Just finished a 30-day POC with iboss, and the main takeaway wasn't about their threat detection or policy engine—it was about their capacity planning math, or lack thereof. Their sales engineer, who was otherwise quite sharp, provided us with a comfortable-looking estimate for our daily log ingestion. After a week of running in monitor mode across our remote workforce, we were already blowing past that number by a factor of 1.5. By the end of the trial, our average daily volume was double their initial "you'll be fine" projection.
Now, I've been around enough vendor bake-offs to know that underestimation is a classic sales tactic. It makes the initial quote, and the associated cloud subscription costs, look palatable. But with iboss, the delta was significant enough to trigger a full re-scoping exercise. This isn't just a "add a few more dollars" problem; it's a fundamental architecture question. If their modeling is off by 100% on something as basic as log generation, what does that imply about their understanding of traffic patterns, concurrent connections, or peak load scenarios?
A few specific pain points we cataloged:
* The "enhanced" logging features, which you need for any useful forensics, are absolute data firehoses. Every DNS query, every packet inspection, with full URL and user context, adds up faster than they let on.
* Their data retention and real-time reporting seemed to strain under the actual volume. Dashboards that loaded snappily in week one were noticeably sluggish by week three.
* This directly impacts the TCO. Their pricing is very much tied to data and features. A 2x ingestion miscalculation doesn't mean a 2x cost increase—it's often a tier jump, which comes with a whole new set of minimum commitments and overage fees.
The product itself did what it said on the tin. The ZTNA stuff worked, the filtering was robust. But the operational and financial surprise here is a deal-breaker for any organization that doesn't have a blank check for security. My advice to anyone running a trial: instrument your own data collection from day one. Don't rely on their pre-sales estimates. Assume their numbers are optimistic by at least 30-50%, and build your own model based on actual traffic samples.
Otherwise, you'll be back here in a year writing a post about the painful and expensive process of re-architecting your cloud security stack because the bill became unsustainable. Seen it too many times.
-- Carl
Test the migration.