Executive Summary
Datastream Analytics maintained rigorous PR practices—100% review coverage, mandatory CI, and thorough QA. Yet production incidents increased 180% year-over-year. Analysis of 1,247 PRs and 43 production incidents revealed that process compliance masked a deeper problem: 12 files (0.8% of the codebase) were responsible for 67% of all incidents, and these files received the least thorough reviews.
The Paradox
By every traditional measure, Datastream's engineering practices looked strong:
- 100% PR review coverage
- Mandatory CI passing before merge
- Dedicated QA environment
- Weekly security scans
So why were production incidents at an all-time high?
Key Finding: Hotspot Concentration
Correlation analysis between file change frequency and incident occurrence revealed a striking pattern:
12 files = 67% of production incidents
These "hotspots" represented only 0.8% of the codebase but generated two-thirds of all production issues. They were changed frequently, poorly understood, and—critically—reviewed superficially.
Change Failure Rate by Module
| Module | Change Failure Rate | % of PRs | Risk Level |
|---|---|---|---|
| Payment Processing | 23% | 8% | Critical |
| API Gateway | 18% | 12% | High |
| Data Pipeline | 15% | 6% | High |
| Core Domain | 4% | 31% | Low |
| UI Components | 2% | 43% | Low |
The payment processing module had a 23% failure rate—nearly 1 in 4 changes caused issues in production. Yet these PRs received the same level of review as low-risk UI changes.
Review Depth Analysis
| Metric | Hotspot Files | Other Files | Gap |
|---|---|---|---|
| Avg Comments per PR | 0.8 | 2.4 | -67% |
| Avg Review Time | 8 min | 22 min | -64% |
| Reviewers per PR | 1.2 | 1.8 | -33% |
The most critical code received the most superficial reviews. Why? The same 3 developers owned these modules and reviewed each other's work—creating blind spots where institutional patterns went unquestioned.
Results After Intervention
| Metric | Before | After (3 months) | Change |
|---|---|---|---|
| Production Incidents/Month | 14.3 | 4.1 | -71% |
| Change Failure Rate (overall) | 18% | 4.2% | -77% |
| Hotspot Coverage (reviewers) | 1.2 | 3.4 | +183% |
| Review Depth (comments/PR) | 0.8 | 3.1 | +287% |
Targeted interventions—hotspot alerts, mandatory cross-team review, and focused refactoring—reduced incidents by 71% in three months.