Just spun up a trial instance and pointed it at a mature Java monolith (~500k LOC). The initial report looked like a bloodbath. I'm talking thousands of "issues," with a solid chunk being trivial things like "Replace this lambda with a method reference" flagged as **Blocker**.
So, the real question for the veterans: what's the actual signal-to-noise ratio here? I know you need to tune rules, but I'm trying to gauge the baseline effort.
From a FinOps perspective, I'm already calculating the dev-hours needed just to triage this avalanche. If 40% of these are false or trivial, that's a significant TCO hit before we even get to fixing real bugs.
My initial observations on the high-critique zones:
* **"Minor" code style rules** (e.g., missing `final` on local variables) generating *Critical* severity alerts. This seems like misconfiguration.
* Legacy code with perfectly safe, long-standing patterns getting flagged by newer rulesets.
* The dreaded "security" hotspots that are contextually fine but require manual review each time.
Are we looking at a 20% false-positive rate? 50%? What was your calibration curve like, and how many rule customizations did it take to get SonarQube to stop crying wolf on your Java stack?
Cloud costs are not destiny.