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In my past experience in IT, the ticketing system basically doubled as an aggregated event log, and it was a legitimately good use case. The monitoring software we ran on our thousands of client workstations and servers was extremely powerful and could capture any conceivable metric to use as a trigger for auto-generating a ticket.

So, a lot of tickets generated would simply just be data reports with some info dumped in the ticket description, designed to be auto-closed but possibly useful later as an easily-accessible timestamped reference to some data.

Lots of other auto-generated tickets were "probably not an issue but it should pass over the eyes of someone knowledgable about this server/network" tickets. Like Windows Event Log error roundups, CPU usage spikes, or specific triggers that were set up in the aftermath of some catastrophe to help preemptively avoid a repeat incident.

Anyway, tickets are a great "first line of filtration" where you can take a massive ingest of all different kinds of data (hardware metrics, system logs, network activity), apply meaningful human context ("This pattern could be a sign of xyz"), and store it in a unified database. With that use case, it's easy to imagine a company with millions of customers and millions of servers producing millions of tickets.

I've never seen a ticket system used as just as dumping ground for data in auto-closed tickets. Seems like there would be better solutions for that, particulary for data you want to find later (in my experience, the search capability of ticket systems varies from poor to "don't bother, you won't find what you're looking for")

Anything else, that needs a human to interpret or take action on, yes, ticket systems get extremely wide usage.

That makes sense, but a part of me is wary of introducing noise at such a scale and drowning out whatever signal remains.

Also ticketing systems in my (very) limited experience tend to be bloated pieces of software, so that adds a fun dimension to it.