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Use case (anonymized)

Asset Performance Monitoring

A monitoring program to make telemetry usable for operations: clean signal modeling, stable definitions, and an incident posture that reduces noise while preserving safety.

Executive summary

  • Business goal: detect performance and reliability drift earlier, with clearer ownership.
  • Approach: telemetry modeling plus a signal strategy aligned to action paths.
  • Outcome: fewer noisy alerts and faster diagnosis when incidents occur.

Business context

  • Telemetry existed but was not standardized across teams and assets.
  • Operations could not tell which alerts were actionable vs informational.
  • Root-cause analysis required manual stitching across dashboards.

What we delivered

  • Telemetry contracts and event standards for key asset classes.
  • Operational models: health states, drift, and exception taxonomy.
  • Dashboards designed for diagnosis, not reporting.
  • Runbooks and ownership mapping tied to alert routes.

Technical approach

Telemetry sources Sensors · Logs · Events Contract gates Validation · Versioning Normalization Enrichment · Units · Semantics Health models States · Drift · Exceptions Ops surfaces Dashboards · Alerts · On-call views Runbooks + evidence Ownership · Actions · Postmortems

How it holds up in production

  • Schema evolution through contract gates and review workflows.
  • Signal strategy built around “what to do next”.
  • Drift signals to catch slow degradation before incidents.
  • On-call posture: ownership routing and runbook clarity.