataBrew console. Learn more about supported AppFlow sources and destinations here .