Automation is wonderful until it breaks. And it will break. External APIs change. Data formats shift. Edge cases emerge. Debugging skills are essential.
Start with the error message. Most automation platforms provide error details. Read them carefully. The message often points directly to the problem.
Technical Note
Choose technologies that your team can maintain. The best tool is one you'll actually use and improve.
Identify when it last worked. Check execution history. Find the last successful run. What changed between then and now? Often the answer is obvious.
Test each step individually. Isolate the failing component. Run upstream steps manually. Verify the data looks correct. The break point becomes clear.
Check external dependencies. APIs go down. Credentials expire. Rate limits get hit. Verify each external service is accessible and responding correctly.
Look for data anomalies. A new customer with a special character in their name. A product with missing required fields. Edge cases break automations that worked for months.
"Simple systems that work beat complex systems that don't. Start with reliability, then add sophistication.
Review recent changes. Did someone modify the automation? Did a connected app update? Change logs reveal correlation with failures.
Test with known good data. Create a test case with clean, predictable data. If it works, the problem is input data. If it fails, the problem is the automation logic.
Legacy Systems
- •Siloed data
- •Manual integrations
- •Security vulnerabilities
- •High maintenance costs
Modern Stack
- •Unified data layer
- •API-first design
- •Built-in security
- •Automated maintenance
Build monitoring and alerts. Do not discover failures at 3am. Set up notifications for failed runs. Catch problems early before they cascade.
Document fixes for future reference. The same problems tend to recur. A troubleshooting playbook saves time on repeat incidents.
