Commits Metric

Definition

Commits measures the total number of commits made within the selected time range.

It reflects commit activity across the selected repositories and filters.

How the Metric Is Calculated

• Commits is calculated as:
  Total number of commit events within the selected time range
  In the dashboard, this value is normalized as: Commits per day
  The headline value represents: Total commits ÷ Number of days in the selected time range
  This normalization allows comparison across different time ranges.

How the Metric Is Displayed in the Dashboard

The metric card displays two types of values:

1. Headline Value (e.g., 70.21 commits per day)

The large number shown at the top represents the average number of commits per day across the selected time range.

This is a daily average — not a total count.

2. Time-Based Values in the Chart

The line chart shows the total number of commits per time bucket (for example, per day).

Each point represents: The total number of commits within that specific time bucket

Clicking a point displays:

• The total number of commits on that date

Daily bucket values do not average to produce the headline; the headline is calculated independently across the full selected range.

• Consistent commit patterns correlated with stable delivery schedule.

Why This Metric Is Useful

Commits provides visibility into:

• Development activity cadence
• Work segmentation patterns
• Team workflow intensity

Sustained increases may indicate:

• Active feature development
• Incremental development practices
• Increased team capacity

Sudden spikes may indicate:

• Bulk merges
• Automated commits
• Repository migrations

How to Interpret Commits

Commits measures activity frequency, not impact.

It should be interpreted alongside:

• Code Changes
• PRs Opened
• PR Size
• Cycle Time

High commit counts do not necessarily indicate high productivity or value delivered.

Context matters — commit granularity varies by team and workflow style.

Data Sources

Derived from:

• Repository commit history
• Branch inclusion/exclusion rules
• Repository-level filters

Tunable Configurations

Commits may be influenced by:

• Repository filters
• Branch inclusion/exclusion rules
• Service accounts or automated commit filters
• Minimum commit thresholds

Limitations

• Measures frequency, not complexity.
• Large commits and small commits are weighted equally.
• Automated or CI/CD commits may inflate counts.
• Does not measure review quality or delivery success.
• Small datasets may produce volatility.

Commits reflects activity volume, not delivery impact.

Stakeholder Use Cases

Engineering Managers

• Monitor workflow cadence.
• Detect abnormal activity patterns.

Team Leads

• Track commit frequency trends across sprints.

Developers

• Understand contribution cadence.

Product Leadership

• Monitor development intensity relative to roadmap phases.