Handling API Errors in Synchronous Verification Workflows

When building integrations that rely on external identifier verification, the most robust systems are those that treat errors as expected application states rather than unexpected crashes. Whether you are performing a simple check or integrating complex scoring, handling the request-response lifecycle correctly is critical for maintaining a stable service.

Understanding the Synchronous Request Lifecycle

In a synchronous verification workflow—such as checking if a phone number is registered on a specific platform—your application sends a request and waits for a response. The POST /v1/check endpoint is a primary example of this pattern.

Because these checks rely on external signals, your code must account for the reality that not every request will return a successful result. A successful request returns a 200 status code, but your logic should be prepared for non-success scenarios.

Mapping HTTP Status Codes to Decision Logic

Effective error handling starts with categorizing the HTTP status codes returned by the API. Here is a recommended strategy for mapping these codes to your application logic:

1. The Success Case (200)

When you receive a 200 status, the check has completed. However, success at the transport layer does not always mean the identifier was verified. Always check the success boolean in the response body to confirm the outcome of the verification itself.

2. Client-Side Errors (400, 401)

• 400 Bad Request: This typically indicates an issue with your input, such as an incorrectly formatted phone number or a missing service_type field. Do not retry these requests; instead, log the validation error and notify the user or the upstream system that the input requires correction.
• 401 Unauthorized: This signals an issue with your X-API-Key. This is a configuration error that requires immediate attention from an operator. Ensure your key is correctly injected into the request headers.

3. Server-Side Errors (500)

• 500 Server Error: These indicate a temporary issue on the provider's side. This is where your application should implement a controlled retry strategy. Avoid aggressive loops; instead, use an exponential backoff approach to allow the service time to recover.

Implementation Pattern

When designing your adapter layer, encapsulate the API call to separate the transport logic from your business rules.

async function verifyIdentifier(identifier, serviceType) {
 try {
 const response = await fetch('https://api.ekycpro.com/v1/check', {
 method: 'POST',
 headers: {
 'X-API-Key': process.env.API_KEY,
 'Content-Type': 'application/json'
 },
 body: JSON.stringify({ service_type: serviceType, identifier: identifier })
 });

 if (response.status === 200) {
 return await response.json();
 } else if (response.status === 500) {
 // Handle transient failure with retry logic
 throw new Error('Transient server error');
 } else {
 // Handle permanent client errors
 throw new Error(`Request failed with status: ${response.status}`);
 }
 } catch (error) {
 // Log and manage failure states
 console.error('Verification failed:', error.message);
 }
}

Conclusion

Robust error handling is the difference between a brittle integration and a production-ready system. By distinguishing between permanent client errors and transient server issues, you can create a resilient workflow that provides meaningful feedback to your users while gracefully handling the inevitable hiccups of distributed systems. For more details on integrating these services, refer to the official documentation.

This article was drafted with AI assistance and reviewed before publishing.