Source-level metrics tracked

Ingestion logs that lack a source_id dimension tell you what happened but not where. When one source starts producing bad records at scale — malformed emails, duplicate floods, elevated bounce rates — you cannot isolate it without manual log correlation. NIST CSF 2.0 DE.AE-3 requires that event data include enough context for anomaly detection. Missing source dimension in logs means the signal exists but is not actionable without hours of forensic work.

Add source_id and source_type as first-class fields on every structured log emitted during ingestion — both success and failure paths. Use a structured logger (pino, winston) so these fields are queryable in your log aggregation tool.

// Emit on every record processed
logger.info('contact_ingested', {
  source_id:   source.id,
  source_type: source.type,
  contact_id:  contact.id,
  status:      'success',
})

logger.warn('contact_ingestion_failed', {
  source_id:   source.id,
  source_type: source.type,
  reason:      'validation_error',
  error:       err.message,
})

If you use a metrics platform (Datadog, PostHog), emit a counter keyed by source_id to enable dashboards and alerting by source.