Modern networks generate huge amounts of operational data. Observability attempts to turn that data into understanding, so you can diagnose issues, explain behavior, and improve reliability.
In practice, observability helps teams answer: - What changed? - Where did it happen? - Why does it matter? - What should we do next?
In most modern environments, observability relies on three core telemetry types:
Metrics: measurements over time (latency, utilization, error rate)
Logs: event records with detail and context
Traces: end-to-end paths across services
Monitoring typically tells you if something is wrong using predefined thresholds.
Observability helps you explain why something is wrong, even in complex, dynamic environments, by correlating telemetry with context.
For CSPs, MSPs, enterprises, satellite operators, and AI clouds, the “network” isn’t just connectivity anymore, it’s all about customer experience.
Users don’t experience “network health.” They experience whether the apps they care about work.
That’s why observability must evolve from collecting data to delivering experience, context, and action.
Once you can explain what’s happening, you can do more than traditional tools: