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Santé et Disponibilité

Automated fault recovery, predictive maintenance, and uptime SLA tracking — your chargers fix themselves before drivers notice a problem.

Le Problème

Pourquoi cette extension existe-t-elle ?

A faulted charger is lost revenue and a frustrated driver. The average CPO discovers a charger fault 4-8 hours after it occurs — often from a driver complaint. Manual recovery takes 1-3 days. Meanwhile, the charger sits offline, earning nothing. Automated recovery and predictive maintenance change this equation entirely.

La Solution

Ce que vous obtenez

  • Automated fault recovery pipeline: soft reset, hard reset, unlock connector, escalate — all without human intervention
  • Predictive fault detection: 90-day error pattern analysis with risk scoring per charger
  • Uptime SLA tracking per charger and per location — know your actual uptime vs target
  • Ticketing integration: Zendesk and Jira — automatic ticket creation when automated recovery fails
  • MTTR (Mean Time To Recovery) analytics — measure and improve your recovery performance
  • OpenTelemetry distributed tracing for deep technical observability
  • Prometheus metrics endpoint — export to Grafana for custom dashboards
🎯 Pour qui est-ce ?

Any CPO managing physical chargers — especially operators with 10+ chargers, those with SLA commitments, or operators in regulated markets with uptime requirements.

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Capacités Clés

Tout inclus

Automated Recovery

Soft reset, hard reset, unlock connector. The system tries every recovery option before escalating to a human. Most faults resolved in under 5 minutes.

Predictive Maintenance

L'analyse de patterns d'erreur sur 90 jours attribue un score de risque à chaque chargeur. Chargeur 42 : 78% de probabilité de panne dans 7 jours - planif

Uptime SLA Tracking

Track actual uptime per charger and per location. Compare against your SLA targets. Identify chronic underperformers.

Auto-Ticketing

When automated recovery fails, a Zendesk or Jira ticket is created automatically with full fault context. Technician dispatched with all the information they need.

MTTR Analytics

Track Mean Time To Recovery over time. See whether your recovery performance is improving. Benchmark against industry standards.

Prometheus and Grafana

Export metrics to Prometheus and visualise in Grafana. Build custom dashboards for your operations team.

Cas d'Usage Réels

Voyez-le en action

Comment les opérateurs du monde entier utilisent cette extension pour résoudre des vrais problèmes et développer leur activité.

Charger fault resolved in 4 minutes without human intervention
Charger CP042 reports ConnectorLockFailure at 2:17 AM. The system attempts a soft reset — fails. Hard reset — succeeds. Charger back online at 2:21 AM. Total downtime: 4 minutes. No technician called. No driver complaint.
Predictive maintenance prevents breakdown
The system flags Charger 17: PowerSwitchFailure errors increasing — 82% failure probability in 5 days. The operations manager schedules a maintenance visit. The technician finds a failing relay and replaces it. The charger never goes offline.
MTTR improves from 4.2 hours to 47 minutes
A CPO enables automated recovery across 80 chargers. Over 3 months, MTTR drops from 4.2 hours (manual process) to 47 minutes (automated recovery plus auto-ticketing). Uptime improves from 94.2% to 98.7%.
Étude de Cas

UK CPO improves uptime from 94% to 98.7% with automated recovery

A UK CPO operating 120 chargers across 15 locations was manually responding to faults — average MTTR was 4.2 hours. Many faults occurred overnight and were not discovered until morning. After enabling Health and Uptime with automated recovery, 73% of faults are resolved automatically in under 10 minutes. MTTR dropped to 47 minutes. Network uptime improved from 94% to 98.7%.

98.7%
Network uptime
47 min
Average MTTR
73%
Faults auto-resolved
-89%
MTTR improvement

Stop losing revenue to charger downtime.

Parlez à notre équipe et voyez cette extension en action avec une démo personnalisée.