Our team is evaluating approaches for extracting data from legacy systems that lack modern APIs. We’re debating between using ServiceNow RPA Hub with API connectors versus building custom scripted automation using REST messages and scheduled jobs.
The legacy systems have basic HTTP endpoints but no structured API documentation. RPA connectors seem appealing for their visual configuration and error handling capabilities. However, scripted automation offers more flexibility for complex data transformations and conditional logic.
From an API development perspective, I’m curious about others’ experiences with RPA API integration versus traditional scripting for similar scenarios. What are the trade-offs in terms of maintainability, error handling strategies, and long-term scalability? Specifically interested in Tokyo release experiences.
Both approaches have merit. In Tokyo, RPA Hub improved significantly with better API connector templates and error handling. However, I’ve found that scripted automation scales better when you need to handle multiple legacy systems with varying authentication methods. RPA works great for 1-3 systems, but managing dozens of RPA flows becomes cumbersome compared to centralized script libraries.
We actually use a hybrid approach. RPA Hub for the initial data extraction and session handling, then hand off to scripted business rules for complex transformations. This gives you the best of both worlds - RPA’s strength in handling legacy UI interactions and scripting’s flexibility for data processing. The RPA API can trigger script includes seamlessly.
That’s a great point about scale, Sofia. We’re looking at potentially 8-10 legacy systems over the next year. The scripted approach might give us better code reuse through shared libraries. How do you handle the lack of visual documentation with scripts though? That’s one advantage RPA has for knowledge transfer.