Insights

The insights section of the dashboard provides a comprehensive overview of key metrics and trends derived from your data. It includes visualizations such as the time that it takes to land code in production and meta data derived from your data.

For example, you can track metrics like Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Recovery (MTTR). These insights help you understand the efficiency and effectiveness of your development and deployment processes. Those come from your pipelines. However, pairing index comes from your git history, from the source code.

The dashboard tab also shows recommendations. Recommendations combine target values, metric thresholds, and the selected filters to highlight actions worth investigating. Each recommendation links to the relevant dashboard section while preserving filter context.

Summary cards

The Insights tab includes three summary cards:

• Pairing Index: percentage of analyzed commits with co-authors, plus paired commit count.
• Pipeline Runs: total runs, success, in-progress, queued, and first/last data frame.
• Pull Requests: total PRs, merged, closed, open, and first/last data frame.

The status values in the Pipeline Runs and Pull Requests cards link to the related dashboard page with matching filters applied.

Deployment Frequency

Works with:

GitHub

Deployment Frequency measures how often code is deployed to production. A higher deployment frequency indicates a more agile and responsive development process.

The deployment frequency is calculated by dividing the number of deployments by the number of deployments in a given time period. To track the deployment frequency, Smm requires a pipeline that deploys to production.

This is configured in the configuration file. You need to specify the pipeline and the job that deploys to production.

In the dashboard, deployment frequency can show multiple configured deployment targets. Use the target toggles to hide or show individual deployment pipelines and jobs. The chart also provides Show all and Hide all actions when multiple targets are available.

Pairing index

Works with:

GitHubGitLabBitbucketany git based repository

The Pairing Index provides insights into collaboration within your development team by analyzing how often developers work together on code changes. A higher pairing index suggests a more collaborative environment, which can lead to improved code quality and knowledge sharing.

Dashboard filters

Insights supports global date filters and uses pipeline, pull request, and source-code filters when building recommendations and summary cards.

Dashboard filter	Backend query parameter
startDate	start_date
endDate	end_date
timezone	timezone

The shared date picker, timezone behavior, saved views, and tab navigation are documented in Dashboard.