Modern flight-search systems juggle dozens of services — search APIs, fare engines, cache clusters, and partner gateways — all to assemble a single price quote in milliseconds. When something goes wrong (say, a price anomaly or missing fare), sifting through siloed logs can leave engineers blind. True visibility comes from observability: correlating logs with metrics and traces across the architecture. In practice, senior teams have learned that without request tracing and rich metrics, elusive faults in fare pricing often defy diagnosis.
Here we describe a typical flight‐search flow, show why plain logging falls short, and share how Datadog-powered observability (metrics, tracing, correlation IDs, alerts) saves the day. We draw on anonymized incidents — intermittent mismatches, provider glitches, race conditions — to underscore practical lessons and concrete debugging strategies.