The hype around Lacework’s "data-driven" security platform is palpable, but I find myself wondering who’s actually running this at scale in a complex enterprise. It’s one thing to pilot it in a dev environment or a startup with a single cloud. It’s another to replace an existing, entrenched stack in a Fortune 500 with multiple legacy systems, three clouds, and a compliance team that still thinks in binders.
I’m auditing our own vendor landscape and the usual buzzwords are flying: "polygraph," "machine learning," "normalized behavior." Sounds great until you need to map those alerts directly to a CIS control framework for auditors, or prove to a GDPR data protection officer that your PII detection is actually exhaustive. The pricing model based on "data units" also gives me pause—in a large environment, that feels like a blank check.
So, I’m looking for real-world experiences. Not from a sales engineer, but from someone who’s fought the battle. Did the behavioral baselines actually stabilize, or are you drowning in false positives from authorized change management tickets? How did you handle the ingestion costs for full audit logs across everything? And most importantly, did it materially improve your mean time to *resolution*, or just give you prettier graphs while you chased incidents the same old way?
Trust but verify