Testing and validating workflows
1. Testing and validating workflows
Hello again! Before deploying any automation into production, it's essential to test and validate it.2. Why testing matters
Testing confirms that a step behaves as expected. It helps us catch issues early and fix them fast, reducing errors, saving time, and building confidence in our automations. Workflows are chains of many steps. If one step fails, the whole chain can break. Instead of running everything and discovering issues at the end, we can isolate and test a single step with the Execute Node button. That way, we catch problems early and fix them before they spread.3. Test a node
Imagine we've built an onboarding workflow for new employees. It collects their details, sends a Slack message, and creates their accounts.4. Test a node
If our Slack setup is wrong, we don't want to run the entire process and discover the problem at the end. By testing just the Slack step, we immediately see the error and can fix it before moving forward.5. Test a node
It might seem manual, but this approach saves time; we'll know precisely where things break and why. Once a step runs, the next question is: Does the output make sense? That's where validation comes in.6. Validating your data
After running a node, don't just check that it executed; look closely at the output. Testing shows that the step ran; validation confirms that the data is correct.7. Validating your data
Ask: Do the fields contain what we expect? Is the format correct? Does the data follow the right rules or patterns? We're not only checking that it ran, but also making sure the result makes sense.8. Validation in e-commerce
Let's make this concrete with an example. Imagine an online store that automatically sends out discount codes to customers.9. Validation in e-commerce
Each code needs to be unique and exactly 10 characters long. Our workflow runs smoothly, and the system reports "success".10. Validation in e-commerce
But when we check the output, one of the codes is only six characters, or a duplicate appears twice. The step succeeded, but the output breaks the rule; testing passed, validation failed. It's like mailing out a batch of gift cards; we know the printer worked, but a few cards might still have the wrong amounts printed on them.11. When testing succeeds, but validation fails
This is the key idea: Testing checks if something runs. Validation checks if the result is right.12. When testing succeeds, but validation fails
In our e-commerce workflow, the generation step worked perfectly; that's the test.13. When testing succeeds, but validation fails
However, the data didn't follow the business rule, so validation failed. Prevent it with simple checks: is the code 10 characters unique? If not, regenerate or halt before sending anything. If either rule fails, stop the flow or trigger a correction path before sending anything to customers. By combining testing and validation, we protect our workflow from technical errors and data quality issues.14. Why both matter
Testing and validation work best together. Testing helps us isolate problems early and check our logic,15. Why both matter
while validation keeps our data clean and trustworthy.16. Why both matter
Together, they turn prototypes into production-ready systems that are reliable, predictable, and scalable.17. Let's practice!
Let's test and validate our workflows step by step. We'll run individual nodes, inspect outputs, and ensure data flows as expected.Create Your Free Account
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