WorkflowsguideNovember 24, 20256 min read

Track Maintenance Metrics That Actually Matter

Measure AI-powered code maintenance effectiveness with the right metrics. Learn what to track, how to track it, and how to use metrics to improve your AI maintenance workflow.

What gets measured gets managed. Without metrics, maintenance is faith-based: you hope code is healthy, believe things are improving, trust that effort is well-spent. With the right metrics, maintenance becomes data-driven: you know the current state, see trends over time, and prove the value of maintenance investment.

The key is measuring what matters, not just what's easy to measure.

Why Metrics Matter

Metrics enable better decisions.

Visibility

Know the current state:

@devonair show current code health metrics

You can't manage what you can't see.

Progress Tracking

See improvement:

@devonair show maintenance trends over time

Are we getting better?

Resource Justification

Prove value:

@devonair show maintenance ROI metrics

Justify continued investment.

Focus

Prioritize effort:

@devonair show where maintenance effort is most needed

Code Health Metrics

Technical Debt

Measure accumulated debt:

@devonair track technical debt metrics:
  - Debt estimate (time to fix all issues)
  - Debt trend (increasing or decreasing)
  - Debt by component
  - Debt age (how long issues have existed)

Code Quality

Measure code quality:

@devonair track quality metrics:
  - Lint violation count
  - Complexity scores
  - Duplication percentage
  - Code smell count

Test Coverage

Measure testing:

@devonair track coverage metrics:
  - Line coverage percentage
  - Branch coverage
  - Coverage trend
  - Coverage by component

Dependency Health

Measure dependencies:

@devonair track dependency metrics:
  - Dependencies out of date
  - Security vulnerabilities
  - Major version behind
  - Deprecated dependencies

Maintenance Activity Metrics

Issue Resolution

Measure fix rate:

@devonair track issue metrics:
  - Issues found per week
  - Issues fixed per week
  - Net change (found - fixed)
  - Backlog size

PR Metrics

Measure maintenance PRs:

@devonair track PR metrics:
  - Maintenance PRs created
  - Maintenance PRs merged
  - Time to merge
  - PRs stuck in review

Automation Effectiveness

Measure automation:

@devonair track automation metrics:
  - Auto-fixed issues
  - Auto-fix success rate
  - Manual interventions required

Time-Based Metrics

Detection Time

How fast are issues found?

@devonair track detection time:
  - Time from issue introduction to detection
  - Goal: detect within hours, not weeks

Resolution Time

How fast are issues fixed?

@devonair track resolution time:
  - Time from detection to fix
  - Time by severity level
  - Time by issue type

Review Time

How fast are maintenance PRs reviewed?

@devonair track review time:
  - Time to first review
  - Time to approval
  - Time to merge after approval

Cycle Time

End-to-end time:

@devonair track cycle time:
  - Time from issue creation to merge
  - Full maintenance lifecycle

Trend Analysis

Direction

Are things improving?

@devonair show trends:
  - Code health: improving ↑
  - Tech debt: decreasing ↓
  - Test coverage: increasing ↑
  - Security issues: decreasing ↓

Velocity

How fast are we improving?

@devonair show velocity:
  - Issues resolved per week
  - Debt reduced per month
  - Coverage added per sprint

Comparison

Compare to baseline:

@devonair compare to baseline:
  - Code health vs 3 months ago
  - Code health vs last year
  - Code health vs target

Team Metrics

Contribution

Who's helping with maintenance?

@devonair track contributions:
  - Reviews by team member
  - Fixes by team member
  - Maintenance PRs merged

Workload

Is maintenance distributed fairly?

@devonair track workload:
  - Reviews per person
  - Issues assigned per person
  - Balance across team

Capacity

How much can the team handle?

@devonair track capacity:
  - Maintenance throughput
  - Sustainable pace
  - Bottlenecks

Repository Metrics

Per-Repository Health

Compare repos:

@devonair show health by repository:
  - Healthiest repositories
  - Most problematic repositories
  - Repositories improving
  - Repositories declining

Hot Spots

Where are problems concentrated?

@devonair identify hot spots:
  - Files with most issues
  - Components with most debt
  - Areas needing attention

Business Impact Metrics

Incident Connection

Connect to incidents:

@devonair track impact:
  - Incidents related to code quality
  - Incidents prevented by maintenance
  - Time saved by early detection

Velocity Impact

Connect to development speed:

@devonair track impact:
  - Time saved by automation
  - Development velocity changes
  - Onboarding time changes

Reporting

Dashboards

Real-time visibility:

@devonair maintain dashboard showing:
  - Current health status
  - Recent activity
  - Trending metrics
  - Alerts and attention needed

Regular Reports

Periodic summaries:

@devonair generate reports:
  - Daily: critical issues and activity
  - Weekly: trends and summary
  - Monthly: comprehensive review
  - Quarterly: strategic assessment

Stakeholder Reports

Communication:

@devonair generate stakeholder reports:
  - Executive summary (high level)
  - Engineering leadership (details)
  - Individual team (their repos)

Setting Targets

Realistic Goals

Set achievable targets:

@devonair set targets:
  - Test coverage: 80%
  - Zero critical security issues
  - Dependencies < 3 months out of date
  - Technical debt decreasing quarter over quarter

SLAs

Define service levels:

@devonair set SLAs:
  - Critical issues: resolved in 24 hours
  - High priority: resolved in 1 week
  - Medium priority: resolved in 1 month

Avoiding Bad Metrics

Vanity Metrics

Metrics that look good but don't matter:

Avoid:
  - Lines of code removed (easy to game)
  - PRs merged (quantity over quality)
  - Issues closed (might just be closing without fixing)

Gaming

Metrics that create bad incentives:

Avoid:
  - Individual rankings (creates competition not collaboration)
  - Pure velocity (speed without quality)

Missing Context

Numbers without meaning:

Always provide:
  - Comparison to baseline
  - Trend direction
  - Context for changes

Getting Started

Define key metrics:

@devonair configure tracked metrics:
  - Code health score
  - Tech debt estimate
  - Issue resolution rate
  - Time to fix

Set up tracking:

@devonair enable metric collection and trending

Create dashboard:

@devonair configure maintenance dashboard

Start reporting:

@devonair configure weekly maintenance report

The right metrics make maintenance visible and improvable. When you can see code health, track trends, and measure improvement, maintenance becomes a manageable engineering discipline rather than an ignored burden.


FAQ

How many metrics should I track?

Start with 3-5 key metrics. More metrics create more noise. Focus on metrics that drive decisions.

How do I handle metrics that make the team look bad?

Metrics are for improvement, not blame. Share metrics as team data, not individual performance. Focus on trends, not absolute numbers.

What if metrics don't improve despite effort?

Re-examine the metrics - are they measuring the right things? Review the effort - is it focused on high-impact areas? Consider whether baseline was accurate.

How often should I review metrics?

Key metrics daily (alerts). Summary metrics weekly. Strategic metrics monthly or quarterly.