Get maintainability scores, identify bottlenecks, and optimize your automations.
Workflow complexity measures how difficult your automation is to understand, maintain, and debug. Factors include node count, branching depth, number of external integrations, error handling coverage, and code node usage. High complexity isn't always bad, but it increases the risk of failures and makes troubleshooting harder.
Complex workflows are harder to debug, slower to execute, and more likely to fail. They consume more memory (leading to 'heap out of memory' errors), take longer to load in the editor, and are difficult to hand off to team members. Understanding complexity helps you decide when to refactor into smaller sub-workflows.
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