That fingerprinting exception list is where your FinOps nightmare starts. It isn't just operational tax, it's a financial blind spot. You've now got traffic bypassing the metered SASE tunnel, so how are you attributing that bandwidth cost back to the diagnostic terminal team?
I've seen this blow a cloud budget - the local breakout for kiosks meant those massive firmware pulls hit the raw internet egress line item instead of the "all-in" SASE fee. Suddenly, a predictable cost model is gone because you had to work around the product's limitations.
- elle
Spot on. We solved the attribution problem by forcing that breakout traffic through a tiny proxy instance in the same site's AWS VPC. All egress gets a tag for the terminal team. It's a total hack, and now we're paying for compute and data processing just to get a clean bill back.
The real kicker? The SASE vendor's own cost reporting tool can't ingest those proxy logs, so we've got another dashboard to maintain.
cost first, then scale
The 15-device break-even you found lines up with our own math, and it gets even tighter if you factor in power and cooling for those on-prem appliances they're replacing. It's a hidden capex-to-opex win the vendor doesn't always highlight.
>the expensive per-user connections
That's the real killer. We tried prioritizing VOIP traffic within the SASE tunnel, but without a hard bandwidth reservation, it's just a suggestion to the aggregate pool. During a mid-day Teams migration sync from one site, all the executive calls tanked. You can't explain that with "shared cloud economics." We ended up putting a cheap, separate DIA circuit in just for critical apps, which completely undercuts the consolidated cost model.
terraform and chill
Your kiosk example is the perfect case of a vendor metric ignoring actual usage. They sell per-user but track per-device, so you're penalized for operational efficiency.
The bandwidth deception is worse than you think. Even if you stay under the cap, the shared pool means one site's backup can throttle another site's calls. You're paying for 1Gbps but never actually getting it anywhere.
Your fallback plan to offload guest traffic with basic firewalls proves the point. You're adding complexity back in to fix their pricing model. So much for simplification.
If it's not a retention curve, I don't care.
>You're paying for 1Gbps but never actually getting it anywhere.
You're describing the oversubscription model, and it's worse when you consider how they measure. The SLA is for average aggregate throughput, not peak per-site. We saw sustained 700Mbps at one site while another was idle, and the vendor's dashboard showed we were "at 40% capacity" because they were averaging across the entire pool. The performance guarantee is essentially meaningless for any real world burst pattern.
We ended up building a monitoring script to track per-site latency and packet loss before and after the SASE tunnel, just to prove the contention was in their cloud, not our WAN links. The data didn't lie, but it didn't change the contract either.
—davidr
Yep. The predictability of sizing a box for a site is exactly why we moved our warehouse control networks off SASE and back to standalone SD-WAN appliances. We own the burst capacity, no arguments. The cloud firewall for egress and you're done.
The "silent killer" bit on bandwidth is real. We caught our aggregate cap being hit by a scheduled AV update rollout across all sites at once. One global policy nearly took out the entire WAN at 10AM on a Tuesday. You can't fix stupid with an SLA.
That "one global policy nearly took out the entire WAN" is terrifying. Makes me wonder, when you moved the warehouse networks back to SD-WAN, did you keep them completely off the SASE fabric, or is there still some integration point, like for central policy?
Containers are magic, but I want to know how the magic works.
You've hit on the real hidden cost that catches so many teams - the mismatch between the vendor's definition of a "user" and the reality of shared physical devices. We saw this exact scenario with digital signage and meeting room PCs. The finance team's eyes nearly popped out when they saw the proposal to license 50 "users" for a single display that just cycles a PowerPoint.
Your point about offloading guest Wi-Fi is a solid mitigation, but be careful. It introduces a policy gap unless your guest network segmentation is absolutely airtight. You might just be trading a cost problem for a security finding in your next audit.
Architect first, buy later
The shared device licensing problem extends beyond signage. We instrumented our manufacturing floor HMI terminals and found the vendor's agent created a unique session ID for each process running on a single Windows embedded system. One physical machine appeared as 12+ "users" due to services and runtime containers.
That policy gap you mention isn't theoretical. Our guest network offload initially used a separate VLAN with local internet breakout, but we missed that the SASE agent was still installed on some corporate laptops. When those devices connected to guest Wi-Fi, the agent tried to tunnel back via the corporate pathway, creating a routing loop that took down the local firewall. Segmentation must include agent deployment scope, not just network rules.
Our audit flagged this as a control failure: we had two distinct security policy enforcement points (local firewall vs. SASE) with no reconciliation. The cost saving was negated by the labor to implement a proper host-based firewall policy for those guest segments.
Your instrumentation of the HMI terminals reveals a critical flaw in the per-user licensing model. We observed similar behavior with terminal server sessions, where a single RDS host generated a unique user identifier for each disconnected session that the agent perceived as active. This turned a 20-concurrent-user RDS server into 80+ licensed "users" in the vendor's portal, based on session history.
The routing loop scenario is a severe operational consequence of that policy gap. It underscores that segmentation isn't just a network design task; it's a systems management problem requiring agent lifecycle control. We had to implement a GPO to disable the agent service based on a network location detection script to prevent this exact failure mode.