Logs
Logs record discrete events and contextual statements whose operational value depends on structure, semantics, correlation, and retention.
Read the page as a transparent path: establish context, inspect the evidence, then test the published stance.
Discrete event evidence
The OpenTelemetry logs data model represents log records with time, observed time, severity, body, attributes, and resource context [1]. Useful logs preserve stable semantics and correlation identifiers while avoiding secrets and uncontrolled high-cardinality fields.
Logs are strongest when a discrete event must be reconstructed. They become weaker when messages are inconsistent, context is missing, clocks diverge, or retention and indexing choices hide the relevant record.
Source record
Bibliography
OpenTelemetry Authors, ‘Logs Data Model.’ [Online]. Available: https://opentelemetry.io/docs/specs/otel/logs/data-model/. [Accessed: Aug. 12, 2026].
Known limits
Unresolved unknowns
- Products differ in event models
- indexing
- retention
- and pricing.
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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