AzureMonitorCommunity, a shared shelf of KQL queries, workbooks and alerts

Three kinds of artifact, one language

The repository holds three kinds of content, and the distinction matters because each is consumed differently. Queries are copy-and-paste Log Analytics queries that you run in your own workspace or against the Log Analytics demo environment hosted at portal.loganalytics.io/demo. Workbooks are the visual layer, and the ones in this repository can be deployed as ARM templates into your own Azure Monitor environment, which is the difference between a screenshot of a dashboard and a dashboard you own. Alerts are log based, and the documentation says so plainly: they are in fact log queries, which means you can run them on the demo environment, or use them to create and test alerts in your own. The common thread is KQL, the Kusto Query Language, and the project points new users at a getting started article for the syntax. The primary language recorded for the repository is PowerShell, which reflects the scripts used to deploy and manage the ARM templates rather than the content itself.

Three organising axes, and why there are three

The directory structure is the design decision worth understanding, because it tells you how the maintainers think about a monitoring query. The Azure Services folder holds queries, workbooks and alerts for specific Azure services, so you can browse by the product you are actually watching. The Scenarios folder holds them to handle common how-to situations, which cuts across services. The Solutions folder organises the same kinds of artifacts by solution rather than by product, which is the most abstract of the three axes and the one that most reflects how an operations team thinks about a problem rather than about a resource type. Reading the same query three ways is a deliberate redundancy, and it means a contributor whose query is about a specific service, a specific task and a specific architecture can place it in more than one home. A reader browsing the repository should use all three, because the same query is likely to appear under different framings.

The demo environment is the evaluation harness

The most useful feature of the repository is that you can test before you adopt. The Log Analytics demo environment is public, and the documentation points at it for both queries and alerts, which turns every artifact into something you can run in a browser in about the time it takes to paste it. For a workbook, the deployment path is an ARM template, so the workbook can be deployed into your own Azure Monitor environment. That is a meaningful difference from a gallery of screenshots, because the template carries the queries, the parameters and the layout together, and deploying it gives you a dashboard whose panel queries you can then edit. The two workbooks highlighted as recent additions show the shape of the content: an AntiMalware Assessment workbook and an Azure Inventory workbook built on Azure Resource Graph, the latter demonstrating that a workbook can query resource metadata rather than logs.

Contributing is deliberately low friction

The contribution rules are stated in one short paragraph and they say something about the intent. Anyone can contribute to the repository, you do not need to be a pro, and the process is the standard one: fork the repo, add your content to your fork and submit a pull request, with the contributing guide linked for details. That framing matters for a repository of this kind, because the scarce resource is not engineering capacity but domain knowledge from people who have debugged a particular problem in a particular Azure service and written down the query that found it. A project that requires a professional background to contribute filters out exactly the people who have the most valuable queries to share. The repository also tracks community participation in a visible way, with a top contributor section each month, and it runs a wiki where the monthly additions are described and where a page collects top asks, ideas about what other users are looking for.

The freshness question, stated honestly

The maintenance record needs a careful reading, because the two signals point in different directions. The last push to the repository was on 2026-08-31, so the content is being touched. But the two published releases are named with numbers rather than versions, 161688 and 161686, both dated 2020-06-23 and both labelled as official Microsoft samples, which suggests the release tags come from an automated pipeline rather than a deliberate versioning scheme. The README also contains a monthly changelog section with a fixed heading about what is new this month and a named top contributor for October, which reads like content that was last refreshed a while ago. The practical implication for a reader is that the structure and the contribution model are current, while individual artifacts are as fresh as their author made them. That is not a criticism of a community repository, it is how this kind of repository works, but it does mean a query you adopt should be tested against your own data before you put an alert on it.

The licence, and one clause about redistribution

The repository is MIT licensed, with the file at the root, which for a collection of queries and templates is the straightforward choice and lets you copy a query into a script or a template into a deployment pipeline without attribution obligations beyond keeping the licence notice. There is one additional instruction that is not a licence term but is worth honouring, and it sits under a heading about redistribution: on redistribution of this repository, please be respectful of the readers and authors of this documentation, and include a link to the original repo master branch. In practice, that is a request to point people at the upstream rather than presenting a fork as the canonical source. A separate SECURITY.md and a CODE_OF_CONDUCT.md sit at the root next to the licence and contributing guide. If you are planning to build a private internal collection by taking this repository as a starting point, that link-back instruction and the MIT terms together mean you have no legal obstacle, and one reasonable social expectation.

What it will not give you

Three limits are worth stating before anyone builds a dependency on this. First, the content is Log Analytics only: the queries, alerts and workbooks are all built on KQL over log and resource data, so if your telemetry lands somewhere else, none of it applies. Second, none of it is a monitoring strategy. A workbook shows you a set of panels, and a log based alert fires when a query returns rows, but the choice of what to watch, which thresholds matter and what constitutes an incident is yours. The repository gives you the plumbing, not the policy. Third, the alerts are queries wearing an alert's clothes, which is convenient for testing and for the demo environment, but it means an alert copied from here inherits whatever assumptions the author made about baseline volume, and a query that is a reasonable diagnostic becomes an expensive or noisy alert in a different subscription. The README itself points readers with questions to the community forum and the FAQ page, which is the right place to sort out that kind of fit before you wire something up.

Editorial conclusion

Adopt this repository as a starting library if you work with Azure Monitor and want proven queries and workbook layouts rather than writing KQL from scratch, and skip it if your environment is not Log Analytics based, since every artifact here is a log query or a wrapper around one. Verify three things before you rely on any of it: that the query you take still returns what it returned when it was written, because the resource schemas and table names in Azure change over time; that the alert rule you copy tests against the demo environment first, since a log based alert is only as good as the query behind it; and that the workbook's queries reference the resources in your own subscription, because the demo environment has a different set of data and a shared one can return nothing rather than an error.

Frequently asked questions

Official sources

1. Issues
2. License: MIT
3. microsoft/AzureMonitorCommunity on GitHub
4. README
5. Releases