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Trace metadata applies to the entire trace. Use it for information that’s constant across spans:
  • Environment — production, staging, development
  • Region — us-west, eu-central
  • Deployment — version numbers, feature flags, A/B test variants
  • Request context — correlation IDs, upstream service info
Set metadata early—ideally where the trace begins—so all spans share the same context.

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Adding Metadata

Set metadata inside an active span context (for example, inside observe() or an @observed function). If you call it outside any span context, it won’t attach to anything. 
import { Laminar, observe } from '@lmnr-ai/lmnr';

await observe({ name: 'processRequest' }, async () => {
  Laminar.setTraceMetadata({
    environment: 'production',
    featureFlag: 'new-algorithm-v2',
    region: 'us-west',
  });
});
See also: Laminar.setTraceMetadata and observe(..., { metadata })

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Notes

  • Setting trace metadata again overwrites the previous metadata—set all keys in one call.
  • Keep metadata JSON-serializable and avoid sensitive data.

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Filtering by Metadata

In the Laminar UI, metadata filters currently match exact key-value pairs (for example, region=us-west).

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Metadata vs Tags

MetadataTags
ScopeEntire traceIndividual spans
FormatKey-value pairsString labels
Best forEnvironment, cohort, request contextCategorization, review labels

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Best Practices

  • Use consistent keys (environment, region, feature_flag).
  • Keep it lightweight and JSON-serializable.
  • Avoid sensitive data (no PII).