Short answer
A reliable API integration treats failure as normal, not as an exception: timeouts, rate limits and repeated messages are designed for up front. The source of truth for each record must be clear, repeating an operation must not create duplicates, and missed records must be findable through reconciliation.
Contract and ownership
Write down the authoritative system for each field. Specify data types, time zones, currencies and unique identifiers. Verify API versions and access scopes against official provider documentation.
Treat failures as expected conditions
Timeouts, rate limits and temporary outages need explicit handling. Define retryable failures, waiting policies and a manual review queue. Retrying invalid input indefinitely will not fix it.
Consistency and reconciliation
Test duplicate and out-of-order events. Periodic source-to-destination reconciliation can reveal missed records. Request identifiers help trace an operation across both systems.
Prepare for operation
Design alerts, credential renewal and user-visible states during outages. Initial request success is not the only acceptance criterion; recovery after failure matters too.
Retries and repeated operations
Retrying a request creates the risk of applying the same operation twice. To prevent this, the operation is given a unique key, such as an order ID, and the target system does not create a new record when it sees the same key a second time. Transient errors get a limited number of retries with growing waits; permanent errors go to a review queue.
A practical evaluation exercise
Test sending an order to a destination system. Deliver the same message twice, delay the response and temporarily stop the destination. Verify that only one record is created, retries are bounded and failed work reaches a review queue. Use test data and record how an operator safely resumes the task.
Frequently asked questions
Two questions we are often asked on this topic.
Are webhooks or periodic polling more reliable?
Webhooks give instant notification but can be missed; polling is slower but can catch missed records. Reliable integrations often combine both: fast triggering by event, compensation through periodic reconciliation.
How should I test the integration?
Besides the normal flow, send the same message twice, delay the response and temporarily shut down the target system. Verify that a single record is created, retries stay limited and the failed job lands in a visible queue.
Sources and further reading
