Hi guys, thanks for all your contributions to this topic, especially @octechnologist and @ClaytonM.
I want to revive this thread because as RPA is evolving, so should our best practices and frameworks. With more automated processes and more robots come different challenges, so this post is regarding flexible and scalable exception handling in rapidly changing IT-environments.
Consider this:
A new and unexpected exception comes up in a system used by a lot of robots. Robots cannot recover from this by simply restarting within the ReFramework. A human can log on to the machine and perform a workaround, but the error might come again the next day. IT can’t help and so your robotics operations team is stuck handling the same error on several machines to keep things running. This takes a lot of time.
Now, robots should be able to perform the workaround themselves, but due to the high number of processes it takes plenty of time to implement the workaround and republish for every process. Also, if one thing is for sure, it is the next (major) exception will always be coming! The exception handling should be flexible and scalable!
One idea is to publish an ExceptionHandling workflow to Orchestrator as a library and then use this library in all processes to - obviously - handle exceptions if they occur. When the next exception comes up, the robotics team can update the ExceptionHandling library to include a workaround for the new exception, publish to Orchestrator and use the Mass Project Dependencies Update Tool to equip all the processes with the new ExceptionHandler.
This way your robo operations can quickly react to global issues in the IT environment and implement a fix for all your robots with comparatively little work.
Do you guys have experience and/or best practices with some kind of flexible and scalable exception handling? What do you think of the scenario explained above? Am I missing anything? I’m excited for your feedback.
Thanks,
Lukas