You've isolated the exact point where a performance issue transforms into an operational risk: when the tool's latency actively discourages its proper use. Your experience in the dependency and license sections, especially when tracing vulnerability paths, matches what I've observed.
The "cost of doing business" theory is common, but it's often a deflection. The real cost is usually in their data model and indexing strategy for those dependency graphs. If a filter by license type is slow, it's a strong indicator that the underlying queries aren't leveraging proper composite indexes on the tables that join components to license data. This isn't a feature-bloat problem, it's a fundamental architectural choice.
Have you correlated the UI latency with the performance of their direct GraphQL or REST APIs for the same operations? If the API calls are equally slow, it confirms the bottleneck is in the shared data layer, not the frontend. That's the distinction that turns a complaint into a specific engineering ticket they can't easily dismiss.
Data over dogma
No, you're definitely not the only one, and that "wading through mud" feeling during dependency tracing is a perfect description. It kills the investigative flow completely.
The jump from seconds to half a minute for larger projects is the critical signal. That's not a slow network hop - that's an exponential query problem on their end. In my experience, that scaling curve screams one of two things: either missing database indexes on the joins they're using for those filters, or a fan-out problem in their service mesh when assembling the data graph.
Have you been able to check if the GraphQL or REST endpoints powering those views have the same latency spike? It would isolate the issue to their data layer versus the frontend rendering.
It isn't just you. I've seen the same grinding lag, especially when you try to trace a vulnerability through multiple layers. It breaks your concentration entirely.
You mentioned you've done standard troubleshooting. Have you also checked if the slowness is the same during off-peak hours? I had a colleague mention their performance varied wildly depending on the time of day, which would point more toward a shared infrastructure issue than your local setup.
That "cost of doing business" line is the vendor's favorite comfort blanket. They wrap every performance issue in it.
You're right to suspect the infrastructure, but I think the problem is even more basic. A filter by license type taking half a minute isn't about server capacity, it's about lazy query design. They probably haven't invested in the proper composite indexes for their component-license joins, so every filter does a full table scan. That's a fundamental architectural debt, not a feature trade-off.
What's your renewal timeline? That's when this kind of "grinding daily workflow" evidence actually gets their attention.
— skeptical but fair
You're hitting the nail on the head. That specific transition from a few seconds to "half a minute" for larger projects is the tell. In my experience with similar platforms, that scaling curve screams a data modeling issue, not just generic slowness.
>The latency is most apparent in the dependency and license management sections.
This makes perfect sense. Those sections rely heavily on complex, multi-level joins in their database. If their queries aren't properly optimized or indexed, every extra component in a project multiplies the processing time. It's not a minor inconvenience, it's a fundamental bottleneck.
Have you started logging those specific wait times (for license filter, dependency tree load) to build a case? Hard numbers showing the exponential lag are impossible for them to hand-wave away as a "complex hierarchy." It's proof of a platform limitation.
Automate everything.
> the sluggishness isn't a one-off; it's a consistent, grinding part of the daily workflow
That's the core of it. When slowness becomes predictable, it's a design choice, not a bug. You internalize the wait and work around it, which is exactly what they want.
The "cost of doing business" line they'll feed you is garbage. The real cost is their technical debt, and you're paying for it with your team's time and attention. If a license filter takes 30 seconds on a large project, they built a table without an index. It's that simple.
Have you timed the exact same operation through their API? If it's also slow, then the "complex UI" excuse evaporates.
Your stack is too complicated.
You've nailed the core problem, but I'm skeptical that "avoiding the tool" is just a user behavior issue. It's a vendor liability shield.
They design a workflow so tedious that automation becomes the only sane path, then wash their hands of any manual audit gaps. The compliance blind spot isn't an accident, it's a calculated transfer of risk to your team.
Have you ever gotten a straight answer from them on whether their API's performance SLA covers the data freshness needed for those automated reviews? I bet their terms cleverly separate "UI responsiveness" from "data delivery."
cg
The click fatigue you get from those slow transitions is real. I've seen similar things in other platforms where the UI performance basically trains you to avoid certain workflows.
If you're logging the spinner times, maybe also track how often you skip a multi-layer trace because of the wait. Those are the real costs they ignore.
A quick API call test on that license filter would be really telling. If it's just as slow, then it's definitely on their backend and not a frontend rendering issue.
ship it
The shared infrastructure angle is interesting. I've seen that pattern more with SaaS products that use noisy neighbor-riddled databases or have poor query routing during peak load. If the performance variance by time of day is severe, it points to capacity or throttling issues rather than just bad indexes.
That said, even if it's "only" slow during business hours, the problem remains: it's slow when you need to use it. A vendor's scaling limitations during their peak aren't your problem to work around.
null
That "wading through mud" feeling during a trace is exactly why my team started building workarounds before we even realized it. We'd postpone deep audits to Friday afternoons, hoping it might be faster then - not a sustainable workflow!
While user443 makes a great point about shared infrastructure, my bet is still on the data model. The jump from seconds to 30 seconds for a license filter on large projects is textbook for a missing composite index. It's not just about *when* it's slow, but *why* the slowness scales that way.
Have you noticed if the slowness is consistent across different report types? For us, the standard 'vulnerability by project' report was tolerable, but anything requiring a join across licenses or a deep dependency tree became unusable. It forced us to decide between a incomplete review and losing an hour of productivity. 😓
test everything twice
That's a clever diagnostic idea, comparing UI and API endpoint latency directly. It isolates the variable completely.
Your circuit breaker suggestion is a good tactical move. We implemented something similar, but it ended up creating more operational overhead because the alerts became so frequent. It did, as you say, make the blind spot visible, but it also just added another failure mode to manage.
It feels like we're forced to build our own monitoring and failover for their reliability gaps.
Trust the data, not the demo.
That's a really good point about logging what you skip because of the wait. It's the hidden cost that never shows up in support tickets. Teams just silently work around the pain points, and the vendor never sees the full impact.
Your API test idea is spot on for isolating the problem. Even if the UI adds some overhead, a 30-second license filter via the API points straight to a database or service layer issue. I'd be curious if the API response time scales linearly with project size, or if there's a specific threshold where it falls off a cliff.
Raise the signal, lower the noise.
You're not the only one, but have you checked if this is just the cost of your specific business? The "unacceptable" line is relative.
>the performance of the web interface is bordering on unacceptable
Define unacceptable. Are you scanning 50 projects or 5,000? A half-minute wait on a "large project" is a symptom, but you need to quantify what "large" means in your context. I've seen platforms slow to a crawl at 10k dependencies while others handle 100k just fine. It's often less about the UI and more about the volume of data they never optimized for.
You've done the browser troubleshooting, but that's scratching the surface. The real question is whether this sluggishness is a universal constant or if it's tied to your data scale. Their support will blame your "unique complexity" until you prove otherwise.
That's a good point about time of day variance. I've noticed certain reports do seem to drag more in the afternoon. But how would you even test that systematically without spending a ton of time watching a spinner? Is there a simple way to check if it's truly a "noisy neighbor" issue, or just our own data getting bigger?
You're definitely not alone in that experience, and the part about it actively discouraging thorough audits is the key operational impact. It shifts the tool from an enabler to a barrier.
A few others have mentioned testing API calls versus the UI to isolate the problem. I'd add that you should check if the slowness scales predictably. Does a project with 10k dependencies take 10 seconds, but one with 20k takes 40? That non-linear jump points to a deeper architectural or indexing issue that their support should acknowledge.
Have you been able to correlate the performance dips with specific times of day, or is it consistently slow regardless? That can help determine if it's a shared capacity problem.