Azure Automation is now available in the Azure UK and West Central US regions. These new regions give you more options for locating Automation accounts in geographic locations that work best for you.
You can use Azure Automation to create, monitor, deploy, and maintain resources in your Azure, on-premises, and third-party cloud environments, by using highly scalable and reliable process execution and desired state configuration engines.
In a post, Microsoft explains how to enable Azure resource metrics logging using a script that allows users to enable metrics logging for PaaS resources at a the level of a subscription or resource group.
“This native metrics logging capability and OMS monitoring enable customers to monitor Azure Resources at scale,” wrties the team, for example, “you can now use OMS to monitor hundreds of thousands of SQL Azure databases in one OMS workspace.”
Azure Platform as a Service (PaaS) resources, like Azure SQL and Web Sites (Web Apps), can emit performance metrics data natively to OMS. Today, there is no way to enable metrics logging for PaaS resources through the UI. Therefore, “customers need to use a PowerShell script,” says azure team.
Make sure that you have the following AzureRM modules installed on your workstation before you begin: “Insights, OperationalInsights, Resources, and AzureRM.profile.”
In other news today, the ASTrace utility that provides the ability to capture an Analysis Services trace and log it into a SQL Server table is now available on Git repo. The table can be queried later or read using SQL Server Profiler.
“The ASTrace utility runs as a Windows service that connects to Analysis Services, then creates a trace, and logs trace events into a SQL Server table using the SQL Server Profiler format. The ASTrace utility creates the trace using a standard trace template that you can author using SQL Server Profiler,” Microsoft explained.
Get the ASTrace in the Analysis Services Git repo.
“The Automated Partition Management for Analysis Services Tabular Models whitepaper is available today, describes ‘how to use the AsPartitionProcessing TOM code sample with minimal code changes.”
The sample, “Is intended to be generic and configuration driven, Works for both Azure Analysis Services and SQL Server Analysis Services tabular models, Can be leveraged in many ways including from an SSIS script task, Azure Functions and other.”
Analysis Services tabular models can store data in a highly-compressed, in-memory cache for optimized query performance. This provides fast user interactivity over large data sets.
“Large data sets normally require table partitioning to accelerate and optimize the data-load process. Partitioning enables incremental loads, increases parallelization, and reduces memory consumption. The Tabular Object Model (TOM) serves as an API to create and manage partitions. TOM was released with SQL Server 2016 and is discussed here. Model Compatibility Level 1200 is required,” Microsoft writes.
The following list shows some of the many options available with Azure Functions.
- Scheduled using a Timer function CRON expression. In this case, it is not necessary to set up a separate scheduling system.
- Using a webhook request for a WebHook function, or an HTTP request for an HttpTrigger function. This allows integration with existing scheduling systems that can call a URL.
- Triggered from Azure Queue using built-in integration points in Azure Functions.
Automated Partition Management for Analysis Services Tabular Models whitepaper is availabel HERE.