Each platform in a large landscape usually works. The failures happen in the space between them — where a record is transformed, a field is mapped, a job runs on a schedule, and nobody owns the result end to end.
Reliability is not uptime
An integration can run every day, complete without errors, and still deliver the wrong data. It can process everything it receives and silently drop what it cannot handle. Reliability, properly defined, means the right data moves completely to the right place in a form the receiving system can use — and that someone can tell within minutes when it does not.
That standard changes the design. It means explicit error paths rather than implicit ones, retries that cannot duplicate a record, and reconciliation that can answer the question actually being asked: did everything that should have arrived, arrive?
Where the engineering effort concentrates
Interface contracts and integration architecture; transformation, mapping and validation rules; error handling, retries and idempotency; and the reconciliation and monitoring that make an integration's health visible rather than assumed.