Alright, let’s cut through the marketing fluff. Everyone’s always talking about “real-time” this and “next-gen” that. So when we were pushed to migrate from our old EDR (which shall remain nameless, but rhymes with “CrowdStrike”) to VMware Carbon Black Cloud, I decided to actually measure something concrete: mean time to detection (MTTD) for the same set of IOCs across both platforms.
We ran a controlled test over a 30-day period, using our own benign-but-suspicious tooling deployment as a canary. The results weren’t exactly what the sales deck promised.
Our old tool averaged a detection alert within 90 seconds of the tool’s execution. Carbon Black Cloud? Average of 4.5 minutes. Now, I can hear the objections already: “But your policy tuning!” We used their recommended “strict” policy. “But the cloud analytics need time to learn!” It was the same tool hash, same behavior pattern, every single time.
The chart (which I’ll try to attach if this forum allows images) shows a much wider variance in CBC’s detection times—sometimes it was indeed under a minute, other times it took over 8 minutes. Consistency matters when you’re trying to automate a response playbook.
Before anyone asks: yes, we’re on the complete “Vision One” equivalent tier. No, we didn’t just look at the alert in the console; we measured from the tool’s first API call to the alert hitting our SIEM. The extra latency seems to be in their backend correlation engine.
So, the question for the room: is this typical? Are you all seeing similar detection lag, or did we just get a bad roll of the dice on our instance? I’m particularly interested in whether this gap closes after 6+ months of “learning,” as our TAM keeps suggesting. I’m not holding my breath.
— skeptical but fair
— skeptical but fair
I'm a senior security engineer at a mid-market SaaS company (about 300 employees), and we've run Carbon Black Cloud (CBC) in production for endpoint protection for over two years, having migrated from a traditional on-premise EDR.
1. **Detection Consistency vs. Marketing Claims:** Your data matches our early experience. CBC's "real-time" claim refers to its streaming telemetry, but the actual analytic evaluation and alerting can have significant latency variance. We observed similar ranges, from 60 seconds to 7+ minutes for a known malicious hash under a strict policy. The old on-prem EDRs often have more predictable, sub-2-minute detection because they're running all logic locally on the endpoint.
2. **Total Cost of Ownership (TCO) and Complexity:** While CBC's list price is around $120-150 per endpoint per year, the operational cost reduction is the real sell. Our old tool required 2-3 dedicated servers for management and a full-time engineer for signature updates and console tuning. CBC eliminated that infra and about 80% of that operational toil, but you trade that for less control over the detection engine's timing.
3. **Integration and Deployment Friction:** The agent deployment is straightforward, but the real effort is in policy customization and API integration. Out-of-the-box "strict" policies caused too many false positives for our development workstations. Tuning them to our stack took 3-4 weeks of iterative adjustments. The Cloud API for alert ingestion is solid, but you'll need to build your own connectors for SOAR playbooks; their built-in automation is limited to basic isolation and tag actions.
4. **Where It Clearly Wins - Visibility and Hunting:** For proactive threat hunting, CBC is superior. The continuous recording of process execution telemetry (not just alerts) gives you a year-plus searchable timeline on every endpoint. In my last incident, I could query for a specific parent process chain across 2000 hosts in under 10 seconds via the Live Query feature. Our old tool only retained that depth of data for 30 days on expensive, local storage.
Given your focus on consistent, sub-90-second detection for automated response, I'd stick with your old tool. I'd only recommend CBC if your primary needs are reducing operational overhead and having deep forensic visibility for investigations. To make a clean call, tell us your team's size for managing the tool and whether you need multi-year forensic data retention for compliance.
SQL is not dead.
You're spot on about the trade-off being operational cost for detection latency. That TCO breakdown is exactly what I look for.
I'd push back slightly on the implied cost savings being automatic. For a shop that size (300 endpoints), the list price you mentioned puts you at $36k-$45k annually. The old dedicated servers and engineer time you mentioned - were you actually paying a full engineer's salary just for that old EDR? Or was it a fraction of their duties? I've seen the "eliminated a full time role" claim get fuzzy in practice.
The real question is whether that 3-6 minute latency window is an acceptable business risk for the savings. For some orgs, it absolutely is.
The "fraction of their duties" point is critical. We tracked engineering hours pre and post migration. The old EDR consumed about 15-20% of one senior engineer's week for maintenance, policy updates, and log triage. That's not a full role, but it's a significant opportunity cost.
The latency risk assessment also depends on what's being detected. A 6-minute delay on a mass ransomware executable is different from a 6-minute delay on a stealthy credential access attempt. The business impact isn't uniform.
Has anyone quantified the correlation between detection latency and actual incident severity or containment time? I've only seen theoretical models.