What to plan before integrating supplier APIs

Wiring up a supplier API, authenticating, sending a request, parsing a response, is usually the least demanding part of the job. The hard, valuable work is everything around it: handling data that arrives inconsistent or incomplete, coping when the supplier is slow or down, and deciding what your system does when reality does not match the documentation. Teams that underestimate this ship integrations that work in the demo and fail in production.

Before writing any code, it is worth planning for the messy reality of third-party data. Supplier APIs in travel are often older, quirky and only loosely standardised. Assuming they will behave like a clean modern API is the fastest route to a fragile integration that breaks whenever the supplier changes something you did not control.

Not all supplier data is trustworthy or complete. Fields may be optional in practice, formats may vary between records, and the same concept may be represented differently than in your own system. Before relying on a feed, examine real responses, not just the documentation, to understand what actually arrives, how consistent it is, and where you will need to clean, map or reject it.

This mapping work is where integrations succeed or fail quietly. Currency, dates, room types, cancellation terms and pricing rules rarely align neatly between two systems. Deciding your canonical model up front, and translating supplier data into it deliberately, prevents the slow accumulation of edge cases that otherwise turns a tidy integration into an unmaintainable tangle of special cases.

External APIs go down, time out and return errors, and a resilient integration expects this rather than hoping against it. Timeouts, retries with sensible limits, and clear fallbacks keep your own product usable when a supplier misbehaves. Without them, one slow third party can freeze your booking flow and take your conversion rate with it, turning their outage into your problem.

Resilience is also about isolation. A single failing supplier should degrade one part of the experience, not the whole site. Designing so that one bad response is contained, a missing result rather than a broken page, is what keeps your platform dependable even though the systems it depends on are not entirely within your control.

Calling a supplier for every request is slow, expensive and fragile. Sensible caching reduces load, speeds up your product and shields you from transient failures. But caching in travel is delicate: prices and availability change, and serving stale data can mean quoting something that no longer exists. The plan must balance performance against how fresh each type of data genuinely needs to be.

Different data tolerates different staleness. Static descriptions can be cached for a long time; live availability often cannot be cached at all. Deciding these boundaries deliberately, per data type, rather than applying one blanket rule, is what lets you gain the performance benefits of caching without misleading customers about what they can actually book.

Most of an integration's real complexity lives in the exceptions: partial responses, unexpected values, rate limits, records that violate assumptions the documentation never mentioned. Planning explicitly for these, how you log them, whether you fail loudly or degrade quietly, how you alert someone when a supplier changes behaviour, determines whether the integration is maintainable or a constant source of firefighting.

Good exception handling also protects the customer. The aim is that a supplier's problem never becomes a confusing dead end for the person booking. Clear internal alerting lets your team react before customers notice, while sensible user-facing fallbacks mean that when something does go wrong, the experience degrades gracefully rather than breaking outright.