1. What type of reports can I create with Reporting for Confluence Cloud?

You can create live reports/dashboards. We call them live reports because these reports surface the latest version of your data and metadata and always reflect the latest changes.

2. What are the app's main components?

Reporting for Confluence cloud has three main components:

  • Fetching the raw data (via Confluence API using CQL and Expansions)

  • Transform the data/ metadata and refine the results (manipulate the returned raw JSON to produce readable data)

  • Format the information and turn it into insights (via the report builder)

3. How does the app work?

Reporting relies on CQL (Confluence Query Language) to fetch the data and metadata via Confluence API from the surface and depth of your Confluence and then transform the data into actionable insights. And at the last stage, format it in an intuitive structure that is digestible for any audience.

4. Do I need to have any technical background to work with the app?

Not at all, as the app is geared with a “Recipes” feature that allows you to import/ export your recipes. Our team has been curating different scenarios in recipe format. You can easily copy these recipes from our documentation site here. Having a basic understanding of writing a CQL syntax for more advanced users helps to get more value quicker. We have documentation and tutorials that can help you grasp the main concepts and build your custom reports/ dashboards.

5. How does the cloud version of the app differ from the server or Data Center(DC) version?

  • While both apps try to address the same problem, reporting for Confluence cloud uses CQL to obtain the raw data/ metadata from Atlassian APIs. In contrast, the Server/DC version has direct access to the Confluence on-prem database, which makes the data-acquisition stage a bit different in both the areas below:
    • the format of the raw response 
    • the limitations tied to the API response (Currently, Confluence API has a memory cap of 10MB.)
  • Reporting server/ DC version allows you to build infinite combinations of different macros and suppliers, including via nesting of macros; unfortunately, this ability is unavailable on the Confluence cloud platform as Atlassian has restricted the use of nesting macros to ensure the performance of sites. (See CONFCLOUD-68323
  • If you’ve had experience with the server/DC version of Reporting, you would know that it takes a considerable amount of time and expertise to build sophisticated reports and dashboards. You would need to learn and understand dozens of different macros, and suppliers and how to connect them. In Reporting for Confluence cloud, we redesigned the entire experience to allow report-builders, to structure their entire reports in one unified macro. All data points are represented with Report Blocks which are later wrapped in one of the predefined formats (table, list, paragraphs), ready to be added to your pages.

6. Can I use my existing reports built on my Confluence Server?

Unfortunately, no. Due to the drastic differences between the two platforms and how the underlying technologies differ, there is no out-of-the-box way to port your existing reports from server to cloud. This, however, may change in the future. For now, our Services team can help you navigate and prepare your organization for Cloud Migration for the time being. You can contact our Services team here.

7. Can I migrate my existing reports built on Reporting for Confluence (Server) when I migrate my spaces from Confluence Server to Confluence Cloud via Atlassian Confluence Migration Assistant?

Unfortunately not, due to drastic differences between the two platforms and how the underlying technologies differ, there is no out-of-the-box way to port your existing reports from server to cloud. This may change in the future. For the time being, our Services team can help you navigate and prepare for Cloud Migration. You can contact our Services team here.

8. Are there any limitations when working with the Confluence API?

The Confluence CQL API is powerful and robust, and it uses GraphQL structure, so it is efficient and allows you to fetch multiple data points in the same call. Currently, the only limitation is an API memory cap of 10MB. Based on our initial tests, most use cases won’t run into any issues with this cap.