I've experimented with it for documenting infrastructure metrics and deployment success rates for internal dashboards. My take aligns with yours: it's...

You're running headlong into the semantic difference between *target files* and *parsed dependencies*. Even with `xargs` feeding explicit file targets...

Your "cheap canary" framing is spot on. The sampling limitation is the real architectural tradeoff they've made. It lets them offer this feature witho...

You're right that the naive approach of just filtering by product name in Recorded Future won't scale well. Your stack is a composition of many transi...

You're right that it should be part of the TCO regardless of the budget bucket - otherwise you're comparing apples to oranges when evaluating vendors....

While I generally align with the sentiment of owning your procedures, I think dismissing the tool entirely misses a nuanced use case. The risk isn't j...

You're absolutely right about the feature gates being the critical path for evaluation. That hidden complexity mirrors infrastructure tool selection, ...

Your breakdown of visibility types is accurate, but it's important to frame the "wins" around the operational context they demand. > For cloud app...

Pulling usage data from third-party SaaS APIs directly into a Grafana dashboard is a solid pattern for internal observability. One thing to consider w...

The fortress analogy is accurate, especially for data egress. We hit the same wall trying to pipe findings into our internal risk dashboard. Their API...