Which one is preffered Archieving or Deleting a process model in Data management .
Any use case for the both ?
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Cost benefit analysis required:
Archive: Cost, you have to store on disk. You can eventually fill up disk completely. Benefit: You can unarchive and if needed you can use to debug issues or correct problems.
Delete: Cost: You can't debug. You can't figure out what happened beyond what you recorded in audit logs. Benefit: You don't take up any space or resources at all.
Keep Running: Cost: Keeps your engines busy and takes up RAM on your servers. Benefit: Really easy to debug and correct on the fly when you need to.
My advice: If it's a process that does a basic thing, and especially if it processes a mountain of data, go ahead and quickly delete it. Or quickly archive if you can afford the space it takes up. If it's complex, or error prone, or there's lots of ways that it could go wonky, and especially if you have a lot of tickets, keep those longer before you archive or delete to help your O&M team. If each instance is huge, think about delete. If each is small, don't worry and just archive. Think about how long you keep your archives before you offload or delete them too.
Find a balance between being able to fix issues, and improving performance, and saving resources.