- Add perf-aggregate-report CI job to analyze variance across releases
- Implement dynamic version discovery using git tags (ever-growing)
- Generate charts via UN sandbox using matplotlib
- Create AGGREGATED-PERFORMANCE.md with comprehensive methodology
- Add Makefile target for local report generation
- Include 3 visualization charts showing variance trends
Key findings: 2-3x performance variance due to orchestrator placement
on CPU-bound pool causing non-deterministic scheduling.
Updates generate-perf-report.sh to produce markdown with:
- Embedded chart images for all 6 visualizations
- Dynamic observations pulled from actual performance data
- Slowest/fastest language names extracted from JSON
- Raw data table at the end
The markdown now matches the manual report format and will be
generated automatically on each tagged release.
- Add scripts/generate-perf-charts.py for matplotlib visualizations
- Update generate-perf-report.sh for versioned directories (reports/TAG/)
- Add make perf-charts and make perf-all targets
- Add GitLab CI perf-report job to auto-commit after tagged releases
- Generated 6 charts for 4.2.0: dashboard, duration, histogram, leaders, etc.
Each release now gets its own reports/TAG/ directory with:
- perf.json (raw timing data)
- perf.md (markdown report)
- chart-*.png (6 visualizations)
