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DevOps data import
eazyBI for Jira

DevOps data import is available starting from the eazyBI version 5.1 (for Jira Server and Jira Data Center).

On this page:

DevOps source data

If you have Bitbucket and Bamboo servers linked to Jira with application links, then in the Jira import Add-ons section you can select the import of DevOps data [1]. In case there are several Bitbucket or Bamboo application links in your Jira instance, you can choose from which server you wish to import the data to eazyBI. Bitbucket and Bamboo project names that match Jira project names will be offered for import automatically. If the names differ, you can search the Bitbucket [2] and Bamboo projects [3] with issue links to projects imported in this eazyBI account. 

Besides the project import, you can specify which issue types are Incidents [4]. Other issue types will be considered to be Change issues in the pre-defined DevOps calculations.

The DevOps data are imported incrementally, and only the new data will be processed with each import. 

If Jira, Bitbucket, and Bamboo do not have common user management, then the user who has authorized eazyBI data import in the account, before importing DevOps metrics to eazyBI, has to go to one of Jira issues and in the development properties section authorize the access by clicking on the Bitbucket / Bamboo property.

To also allow access from Bamboo to Jira, from the Bamboo build screen user has to navigate to the Issue tab and click on Login & approve.


The above actions need to be performed by each user who has authorized import in any account that imports DevOps metrics.

Imported measures and properties

DevOps measures

Issue level metrics will link to the issues that have the issue key specified in Bitbucket Pull Requests or tied to Bamboo Builds/Deployments.

Min and Max values display on issue level finding the pull requests and builds of the issue. The average values show only on the Project level as one pull request can be related to several issues, and several issues can link to one pull request. On the Project level, the average calculation finds the total time as described for each measure and divide it with total pull requests per project.

Build min, max, and avg execution duration

Bamboo build execution time in seconds.

Builds created

Count of Bamboo builds for commits related to the issue.

Deployment min, max, and avg execution duration

Bamboo deployment execution time in seconds.

Deployments created

Count of Bamboo deployments for builds related to the issue.

Pull request min, max, and avg build wait time

The time between pull request closed date and build creation date.

Pull request min, max, and avg deploy wait time

The time between pull request closed date and deployment creation date.

Pull request min, max, and avg development time

The time between the first commit time and pull request creation in Bitbucket.

Pull request min, max, and avg review time

The time between pull request created and closed dates.

Pull requests merged

Bitbucket pull requests merged count. eazyBI imports only those pull requests that have issue key linked to it (either in the title, comment, or in the commit message). In this way, eazyBI can display the pull requests on the issue-level.

DevOps calculated members

Calculated members in Issue type dimension

Change issue typesAll issue types that are not specified as incident issues in the DevOps import screen.
Incident issue typesAn aggregate of all issue types that are defined as incidents in DevOps import screen.

Other pre-defined members in Measures

Average change build lead time

The average time it takes from the first commit until the build completed in Bamboo.

Average change deploy lead time

The average time it takes from the first commit until the deploy completed in Bamboo.

Average Mean Recovery Time

Average resolution days for incidents (issues with pre-defined incident issue types).

Average Mean Time to Change

Average days from issue creation to resolution for issues that are not with Incident issue type.

Build change failure rate %

How often are incidents discovered during build creation? Incidents raised divided by Builds created.

Incidents raised

Issues created in Jira with pre-defined Incident issue types.

Incidents resolved

Jira issues resolved with pre-defined Incident issue types.

Open incidents

Jira open issues with pre-defined Incident issue types.

Hidden dimensions

There are several DevOps data related dimensions that are not visible in the UI. They are listed here so you can use them in the calculations:

  • Pull Request
  • Build Result
  • Release
  • Environment
  • Deployment

Sample reports and dashboard

If you have selected to Import sample reports, eazyBI will create several DevOps report examples in a new folder named Samples DevOps. In this folder, you will find a collection of most essential DevOps metric examples - from Build, Deployment frequency to Change lead time, failure rate, mean time to recovery. The metrics combine from already existing Jira issue data in the cube (Incident and Change issue life cycle) as well as BitBucket and Bamboo data described above. eazyBI will automatically filter the reports to show for the top three projects.

eazyBI also organizes the sample reports in one SampleDevOps metrics dashboard that gives an overview of the DevOps processes in these top three DevOps projects.

Standard DevOps metrics require data of the full request life cycle. For this reason, before version 6.0, eazyBI created Sample reports if both Bitbucket and Bamboo data were available in the cube. 

Starting with eazyBI version 6.0, the DevOps sample report folder contains reports using only Bitbucket data. Still, the DevOps dashboard will be created if there are data for the full request life cycle.

If you would like to customize some reports, then save them and change the name (as eazyBI overwrites the default sample reports during each Jira import).