Common IBM i Integration Mistakes

Learning Objective

By the end of this lesson, you will be able to recognize the most common mistakes developers make when first working on IBM i integration, drawn from across this batch.

Simple Explanation

A handful of mistakes come up repeatedly when developers first start working on integration:

• Assuming a status code always means what it seems to. Treating every non-200 response the same way, rather than distinguishing a 404 (nothing found) from a 500 (something went wrong), leads to confusing, misleading error handling.
• Assuming an external call always succeeds quickly. Not planning for a slow, failed, or unavailable external system leaves a program with no reasonable way to handle a real, common situation.
• Rewriting trusted logic instead of exposing it. Duplicating an existing validation rule or calculation in a new layer, rather than calling the existing, already-tested logic, risks the new copy quietly drifting out of sync with the original.
• Treating JSON payloads as an afterthought. Not carefully checking that a payload's structure actually matches what is expected before using its values leads to problems that are easy to avoid by checking payload structure deliberately.
• Losing track of integration files in the IFS. Writing payloads and logs to the IFS without a clear, consistent organization makes troubleshooting a specific request much harder than it needs to be.

Why It Matters

Every one of these mistakes shares a common thread with the mistakes covered in the Common ILE Mistakes and Best Practices lesson: things can look like they are working, a request goes out, a response comes back, while a real problem is quietly present underneath. Recognizing these patterns early is what separates integration work that stays reliable over time from integration work that becomes a constant source of confusing, hard-to-diagnose problems.

Practical Example

Imagine a program calling an external shipping rate API. If the program only checks "did I get a response back?" without checking its status code, it might try to read a shipping rate from an error response that never actually contained one, producing a confusing downstream failure instead of a clear, early error message. Checking the status code first, exactly as covered in the REST API Concepts lesson, and only reading the payload once success is confirmed, avoids this entirely.

This is a simplified, illustrative example rather than a specific real incident, but it reflects a genuinely common integration mistake.

Common Confusions

"If a request comes back with any response at all, doesn't that mean it worked?" No. A response can come back with an error status code, meaning the request was received but did not succeed the way it was intended to. Checking the status code, not just whether a response arrived at all, is essential.

"Is duplicating a small validation rule in a new layer really that risky?" Yes, over time. Even a small duplicated rule can drift out of sync with the original if one is updated and the other is forgotten, which is exactly why exposing the existing logic, covered earlier in this batch, is generally the safer approach.

"Are these mistakes only a concern for large, complex integrations?" No. Even a single, simple integration, such as one customer lookup endpoint, can run into any of these, particularly not checking status codes properly or not organizing IFS payload files clearly.

Quick Recap

• Not distinguishing status codes properly, assuming external calls always succeed quickly, duplicating trusted logic instead of exposing it, treating JSON payload structure carelessly, and losing track of IFS integration files are the most common integration mistakes covered across this batch.
• Many of these mistakes let a request and response look like they worked while a real problem is quietly present underneath.
• The underlying habit that prevents most of them is treating integration as carefully as any other part of an IBM i application: checking results deliberately, reusing trusted logic, and keeping artifacts organized.

Try Asking the AI Tutor

Use the AI Tutor to ask follow-up questions about this lesson. For example, try asking:

• "Can you give me a short integration scenario with one of these mistakes and ask me to spot it?"
• "Which of these mistakes would be easiest to miss during code review, and why?"