5 API Error Handling Mistakes That Are Costing You Users

Poor error handling is the silent killer of API adoption. You can have the fastest, most feature-rich API in the world — but if your errors are confusing, inconsistent, or unhelpful, developers will abandon it.

Here are 5 common API error handling mistakes and how to fix them.

1. Returning 200 OK for Errors

This is the cardinal sin of API design. Some APIs wrap every response in a 200 status and put the "real" status in the body:

// ❌ Don't do this
HTTP/1.1 200 OK
{
  "success": false,
  "error": "User not found"
}

This breaks HTTP clients, caching layers, and monitoring tools that rely on status codes.

// ✅ Do this instead
HTTP/1.1 404 Not Found
{
  "error": {
    "code": "USER_NOT_FOUND",
    "message": "No user exists with ID 42"
  }
}

Why it matters: Monitoring tools like Datadog and Grafana track 4xx/5xx rates automatically. If everything is 200, you're flying blind.

2. Generic Error Messages

Nothing frustrates a developer more than:

{
  "error": "Something went wrong"
}

Your errors should tell developers what went wrong, why, and how to fix it:

{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Request validation failed",
    "details": [
      {
        "field": "email",
        "issue": "Must be a valid email address",
        "received": "not-an-email"
      }
    ],
    "docs": "https://api.example.com/docs/errors#VALIDATION_ERROR"
  }
}

The docs link is the secret weapon — it reduces support tickets dramatically.

3. Inconsistent Error Formats

If your /users endpoint returns errors one way and /orders returns them differently, developers have to write custom error handling for each endpoint. Pick a format and stick to it:

// A consistent error response interface
interface ApiError {
  error: {
    code: string;       // Machine-readable: "RATE_LIMITED"
    message: string;    // Human-readable: "Too many requests"
    details?: any[];    // Optional field-level errors
    request_id: string; // For debugging: "req_abc123"
  }
}

Pro tip: RFC 9457 "Problem Details for HTTP APIs" is gaining traction as an industry standard. Consider adopting it for new APIs — tooling increasingly supports it out of the box.

4. Missing Rate Limit Headers

When you rate-limit a request, a bare 429 Too Many Requests is not enough. Always include these headers:

HTTP/1.1 429 Too Many Requests
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1739800800
Retry-After: 30

{
  "error": {
    "code": "RATE_LIMITED",
    "message": "Rate limit exceeded. Try again in 30 seconds.",
    "retry_after": 30
  }
}

Without Retry-After, clients will either hammer your API with retries or give up entirely. Neither is what you want.

5. Leaking Internal Details in Production

Stack traces in error responses are a gift to attackers:

// ❌ Never in production
{
  "error": "NullPointerException at com.myapp.UserService.find(UserService.java:42)",
  "stack": "..."
}

// ✅ Safe for production
{
  "error": {
    "code": "INTERNAL_ERROR",
    "message": "An unexpected error occurred",
    "request_id": "req_x7k9m2"
  }
}

Log the full details server-side, tagged with request_id. When a developer reports an issue, you can look it up instantly without exposing your internals.

Quick Checklist

Before shipping your API, verify:

• ✅ HTTP status codes match the actual outcome
• ✅ Every error has a machine-readable code and human-readable message
• ✅ All endpoints use the same error format
• ✅ Rate limit responses include Retry-After
• ✅ No stack traces or internal paths leak in production
• ✅ Every error includes a request_id for debugging

Get these right and your API will be a joy to integrate with. Get them wrong and developers will quietly switch to your competitor.

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Building APIs? 1xAPI provides ready-to-use APIs for email verification, sports data, and more — all with clean, consistent error handling built in.