Jiss Tech insights

What Building a Flight Tracker Taught Us About Third-Party APIs

Six data feeds, none of them fully trustworthy: the verification, caching, and fallback patterns we learned building FlightDetector — and how they apply to business system integrations.

Field notePublished July 31, 2026Practical thinking for teams building better systems.

We recently built FlightDetector, a real-time flight-tracking platform that fuses six independent aviation data feeds into one live picture of the sky. None of those feeds agree with each other all the time. Some go down without warning. Some are confidently wrong. Making them behave as one reliable system taught us more about third-party API integration than any client project could — and every lesson applies directly to the business systems we build, from CRMs to payment pipelines.

Never trust a single source

Two well-known aviation route databases told us the same Southwest flight was going to two different cities — and the aircraft was actually flying to a third. Airlines reuse flight numbers across multiple legs a day, and each database had stored a different snapshot. The fix was not picking the "better" database. It was verification: we check every claimed route against measured reality — where the aircraft actually took off and which direction it is actually flying — and reject anything that contradicts the evidence.

The business translation: if your inventory system, your accounting software, and your e-commerce platform each hold a copy of the same order, one of them is wrong more often than you think. Integrations should not just move data — they should reconcile it against a source of truth and flag what does not match.

Archive first, call the API second

Our primary historical data source allows 4,000 requests a day. That sounds generous until a public site starts asking the same questions repeatedly. So every answer we ever fetch is stored permanently, and a coverage index records exactly which time windows we have already paid for. Repeat questions are answered from disk in milliseconds, at zero cost. The system literally gets cheaper and faster the longer it runs.

Most businesses do the opposite: they call the external API every time and throw the answer away. If a vendor API bills per request — or throttles you at the worst moment — an archive-first design is often the difference between a system that scales and one that gets rate-limited during your busiest week. We go much deeper on this in our guide to cutting API costs.

Enforce API budgets in the database, not in your head

Two of our fallback data sources allow only 100 and 1,000 requests per month. We enforce those caps in the database itself: a usage counter keyed by calendar month, checked before every call, with a hard stop below the real limit. And because every answer is learned permanently, no question is ever paid for twice. A free-tier budget that sounds impossibly small becomes sustainable when the system remembers.

Fail toward honesty, not toward guesses

When every source disagrees with the measured evidence, FlightDetector shows "destination unknown" rather than a confident wrong answer. That choice was vindicated the first time we photographed a flight whose stored route pointed east while the aircraft flew west. Users forgive a system that admits uncertainty. They do not forgive one that lies with confidence — and neither do auditors, accountants, or customers reading an invoice.

Every dependency will fail — decide the fallback before it does

Mid-project, our primary live feed started timing out intermittently. Because the fallback chain already existed, the map silently switched to a secondary source and visitors never noticed. The lesson is not that outages happen — everyone knows that. It is that the fallback has to be designed, tested, and boring before the outage, because you will not be designing calmly during one.

What this means for your systems

The same patterns — cross-source verification, archive-first data, database-enforced budgets, honest failure states, and rehearsed fallbacks — are exactly what make business integrations dependable: CRM syncs that reconcile instead of duplicate, webhook pipelines that survive vendor outages, and reports leadership can actually trust. We build them that way because we have seen what happens when data is taken on faith.

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Whether it is CRM, billing, or a vendor API that keeps letting you down, we design integrations that verify data, survive outages, and stay within budget.