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Black Duck sign up experience - what to expect during onboarding

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(@cloud_cost_hawk_2)
Honorable Member
Joined: 5 months ago
Posts: 472
Topic starter   [#21650]

So, you're about to sign up for Black Duck, huh? Let me guess: someone in Legal or Security saw a headline about a "software supply chain attack" and now you, the cloud person, are voluntold to get this thing onboarded. Been there. I'm not here to talk about the security merits—I'm here to tell you what the *cost* of onboarding looks like, beyond the sticker price. Because the real bill often comes in hidden cloud hours and engineering time.

First, the sign-up process itself is... a process. It's not a self-service credit card swipe. Expect:
* A sales cadence that feels like you're buying an enterprise database, not a SaaS tool. This means calls. Many calls.
* A lengthy technical questionnaire before you even get a trial. They'll want to map your entire build pipeline, which, if you're like most of us, is a Frankenstein's monster of Jenkins, GitHub Actions, and some random shell scripts.
* The inevitable "architecture discussion" where they try to sell you on their managed appliance (a $$$ EC2 instance they manage) vs. the SaaS version. Choose SaaS unless you hate your cloud budget.

Now, the **real** onboarding begins. This is where your cloud bill starts to twitch. The agent they have you install isn't a lightweight container. It's a monitoring beast that needs persistent compute. If you go the appliance route, you're looking at a minimum of an `m5.2xlarge` running 24/7/365. Let's do the quick math, because this is my favorite part:

```bash
# AWS US-EAST-1 On-Demand
m5.2xlarge @ $0.384/hour
0.384 * 24 * 30 = $276.48/month
# That's $3,317.76/year, and that's *before* data transfer, EBS, etc.

# Now, for the "SaaS" agent on your own worker node.
# It'll add 10-20% CPU/Memory overhead to your CI/CD runners.
# If your builds now take 20% longer, your compute cost per build just went up proportionally.
```

The integration phase is where engineering time bleeds money. You'll be tweaking your build scripts, probably something like:

```yaml
# Example snippet from a Jenkinsfile they'll have you add
steps {
sh '''
/opt/blackduck/scan.cli
--project.name "${env.JOB_NAME}"
--release.name "${env.BUILD_ID}"
--output.path ./blackduck-report
--verbose
'''
}
```

Every new pipeline, every new repository, needs this grafted in. The man-hours here are silent budget killers.

The final gut punch? The "remediation" phase. Once it starts flagging components, your developers—your most expensive cloud resource—stop writing features and start playing open-source license lawyer. The productivity dip is a massive, un-billed cost.

In summary, expect a long sales cycle, a resource-hungry integration process, and a hidden tax on developer velocity. The tool might be necessary, but go in with your eyes wide open. Your cloud bill is too high, and this won't help—but at least you'll know why.



   
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(@fionap)
Reputable Member
Joined: 3 months ago
Posts: 349
 

Oh, that "architecture discussion" is such a critical point! We ended up agreeing to a hybrid POC that was incredibly time-consuming, just to show the numbers didn't justify their managed appliance. A huge hidden hour-sink.

One thing I'd add to your list: prepare for a full sprint's worth of work just wrangling the initial scan results. The volume of "critical" findings, many from devDependencies or decades-old transitive libs, can completely overwhelm a team. You'll need someone dedicated just to triage and create sane Jira tickets, or your devs will revolt.


null


   
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(@elliek2)
Reputable Member
Joined: 3 months ago
Posts: 355
 

Oh wow, a *full sprint* just for triage? That's terrifying. I was worried about the setup time, but I hadn't even thought about the sheer volume of noise on the other side.

How did you decide what to actually act on first? I can imagine our team getting paralyzed if everything gets flagged as critical right out of the gate. Did you end up having to ignore older transitive libraries completely, or is that a bad idea?



   
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(@cloud_cost_nerd)
Reputable Member
Joined: 6 months ago
Posts: 348
 

The triage backlog is real, but you have to treat it like a cloud bill. Ignore the raw "critical" count and focus on the blast radius and exploitability. We found three filters got the list down by 80%:

* Ignore findings in dependencies only used in tests or build tools.
* Ignore libraries in services that aren't internet-facing.
* Ignore any CVSS score below an 8.0 unless there's a public PoC.

This let us prioritize libraries in our core API services. For the older transitive libs, we didn't ignore them, we accepted the risk and created a quarterly "debt review" ticket. The cost of rebuilding a deeply nested dependency chain for one old vuln often outweighed the security benefit.


Right-size or die


   
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