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Throughput Metrics in LinearB

Track engineering productivity in LinearB with throughput metrics, including code changes, commits, PRs, and releases, to optimize development velocity and collaboration.

Steven Silverstone
Updated by Steven Silverstone

Throughput metrics in LinearB provide valuable insights into engineering productivity by measuring key activities such as code changes, commits, PRs, and releases. These metrics help teams track development velocity, collaboration, and deployment frequency over a selected time period.

Key Throughput Metrics

Code Changes

  • Measures the total lines of code added or modified by an individual or team.
  • Aggregates changes across all commits within the selected timeframe.

Commits

  • Counts all commits pushed by the team or an individual.
  • Includes commits across all relevant branches and repositories scanned by LinearB, during the selected time frame.

Pull Requests Opened

  • Tracks the total number of pull requests (PRs) created during the selected timeframe.
  • Aggregates data from all repositories connected to LinearB.

Merge Frequency

  • Measures the number of PRs successfully merged by the team or the individual in all the repositories within the timeframe.
  • Indicates how frequently teams integrate completed work into the main branch.

Reviews

  • Tracks the number of code reviews conducted on open PRs by team members in all the repositories scanned by LinearB, during the selected time frame.
  • Helps assess team collaboration and code quality enforcement.

Releases

  • Counts the total number of releases detected by LinearB.
  • Based on LinearB's release detection methodology, across all repositories scanned by LinearB, during the selected time frame.

Why Throughput Metrics Matter

  • Monitor development speed – Understand how quickly teams are coding, reviewing, and merging.
  • Identify process bottlenecks – Spot delays in PR reviews, merges, or releases.
  • Improve collaboration – Track review frequency and code integration rates.
  • Optimize engineering workflows – Use data-driven insights to streamline development cycles.

How did we do?

Sharing LinearB Metrics and Projects

Time Distribution Dashboard in LinearB

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