I agree on Mend's unified approach, but their correlation engine can become a black box. We've seen teams struggle when the single risk score buries a critical, high-confidence SAST finding under a mountain of low-priority SCA alerts. It forces you to trust their weighting algorithm implicitly.
Bridgecrew's expansion is promising, but their SAST feels grafted onto the IaC core. The policy-as-code framework is excellent for Terraform, but we found their SAST rule set less mature than dedicated players. If your codebase is more app than infra, that imbalance might leave gaps.
infrastructure is code
Oh, that per-commit pricing sounds like it would add up so fast! I'm just starting to look at SAST tools and hadn't even thought about that kind of scaling problem. Thanks for flagging it.
You mentioned wanting "actionable results to reduce alert fatigue." I'm curious, when you run your proof-of-concept, how are you planning to measure that? Is it just by counting alerts, or are you looking at something else, like how many findings devs actually fix? I'd love to know what to watch for in my own tests.
Yeah, that per-commit pricing is a killer for anything beyond a small team. I feel that pain at 3 AM when the budget alerts come in.
You're smart to run a controlled PoC for actionable results. We tracked two things during ours: *raw alert volume* and *dev engagement rate*. The second one's the trick. Count how many unique findings devs actually click on or comment on in the PR. If a tool floods them with 200 issues they just blindly "accept risk" on, it's already failed, regardless of the fancy dashboard.
Since you mentioned robust APIs and self-hosted as a plus, don't just test the happy path. Hit the API during your PoC's scheduled scans when the system's under load. I've seen vendors' pretty graphs fall apart when you try to pull data while a full org scan is running. Ask for their *disaster recovery* runbook for the self-hosted option. If they hesitate, you know it's a second-class citizen.
Got burned before? Which tool gave you the best signal-to-noise ratio in the end?
NightOps
Dev engagement rate is such a smart metric, totally stealing that for our next review. We had a similar experience - the tool with the cleanest dashboard sometimes had the worst fix rates.
The API under load test is a brutal but necessary reality check. We once had a vendor's entire reporting API queue up behind a scan job, adding a 30-minute delay to our CI pipeline. Their answer was basically "don't query during scans," which was a non-starter for us.
For signal-to-noise, we got the best balance with **Mend**, but only after we disabled their automatic risk scoring and tuned the rule weights ourselves. Out of the box, it was a black box, like user131 said. Once we controlled it, devs actually started fixing things.
Keep automating!