Workflow Debugging

Every automation builder encounters failures. APIs go down, credentials expire, data arrives in unexpected formats, and configurations have subtle errors.

The skill isn't avoiding failures — it's resolving them quickly.

Understanding what error codes mean, knowing where to look for diagnostic information, and having a systematic debugging approach separates effective automation builders from frustrated ones.

Testing Fundamentals

Test each step as you go. Don’t build 20 steps only to discover step 3 was broken the entire time. Configure a step, test it immediately, verify the output, then move on. Catching errors early prevents cascading issues and wasted debugging time.

Use realistic sample data that matches real production input. Avoid empty fields or placeholders like "test123". Use real examples with proper formatting and likely edge cases. This surfaces problems before they impact live workflows.

Access Zap History from the left sidebar. Every run appears with a status. Open any run to see exactly what data went into each step and what came back. When something goes wrong, Zap History is the first place to look.

Debugging Workflow

When a Zap fails, follow a systematic approach. Start by opening Zap History, drilling into the failed run, and identifying the step that errored. Read the error message carefully, it often explains the problem directly, then check the error code to understand the category of issue. Examine the data in and out of the step to confirm the input matches what you expect. For HTTP requests or API calls, compare your setup against the documentation exactly. Next, check external factors such as service outages, expired credentials, or recent changes in the source app. Try testing the step in isolation to see if the issue is reproducible. If you’re still stuck, get help by providing full context to AI tools, community forums, or Zapier support.