Linear Metric
Issue Tracking
Bug Escape Rate = (Production Bugs / Total Bugs Found) × 100
Bug Escape Rate measures the percentage of bugs that are discovered in production rather than caught during development or QA stages in Linear. It quantifies the effectiveness of pre-release quality gates and testing processes.
LinearIssue TrackingBug Escape Rate
Bug Escape Rate measures the percentage of bugs that are discovered in production rather than caught during development or QA stages in Linear. It quantifies the effectiveness of pre-release quality gates and testing processes.
How to calculate bug escape rate
Why bug escape rate matters for Linear users
Bugs found in production are exponentially more costly to fix than those caught during development. A high escape rate indicates gaps in testing coverage, code review thoroughness, or staging environment fidelity. Reducing this rate directly improves user experience and team efficiency.
For Linear teams, tracking bug escape rate connects quality outcomes to the development process. It provides objective evidence for investing in automated testing, improving code review practices, or strengthening pre-release validation workflows.
Understand and act on bug escape rate with KPI Tree
KPI Tree analyses bug labels and creation context from your Linear data warehouse to classify where bugs were discovered. Place this in your quality tree alongside technical debt and issue reopening metrics.
Assign RACI ownership to quality leads or tech leads. Set alerts when the escape rate exceeds your team's acceptable threshold, triggering a review of quality processes.
Get started with your Linear data
MCPPull metrics from Linear directly through the Model Context Protocol.
Connect your existing warehouse where Linear data already lands.
Our professional services team can build you turn-key AI foundations in a matter of weeks. Data warehouse on Snowflake/BigQuery, ELT with Fivetran, all modelled in dbt with a semantic layer.
Related Linear metrics
Issue Reopening Rate
Issue TrackingMetric Definition
Reopening Rate = (Reopened Issues / Total Completed Issues) × 100
Issue Reopening Rate measures the percentage of Linear issues that are moved back to an active state after being marked as done. It serves as a quality indicator, reflecting whether work is genuinely complete when marked as such.
Technical Debt Accumulation Rate
Issue TrackingMetric Definition
Accumulation Rate = Debt Issues Created − Debt Issues Resolved (per period)
Technical Debt Accumulation Rate measures the net change in technical debt issues in Linear over time. It compares the rate at which new debt issues are created against the rate at which existing debt is resolved, indicating whether overall debt levels are growing or shrinking.
Issue Resolution Time
Issue TrackingMetric Definition
Resolution Time = Issue Resolved Date − Issue Created Date
Issue Resolution Time measures the total elapsed time from when a Linear issue is created to when it is resolved. It encompasses both waiting time and active work time, providing a full lifecycle view of how long issues take to address.
Code Review Bottleneck Analysis
Issue TrackingMetric Definition
Code Review Bottleneck Analysis examines the time Linear issues spend waiting for or undergoing code review. It identifies reviewer capacity constraints, uneven review distribution, and workflow states where issues accumulate, slowing overall delivery throughput.
All Linear metrics
Code Review Bottleneck AnalysisComment Collaboration RateCross-Team Dependency ImpactCycle Burndown RateCycle Commitment AccuracyDeveloper Workload BalanceEpic Completion ForecastingFeature Delivery Cycle TimeIntegration Impact AnalysisIssue Aging AnalysisIssue Priority Distribution AnalysisIssue Reopening RateIssue Resolution TimeLabel Work Classification AnalysisMilestone Delivery PredictabilityProject Health ScoreRoadmap Progress TrackingSeasonal Development PatternsTeam Capacity UtilisationTeam Velocity AnalysisTechnical Debt Accumulation RateUser Story Size ConsistencyWorkflow State Transition AnalysisEmpower your team to understand and act on Linear data
Map what drives your metrics, measure progress at any grain, prove what works statistically, and deliver personalised action plans to every team member.
