This page pulls together the measured benchmark snapshot, release checklist, rollback path, and operator-facing UX controls used to run OffGridFlow. Benchmark figures below come from the latest documented benchmark run on December 5, 2025 in a controlled Docker Compose environment.
18 ms
Health endpoint p95
Target < 50 ms
78 ms
Auth p95
Target < 100 ms
156 ms
Emissions calc p95
Target < 200 ms
780 ms
Report generation p95
Target < 1000 ms
58 ms
Database query p95
Target < 100 ms
99.8%
Overall success rate
14,275 / 14,300 requests
1. Benchmark Snapshot
Latest documented test configuration: 10 workers, 60-second duration, 100 RPS target for the main workload.
Workload
Total requests
Success
Avg latency
p95
Throughput
Health endpoint
500
100%
12 ms
18 ms
50.2 RPS
Authentication API
3,000
99.9%
45 ms
78 ms
99.9 RPS
Emissions calculation API
6,000
99.8%
85 ms
156 ms
99.8 RPS
Report generation
300
99.3%
450 ms
780 ms
9.93 RPS
Database query load
4,500
99.8%
32 ms
58 ms
149.7 RPS
Capacity model from the same benchmark set: API target 1,000 RPS, web target 500 to 1,000 concurrent users, and worker target 50 batch jobs per hour per baseline replica set.
2. Release Discipline
Major releases follow a written pre-deployment, deployment, and post-deployment checklist.
✓Run backend, frontend, integration, and security checks before major release.
✓Execute migrations first, then roll out API, worker, and web services with rollout status checks.
✓Run smoke tests and live health checks after deploy, then monitor error rate and p95 latency for two hours.
Monitoring window after deployment: error rate < 1%, p95 latency < 500 ms, database connections < 80% of max, no unexpected alerts firing.
3. Rollback and Recovery
Recovery targets are documented and rollback steps are explicit rather than ad hoc.
✓Roll back API, worker, and web deployments with rollout undo.
✓Verify rollback health before considering database rollback.
✓If schema change is implicated, roll back one migration step and re-check service health.
✓Continue monitoring for 30 minutes and run a post-incident review.
RTO
4 hours
RPO
1 hour
4. Accessibility and Dense Workflow Evidence
The operator-facing application is designed for keyboard, assistive technology, and high-density data work.
Dashboard keyboard navigation coverage exists in Playwright workflow tests.
Dynamic chart components expose aria-label, aria-labelledby, and aria-describedby metadata.
Dialogs use role="dialog" and aria-modal="true"; error states use aria-live alert regions.
Loading states, focusable controls, and dense tables are exercised in end-to-end flows.
5. Operational Caveat
The benchmark figures on this page are the latest documented internal measurements, not a public third-party attestation. They are published to show actual performance envelopes, targets, and release controls without overstating certification or uptime claims.