An API integration is a workflow between systems. A successful request is only one part of it. Before agreeing a scope, establish what should happen when data is missing, requests repeat, or one system becomes unavailable.
This checklist helps turn “connect these tools” into something an engineering team can assess.
Verify the operations you need
List the records to read or change. Check the documented endpoints for each operation, the required permissions, and whether access depends on a paid plan or vendor approval.
An inventory API that reports stock does not necessarily support reserving it. A CRM that accepts contacts may not expose custom approval states. Test the exact operation in an appropriate test environment before treating it as available.
Record the vendor’s documentation URL and the API version you evaluated. Avoid basing the scope on a marketing page that simply says “API available.”
Decide which system owns each field
Choose a source of truth for customer identifiers, contact details, order state, and any other shared information. If two systems can change the same field, define how conflicts are resolved.
Map the actual values. Dates need an agreed time zone. Money needs a currency and precision. An empty string, a missing field, and an explicit deletion may have different meanings.
Use realistic invented examples, including incomplete records. This turns assumptions about data quality into visible decisions.
Plan for repeated and interrupted requests
A timeout does not prove that the other system rejected the request. It may have saved the record before the response was lost. Retrying blindly can create duplicates.
Ask whether the receiving API supports idempotency keys or another way to identify an existing operation. If it does not, decide how your application will reconcile uncertain results before repeating a write.
The MDN explanation of idempotency is a useful reference for repeated operations. The specific API contract still determines which requests are safe to retry.
Separate temporary failures from invalid requests. A brief outage may justify a delayed retry. Missing permission or invalid input usually requires a correction. Repeating either indefinitely makes the problem harder to see.
Define the acceptable delay
Does the data need to move immediately, within a few minutes, or overnight? That answer affects whether a scheduled task, webhook, or queue is appropriate.
For webhook-based work, check how the sender authenticates events, whether delivery can repeat, and how missed events can be recovered. Do not assume events arrive in order unless the provider guarantees it.
For a concrete provider example, GitHub’s webhook guidance covers webhook secrets, asynchronous handling, and missed deliveries. Check the equivalent guidance for your vendor.
For scheduled work, record the last successful position and define how a failed run resumes. The important outcome is knowing which records still need attention.
Assign monitoring and recovery
Decide who receives a failure notification and what they need to resolve it. An alert should identify the affected workflow without exposing unnecessary customer data or credentials.
Include a reconciliation method. Comparing expected and actual records can reveal failures that individual request logs miss. Agree who investigates discrepancies and how corrected records are reprocessed.
Before release, test duplicate input, expired credentials, invalid data, a timeout, and a partial outage. The checklist is complete when the responsible person can explain what happens in each case.
Inputs for an estimate
Send the system names, documentation, required operations, expected volumes, acceptable delay, and a sample data mapping. State which access is already available and which is still being arranged.
These details do not remove all uncertainty. They identify it early enough to choose an investigation, a bounded implementation, or a different approach.
Put it into practice.
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