Travel Observability, Trace and Correlation Model
Trace travel transactions from search through booking and servicing using correlation IDs, distributed traces, metrics and structured domain events.
Observability in travel is more than HTTP latency charts. The goal is to follow the evidence chain from a search request through confirmed booking, payment and servicing outcomes.
Correlation chain
Travel transaction correlation chain
Identity layers
Preserve trace ID, search ID, offer ID/version, booking intent ID, booking attempt ID, payment attempt ID, canonical booking ID, provider booking reference and servicing attempt ID. Do not collapse them into one identifier.
Structured events
Emit domain events for important transitions and include correlation IDs, state change, evidence source and provider reference. Do not place PII in event payloads.
Metrics hierarchy
Track search provider health, offer/reprice freshness, booking confirmation/UNKNOWN/reconciliation, payment authorization/capture/refund, and servicing completion/manual intervention.
Trace spans
Represent provider calls as separate spans with adapter, operation, provider, timeout budget and outcome classification. Avoid raw request/response bodies in traces because they can leak sensitive data.
Logs vs events vs metrics
Logs serve debugging, events preserve domain evidence, metrics aggregate trends, and traces represent causal request chains. Design schemas by purpose rather than duplicating uncontrolled payloads everywhere.
SLOs
Define business SLOs for search completion, booking confirmation, UNKNOWN resolution, reconciliation age and servicing completion, not only infrastructure uptime.
Alerting
Useful alerts include provider p95 latency spikes, aging UNKNOWN backlog, payment/booking divergence, duplicate-booking signals, webhook signature failures and reconciliation queue growth.
Failure modes
Broken provider-reference correlation, PII in logs, high-cardinality metric labels, losing failed traces to sampling, clock skew and inconsistent state vocabularies.
Production checklist
Use canonical correlation IDs, structured domain events, provider spans, PII redaction, metric-cardinality limits, business SLOs, biased retention for errors/UNKNOWN outcomes, searchable provider references and consistent time standards.
Planning a similar integration?
We can review requirements, feed/API design and the production approach with you.