Phone:400-882-3320
Guance 
Customer context
KONE is a Finland-headquartered elevator and escalator company that also provides maintenance, modernisation, and digital services. The published Guance customer story describes KONE digital workloads on AWS supporting scenarios such as equipment status, people flow, and maintenance services.
As equipment and application data grew, the existing monitoring workflow could not keep cloud resources, application calls, user experience, and logs in one context. Development and operations teams needed a shorter path from a symptom to the affected component and business workflow.
Fragmented data lengthened fault isolation
When an equipment or application issue occurred, teams had to inspect system performance, application behaviour, and logs through separate entry points without a persistent time and resource context.
Implementation
Correlate RUM, APM, and logs
KONE brought RUM, APM, and logs into Guance so responders could move from a user-experience or application symptom to the related request, service, and log evidence without rebuilding context in each tool.
Extend collection and alerts with DataFlux Func
DataFlux Func provided a programmable path for business-specific collection and alert logic, allowing operational data outside standard integrations to enter the same monitoring workflow.
Standardise log parsing, search, and alert context
Once logs entered a shared pipeline, teams could parse and present them for each business scenario, then investigate them alongside application context and alerts.
What changed
AWS runtime state became part of the same view
Metrics from services including EC2, EKS, and RDS could be reviewed with application and log data instead of as a separate infrastructure-only workflow.
Custom telemetry reflected business objects
Teams could supplement standard integrations with scripts that brought equipment or business state into monitoring, alerting, and analysis.
Log analysis retained more incident context
Central collection and parsing made it possible to examine distributed logs with alerts and application traces, reducing repeated searches and manual timeline alignment.
