Azure updates
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October 2019
Updates to Azure Monitor for virtual machines (preview) before general availability release
Updates to Azure Monitor for virtual machines (preview) will be launched in mid-November, 2019, ahead of the general availability (GA) release.
Azure IoT Central is now available in Asia Pacific
Azure IoT Central is now available in Asia Pacific geographies.
OMS Agent for Linux October release is now available
Target availability: Q4 2019
The OMS Agent for Linux October 2019 release is now available. This release contains many stability and reliability improvements.
Azure Stream Analytics is now available in France Central region
Customers can now use Azure Stream Analytics in the France Central region.
Azure Stream Analytics is now available in Korea Central
Azure Stream Analytics is now available in the Korea Central region.
Azure Stream Analytics is now available in US GOV Virgina region
Eligible customers can now use Azure Stream Analytics in the US GOV Virginia region.
Service-aided subnet configuration for managed instance in Azure SQL Database is now in preview
Managed instance, a deployment capability of Azure SQL Database, is transitioning from a manual to service-aided subnet configuration, now in preview.
Key Vault references in App Service and Azure Functions are now available
Introduce secrets management into your apps without code changes using Key Vault references.
Upcoming changes for Service Map data stored in Log Analytics
Updates for Service Map are coming that will change where we store some of our data in Log Analytics. These updates should be completed sometime in November, 2019.
Azure Analysis Services QPU AutoScale is now available
Azure Analysis Services QPU AutoScale enables automatic customizable scaling for AAS instances.
Execute Azure Machine Learning service pipelines in Azure Data Factory pipelines
You now have the ability to run your Azure Machine Learning service pipelines as a step in your Azure Data Factory pipelines. This allows you to run your machine learning models with data from multiple sources (more than 85 data connectors supported in Data Factory).
Azure Data Factory—Mapping Data Flows is now generally available
Target availability: Q4 2019
Mapping Data Flows is now generally available. This new capability brings code-free visual data transformation to Azure Data Factory without the need to build transformation logic in external execution engines using custom code.
Introducing new Azure Resource Graph functionality – Track changes to your resource properties
An update to the Azure Resource Graph API allows you to see the type of change to the resource (Create, Update, or Delete) and the breakdown of the properties that changed, including their before and after values.
Azure Sphere 19.09 release adds new use cases for enterprise customers
Update 19.09 for Azure Sphere public preview now available in Retail feed
Azure Application Insights is now available in the Brazil South region
Azure Application Insights is now generally available in the Brazil South region.
Azure Monitor Log Analytics retention is now configurable by data type
Target availability: Q4 2019
Data retention in Azure Monitor Log Analytics can now be configured for each data type, rather than only a single retention setting for the entire workspace.
Private Preview - Azure Spring Cloud service
Simplify Spring Boot based microservices development and application lifestyle management.
New reference data options in Stream Analytics—SQL Managed Instance and SQL Server on VM
Target availability: Q4 2019
It's now possible to configure an Azure SQL Database Managed Instance or even a SQL server running on a virtual machine as a reference data input for you Stream Analytics job.
Azure DNS private zones is now generally available
Announcing general availability of Azure DNS private zones. This is a production ready release containing several bug fixes and removes restrictions that public preview had.
New output options in Azure Stream Analytics—SQL Managed Instance and SQL Server on VM
It’s now possible to configure an Azure SQL Database Managed Instance or even a SQL server running on a virtual machine as an output in your Stream Analytics job.
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