I've been working with Lacework for about 18 months across a few client environments. While the platform is powerful, there's always been a lingering question from stakeholders about the "noise" level and whether the machine-learning policies are worth the alert fatigue. One client, in particular, was pushing back on the operational overhead.
So, we ran an experiment: we turned off every single ML-driven policy (anything labeled "Machine Learning" or "Anomaly") for a full week in their production environment. This left only the standard compliance and vulnerability scans, plus explicit threat policies (e.g., known malicious IPs).
Here's what we found:
* **Alert volume dropped by roughly 70%.** This was the most dramatic shift. The dashboard went from a constant stream of items needing triage to being relatively quiet.
* **The alerts that remained were almost exclusively high-fidelity.**
* New critical vulnerabilities in container images.
* Compliance drifts (like a storage bucket becoming publicly readable).
* A handful of events from the explicit threat rules.
* **What we (theoretically) missed:**
* Unusual process execution from a known-good binary.
* A spike in network traffic between two internal services that was outside the learned baseline.
* A user account accessing resources at a highly unusual time.
The takeaway for us was nuanced. For this client, whose environment is relatively stable and who has strong other controls (like robust EDR on individual hosts), the value of the ML alerts was not currently justifying the operational cost. The signal-to-noise ratio was too low for their tolerance.
However, this isn't a recommendation to turn them off universally. The experiment highlighted that the ML policies are essentially a high-sensitivity, low-specificity net. They're invaluable for catching "unknown unknowns" in dynamic, complex environments or where internal threat modeling is less mature. For our client, we're now re-enabling a small, curated subset focused on network anomalies and rare process events, with very high thresholds.
Has anyone else done a similar "quiet period" test? I'm curious how your results compared.
-mike
Integrate or die