This post has been republished via RSS; it originally appeared at: Azure Data Explorer Blog articles.
We are pleased to announce new features in Kusto Explorer (Desktop version of Azure Data Explorer Web UI) to help you be more productive in managing and executing queries
We are pleased to introduce a new usability feature to help you organize your work with queries, increase productivity and improve efficiency.
There are 2 types of Work folders –
- Unsaved Work folder contains open query tabs that you may still be working on for easier navigation
- Tracked Folders are folders from your local machine that you can add as KQL libraries to Kusto Explorer for easy access and management
Query Automation allows you to define a workflow that contains a series of queries with rules and logic that govern the order in which they are executed. Automations can be reused, and users can re-run the workflow, to get updated results. Upon completion, the saved Automation produces an analysis report, summarizing all queries results with additional insights.
Figure 1 below shows an example of a saved Automation that awaits global parameters to run
Figure 2 below is a snapshot of the Automation during execution, where the results of the current query are displayed on the right-hand side of the screen
How to get started?
To create a new Automation in a database, go to Tools --> Add (DatabaseUser and DatabaseAdmin). To open automation, find it in the cluster connection’s Automations folder, and double click it (DatabaseViewer).
When would this be useful?
A common use case for this feature is DevOps incidents investigations. Using Azure Data Explorer as a centralized logging solution to gather and analyze logs, gives DevOps professionals a unified picture of all network activities, resource exhaustion, data inconsistencies and more, making it simpler to detect and resolve problems.
Automation workflow is stored at the database level and can be reused every time an investigation is kicked off. By running the same Automation in Kusto Explorer for every investigation, DevOps teams ensure that all data points are considered and there are no accidental oversights in the process.
You’re welcome to suggest more ideas (for Kusto Explorer and Azure Data Explorer in general) and vote for them here - https://aka.ms/adx.ideas