Case Study: OUI.SNCF achieves real-time visibility and cuts incident resolution to minutes with Elastic (Elasticsearch & Kibana)

Oui.SNCF Visualizing Data to Enhance Sub-Department Efficiency

OUI.sncf, France’s leading online travel and e‑commerce site, serves 13 million monthly visitors, sells 86 million tickets annually and has 15 million mobile app downloads. Rapid growth in infrastructure (from dozens to thousands of servers) created fragmentation, slow log searches and delayed incident resolution, putting QoS, SLAs and commercial responsiveness at risk for both technical teams and sub‑departments.

The Big Data team centralized logs into a Hadoop data lake and deployed the Elastic Stack (Elasticsearch, Kibana, X‑Pack) with Kafka and Flume/NiFi for ingestion, creating 400 dashboards used across 50 projects and training 200 users for autonomous analysis. The dedicated cluster (≈80 TB, ingesting 2 TB/day) delivered real‑time visibility—cutting incident resolution from hours to minutes, enabling automated anomaly and intrusion detection, reducing bot traffic and improving operational and commercial performance while raising the profile of the technical team.

Oui.SNCF

Dominique Debruyne

Head of The Big Data Arm