I'd be shocked if you can accurately identify waste since you are not ultimately familiar with the product.

Sure, I've kicked over what I thought was waste but told it's not or "It is but deal Ops"

You're right, it's not always binary. That's why we broke it down into categories:

https://docs.usetero.com/data-quality/logs/malformed-data

You'd be shocked how much obviously-safe waste (redundant attributes, health checks, debug logs left in production) accounts for before you even get to the nuanced stuff.

But think about this: if you had a service that was too expensive and you wanted to optimize the data, who would you ask? Probably the engineer who wrote the code, added the instrumentation, or whoever understands the service best. There's reasoning going on in their mind: failure scenarios, critical observability points, where the service sits in the dependency graph, what actually helps debug a 3am incident.

That reasoning can be captured. That's what I'm most excited about with Tero. Waste is just the most fundamental way to prove it. Each time someone tells us what's waste or not, the understanding gets stronger. Over time, Tero uses that same understanding to help engineers root cause, understand their systems, and more.