6/10/2022, 12:00:00 AM ~ 6/13/2022, 12:00:00 AM (UTC)

Recent Announcements

Amazon Connect forecasting, capacity planning, and scheduling, now available in the Asia Pacific (Sydney) AWS region

Amazon Connect forecasting, capacity planning, and scheduling (preview) are now available in the Asia Pacific (Sydney) AWS region. Machine-learning powered capabilities make it easier for contact center managers to help predict contact volumes and average handle time with high accuracy, determine ideal staffing levels, and optimize agent schedules to ensure they have the right agents at the right time. This helps businesses optimize their operations, meet service level goals, and improve agent and customer satisfaction. Getting started takes just a click, eliminating the need to build custom applications or integrate with third-party products.

Amazon Aurora PostgreSQL supports LO module

Amazon Aurora PostgreSQL-Compatible Edition now supports the Large Objects (LO) module. The LO module provides support for managing Large Objects (also called LOs or BLOBs).

Amazon SageMaker Canvas accelerates onboarding with new interactive product tours and sample datasets

Amazon SageMaker Canvas accelerates onboarding with new interactive product tours and sample datasets for different use cases. Amazon SageMaker Canvas is a visual point-and-click interface that enables business analysts to generate accurate machine learning (ML) models for insights and predictions on their own — without requiring any machine learning experience or having to write a single line of code.

Amazon SageMaker Experiments now supports common chart types to visualize model training results

SageMaker Experiments now supports granular metrics and graphs to help you better understand results from training jobs performed on SageMaker. Amazon SageMaker Experiments is a capability of Amazon SageMaker that lets you organize, track, compare and evaluate machine learning (ML) experiments. With this launch, you can now view precision and recall (PR) curves, receiver operating characteristics (ROC curve), and confusion matrix. You can use these curves to understand false positives/negatives, and tradeoffs between performance and accuracy for a model trained on SageMaker. You can also better compare multiple training runs and identify the best model for your use-case.

Amazon Aurora PostgreSQL-compatible edition now supports zero-downtime patching

Amazon Aurora PostgreSQL-compatible edition now supports zero-downtime patching (ZDP). With ZDP, customers can upgrade to a new PostgreSQL version and apply patches to their Aurora cluster without any downtime.

Amazon AppFlow now supports Salesforce Marketing Cloud as a source

Amazon AppFlow, a fully managed integration service that helps customers securely transfer data between AWS services and software-as-a-service (SaaS) applications in just a few clicks, now supports Salesforce Marketing Cloud as a source. Salesforce Marketing Cloud is a leading marketing automation platform for B2B and B2C customers that helps companies deliver relevant, personalized journeys across channels and devices. With this launch, AppFlow customers can now ingest Salesforce Marketing Cloud data such as Campaigns and Activities into AWS where it may be further analyzed and enriched. With this launch, AppFlow is building upon its existing capabilities for data transfer with Salesforce applications.

Amazon Aurora supports PostgreSQL 13.7, 12.11, 11.16, and 10.21 versions, and updated extensions

Following the announcement of updates to the PostgreSQL database by the open source community, we have updated Amazon Aurora PostgreSQL-Compatible Edition to support PostgreSQL 13.7, 12.11, 11.16, and 10.21. These releases contain bug fixes and improvements by the PostgreSQL community. Refer to the Aurora version policy to help you to decide how often to upgrade and how to plan your upgrade process.

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