How FURUNO Uses Elastic to Cut Vessel Incident Resolution Time by 94%

FURUNO sits at the core of global maritime navigation. The company’s radar, sonar, and satellite communication equipment operates aboard commercial vessels worldwide, and its customers depend on reliable connectivity to coordinate operations at sea. When those connections degraded or data charges spiked unexpectedly, FURUNO needed to understand why.

Before deploying Elastic, diagnosing a vessel connectivity issue was a labor-intensive ordeal. Data retrieval from satellite partners required one to two days at minimum, and in some cases stretched to weeks. Once retrieved, the team faced tens of millions of spreadsheet rows to analyze manually. There was no way to see in real time what devices and services aboard a ship were consuming data, which made it nearly impossible to give customers a precise explanation when bills came in higher than expected.

FURUNO built a monitoring architecture using the Elastic Stack across its fleet. Onboard computers run Logstash and Metricbeat to collect data from firewalls, modems, antennas, and communications equipment. That data is filtered, compressed, and transmitted to shore-based infrastructure, where it is indexed into Elasticsearch and visualized through Kibana dashboards and Elastic Maps. The system currently monitors 30 vessels and processes over 300 million documents totaling approximately 50 gigabytes.

The operational impact was significant. Mean time to knowledge on connectivity issues fell by 94%. The team can now identify and diagnose problems in roughly one hour, compared to the previous one-to-two day baseline. When a vessel detected malware, the Elastic Stack surfaced the incident within an hour. Kibana dashboards give customer-facing teams precise visibility into which devices and services are consuming bandwidth, enabling transparent conversations with clients about usage patterns.

FURUNO plans to expand the deployment to several hundred vessels across Japan and Asia Pacific, with Kibana Spaces enabling customer-facing dashboards and automated usage threshold alerts. The architecture positions the company to monetize its data visibility capabilities as a value-added service, shifting from reactive customer support to proactive fleet intelligence.