Metrics
Metrics represent measurements over time and trade event-level detail for efficient aggregation, trend analysis, alerting, and service-level reasoning.
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Efficient measurement over time
The OpenTelemetry metrics model defines metric streams through identifying properties and a sequence of data points [1]. Metrics are efficient for rates, distributions, trends, saturation, and alert conditions when dimensions are controlled.
Aggregation removes detail. A metric can show that behavior changed without preserving the individual event or request that explains why, so investigations often correlate metrics with logs, traces, profiles, changes, and business context.
Source record
Bibliography
OpenTelemetry Authors, ‘Metrics Data Model.’ [Online]. Available: https://opentelemetry.io/docs/reference/specification/metrics/data-model/. [Accessed: Aug. 12, 2026].
Known limits
Unresolved unknowns
- Aggregation temporality and backend semantics can affect portability.
Public review
Discuss and correct
Comments are public. Proposed factual corrections must be incorporated into version-controlled research before they are treated as published.
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