CCOInsights packages Azure cost and configuration insight into deployable Power BI reports

The deliverable is a set of Power BI Desktop reports

CCO Insights is best understood as a reporting package rather than a service that runs inside your subscription. The project description calls it a set of Power BI Desktop Reports, and the stated purpose is to let monitoring, operation and infrastructure teams gain insight into their existing Azure platform footprint, into resources, and into code contribution characteristics on Azure DevOps and on GitHub. The two audiences named in the documentation are therefore distinct: people who watch a cloud estate for cost and configuration drift, and people who look at where code changes originate. The topic tags reinforce that reading, listing asc, azureadvisor, cloud, dashboard, iaas, microsoft-graph-api, microsoft-rest-api, paas and powerbi. Nothing in the documentation describes a daemon, an agent or a scheduled pipeline that runs on its own, so the artifacts a user ends up with are report files that someone opens and maintains.

Power Query M and DAX do the work over the Azure REST APIs

The mechanism is stated directly in the project description: CCO Insights is developed using Power Query M language and DAX that pulls information directly from different Azure REST APIs. Two layers are therefore doing the work. Power Query M handles the connection and transformation side, reaching out to the Azure REST endpoints and shaping the responses, while DAX provides the measure and calculated column layer that the visuals read from. The API targets named in the topic tags include the Microsoft REST API and Microsoft Graph API, which fits the second half of the stated scope, the code contribution data on Azure DevOps and GitHub. That design has a practical consequence for anyone evaluating it: the reports are only as good as the credentials and the API permissions granted to the Power BI service, and the exact set of permissions is not listed in the README, so it has to be confirmed from the deployment guidance in the wiki.

Deployment guidance is deliberately kept in the wiki

The repository does not contain a self-contained installation path, and the README says so through its links rather than through any command. For introduction and detailed deployment guidance it points at the Wiki, for an overview of capabilities, features and installation steps it points at a set of informational videos hosted at an aka.ms redirect, for contributing it points at the contribution guide, and for new features it points at a Release Notes page in the wiki. It also names a Troubleshooting Guide for deployment problems and directs people to existing GitHub issues before opening a new one. So the first real use is not a command you run, it is a read of the wiki pages followed by the steps described there, with the videos as a walkthrough of the same pages. Anyone planning a deployment should budget for that reading, because the README itself carries no parameter names, connection strings or service principal fields.

The directory layout splits dashboards, queries, install, src and tools

The top level of the repository is where most of the verifiable structure sits. Alongside the README, LICENSE, CONTRIBUTING.md, CODE_OF_CONDUCT.md, SECURITY.md and SUPPORT.md there are five working directories: dashboards/, queries/, install/, src/ and tools/, plus docs/, .github/, .gitignore and a .dccache file. The names line up with the described architecture. dashboards/ is where the Power BI report artifacts live, queries/ where the Power Query M and DAX definitions belong, install/ where deployment files belong, and src/ and tools/ for the auxiliary code that supports the reports. The README does not describe the contents of those directories, and the documentation for how they fit together is the wiki rather than the repository, so the layout is best read as an indication of scope rather than as an interface you can rely on.

The primary language field does not match the code anyone will write

One metadata detail is worth flagging before you start: the repository lists Wolfram Language as its primary language, while the project description says the reports are developed in Power Query M and DAX. The mismatch is a reminder of what this kind of project is. The meaningful code is not in a language with a package index, a test runner and a linter. It is expression language inside a desktop application, and it is evaluated by Power BI rather than compiled and shipped. That has direct consequences for how the work is done. Changes are edits to queries and measures that a desktop tool interprets, they are reviewed as text in a repository but validated by opening a report, and there is no published library API to call from another program. The repository does carry a .github directory and a .dccache file, but the documentation does not describe a CI pipeline that compiles or tests the reports on every change.

Contributions require a CLA, and MIT does not settle the branding question

The project is MIT licensed, and a LICENSE file sits at the repository root, so the code and query text can be reused, modified and redistributed under those terms. Two extra obligations sit on top. Most contributions require you to agree to a Contributor License Agreement, and a CLA bot checks each pull request and decorates it with a status, so a first time contributor has to sign before the change can land. The project also states that it may contain trademarks or logos, that authorised use of Microsoft trademarks is subject to the Microsoft Trademark and Brand Guidelines, and that modified versions must not imply Microsoft sponsorship. The trademark clause is not a formality if you plan to publish a fork under your own brand, because it restricts how the Microsoft name and logos can appear even though the MIT terms are permissive about the code. The project has also adopted the Microsoft Open Source Code of Conduct.

No GitHub releases, so the changelog is a wiki page

The maintenance signals are mixed. The repository is not archived and its last push was on 2026-09-22, so the work is recent rather than abandoned. It has no GitHub releases at all, however, which means there is no tag to pin and no version history in the repository itself. Instead, the README points to a Release Notes page kept in the wiki, so the record of what changed lives outside the version control you would normally rely on. That arrangement has a cost for operators: you cannot diff two versions of a dashboard, you cannot reference a specific release in a ticket, and you cannot tell from the repository alone which build of the reports you deployed. The homepage is a video link rather than a documentation site, and the deployment instructions, troubleshooting guide and contribution guide are all wiki pages, so the operational knowledge for this project is spread across several locations that a team has to bookmark.

Building one report yourself is the alternative to deploying the set

The realistic alternative is not a different product, it is a different scope of work: author your own Power BI report against the same Azure REST APIs instead of deploying this maintained set. The technique is identical in both cases, since both approaches rely on Power Query M for connection and transformation work and DAX for the measure layer. The difference is what you take on. Writing one report yourself means you own the query definitions, the visual design and the refresh behaviour, and you can scope it to the handful of Azure services your team actually cares about. Deploying CCOInsights means you inherit a broader set of reports with a defined structure, plus a troubleshooting guide, a release notes page and a wiki that describes how the parts fit together, but you also inherit the credential requirements, the per-service API permissions and the need to track changes through a wiki changelog rather than through tags. The trade is coverage and supporting documents against control and a smaller surface to maintain.

Editorial conclusion

CCOInsights is worth evaluating for platform teams that want a ready made reporting layer over their Azure estate and can give it an owner who reads the wiki and watches the release notes page. It is the wrong choice if you need a deployable Azure-native monitoring service, since the deliverable is Power BI Desktop reports rather than a resource deployed into the subscription, and the wrong choice for a commercial product that cannot carry the trademark terms or sign the CLA. Verify first that the queries cover the Azure services in your tenant, that the dashboards work against your Power BI Desktop version, and that the CLA is acceptable to your legal team before you invest in deployment.

Frequently asked questions

Official sources

1. Azure/CCOInsights on GitHub
2. Issues
3. License: MIT
4. Project website
5. README