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Monitoring data models

Monitoring data models represent the fundamental categories of information used to track the status and performance of software systems^[400-devops-07-monitoring-and-observability.md].

Core Models

Modern monitoring and observability systems are typically built upon four primary data models:

  • Metrics: These are numerical representations of data measured over intervals, used to track the quantitative aspects of a system, such as CPU usage or request latency^[400-devops-07-monitoring-and-observability.md].
  • Logs: These are discrete, timestamped records of specific events or activities that have occurred within the system, providing a detailed audit trail^[400-devops-07-monitoring-and-observability.md].
  • Tracing: Also known as "call chains" (調用鏈), this model tracks the path of a request as it moves through a distributed system, helping to pinpoint where failures or latency occur^[400-devops-07-monitoring-and-observability.md].
  • Health Checks: These are specific signals or endpoints used to determine the current status of a system component, indicating whether it is available and functioning correctly^[400-devops-07-monitoring-and-observability.md].

Sources

  • 400-devops-07-monitoring-and-observability.md