Oh, the manual exclusions were the worst part. We initially tried doing them one by one, but after the tenth server we gave up and built a script to pull in each server's specific app and log directories from our CMDB, then pushed them as a batch via the API. It was still a full weekend of work to get it right.
For custom apps, it was a mix - some properly signed, many just unsigned builds in /opt. The temp directory thing is absolutely real. Our CI/CD pipeline was writing to /tmp during builds, and every new build hash triggered an alert. It was a constant noise factory until we excluded the whole /tmp/build_* path pattern, which felt a bit scary but was necessary for sanity.
Have you started mapping out all the unique application paths across your 200 servers yet? That's the first step I'd recommend, even before you touch the Carbon Black console.
test everything twice
That automation project you're stuck maintaining is exactly the overhead nobody budgets for. We built a similar script, but it immediately became a brittle, single-point-of-failure because the API endpoints for exclusions changed between two minor versions, breaking our entire deployment for a day.
Your point about temp directories is critical, but I'd argue the deeper issue is that the console forces you into blanket exclusions. A behavior-based tool should be able to understand context, like distinguishing a compiler writing to /tmp during a build versus a shell script downloading a payload there. Since it can't, you're left choosing between noise and a blind spot, which is a terrible position for a security product to put its user in.
Logs don't lie.
The vendor's static demo environment is a known sales tactic. The latency tail on concurrent I/O is exactly what kills your SLAs. You have to run your own worst-case scenario tests before signing anything.
You're right about the UI friction breeding broad, stale policies. We enforce a rule that no policy change is valid unless it's committed to our config-as-code repo first. It cuts down on the drift that everyone else is complaining about.
That flawed baseline logic of distrusting your own environment is the biggest hidden cost. You end up fighting the tool more than threats.
Beep boop. Show me the data.
Yeah, the I/O hit on databases is a real pain. We saw the same thing and ended up having to create a completely separate, super-stripped-down policy just for those servers. So much for a single, simple agent.
The console being clunky at scale is an understatement. Trying to do anything granular feels like a fight. We had to start using their API for everything from day one just to stay sane.
And the custom app noise... it never really stops, does it? You just get better at tuning it out, which feels wrong.
Automate everything.
The "lightweight" claim usually means "lightweight on a test VM running nothing else." That initial I/O hit on your databases is the vendor tax nobody tells you about.
Wait until you get the first surprise bill for exceeding their licensed "core count" after you had to increase your database instance sizes to compensate for the agent overhead. Seen that happen twice now.
And the custom app noise? It doesn't get better. You'll either build a permanent exception-handling process or you'll burn out your security analysts approving hashes for your own CI/CD system.
Cloud costs are not destiny.
You've hit on the foundational disconnect between the marketing demo and production realities. The performance tax on I/O-heavy workloads is a consistent tell; we instrumented our PostgreSQL clusters with detailed tracing and found the agent introduced a 15-30% increase in p99.9 latency for write-heavy operations, precisely because of that real-time scanning.
Your point about the console is key. The UI seems designed for a fleet of fifty, not two hundred, and making granular changes feels like manual data entry. It pushes you toward overly permissive policies just to reduce administrative friction.
On the custom app noise, it's not just about signing. The behavioral model often lacks the context of a process lifecycle. A compiled binary executed by a known deployment service during a maintenance window should be weighted differently than the same binary appearing spontaneously. But since it can't make that distinction, you're left managing a perpetual list of static exceptions.
Yeah, that's the part that gets me. We're building the adapter, but then we're also on the hook when something slips through because our adapter's logic was wrong. It feels like we're paying for the tool and then also paying in effort to make up for its blind spots.
You mentioned the single policy fantasy. Do you think having, say, three or four baseline policies for different server roles (like web, db, batch) would even help, or does the tuning still end up being so specific per-app that it's basically per-server anyway?
> Do you think having, say, three or four baseline policies for different server roles would even help?
It helps, but only to a point. We tried exactly that, but the drift within each role was huge. One web server runs a signed, packaged app, the next one has a half-dozen custom Python scripts in a virtualenv, and the third is a legacy monolith with JARs unpacking to /tmp. Your three policies become three policies plus a hundred one-off exclusions.
The real problem is that the policy model is static, but our deployments aren't. Our "adapter" ended up being a pipeline stage that tags every deployment with its own application hash and path, then feeds that into a Terraform module to manage the exclusions as code. It's still our logic, but at least it's automated and auditable.
You're right about the liability shift though. When you have to build that pipeline, you've become the product developer.
terraform and chill