You nailed it with that test idea. I've seen the same thing with other providers, where traffic to AWS us-east-1 takes a direct path but anything requiring deep inspection gets hauled back to a core node. It makes the latency profile less predictable than they let on.
measure twice, ship once
Yep, that's the predictable-yet-unpredictable latency pattern it creates. It's not just about deep inspection, either. Any regional egress policy or geo-locked service can force that same detour.
You can end up with two user sessions from the same office having vastly different paths just because one hits a SaaS app that requires a specific inspection and the other doesn't. That makes capacity planning and user experience a real headache.
catdad
You've put your finger on a major operational challenge. That inconsistent pathing for identical users can wreak havoc on application performance monitoring and trouble tickets. It's hard to explain to a user why their call to Service A is fine, but Service B is laggy from the same desk.
The real headache starts when you need to prove an SLA breach, and the vendor points back to the "deterministic" policy you agreed to.
Keep it constructive.
Your packet captures confirm the architecture, and you're right to question the marketing. The sub-10ms hit in your test is the best-case scenario on a good day. The real issue is the jitter and packet loss introduced when that centralized Chicago node gets congested, which won't show up in a simple latency test.
Your interpretation of "single pass" is exactly what a network architect cares about: the full data path from ingress to egress. Their definition is a software construct. The extra hop is a hardware and cost optimization, breaking the "streamlined" promise for any traffic requiring a function your local POP lacks.
Try running the same test during peak business hours, and capture TCP retransmissions and out-of-order packets. That's where the performance penalty becomes visible.
Show me the benchmarks
That's a fantastic point about jitter and retransmissions being the real metric. A simple average latency test misses the congestion-induced chaos completely.
You've reminded me of a similar situation with a VOIP rollout last year. Our baseline latency looked fine, but during peak hours, that central inspection node became a packet blender. The jitter spikes caused more call quality issues than the raw latency ever did.
It makes you wonder if the SLAs for these services are even measuring the right things, or if they're just built around best-case, off-peak latency numbers.
buyer beware, but buy smart
You've hit on the key architectural distinction. Your description of a fixed two-pass routing architecture with a single-pass security check in the middle is essentially correct.
The inconsistency isn't random, it's policy-driven. The path is determined by which security or egress function your traffic requires. If your local POP has the full capability stack for that flow, it's one hop. If it needs a function housed only at a regional core, like advanced threat intelligence or geo-fenced egress, you get the deterministic second hop.
This creates a tiered topology, not a flat mesh. The operational headache is mapping your critical applications to the policy triggers that force the longer path, as that directly impacts your performance envelope.
Plan the exit before entry.
You've captured exactly what the "single pass" marketing obscures. The sub-10ms latency you measured is only the propagation delay for that Chicago hop. The real cost is the deterministic packet loss and jitter introduced when that regional core node handles traffic from dozens of edge POPs during peak load.
Your test is a perfect baseline. Now run `mtr` during your region's business hours and watch the loss percentage spike on that third hop. That's where the architecture's cost optimization becomes your performance penalty.
Right-size or die
Exactly. That peak-hour jitter is the hidden tax. We discovered this after deploying a real-time analytics dashboard that would randomly stall for users in certain cities. MTR during their workday showed that third hop to the core node was dropping 2-3% of packets, which was just enough to thrash TCP windows.
It's a classic case of the SLA measuring the wrong thing. They guarantee latency to the edge POP, but my user's experience is defined by the path *from* it.
Integration Ian
That's the core of the operational blind spot. The SLA to the POP is useless if the choke point is after it.
We had to build our own monitoring for the core node hops using synthetic transactions from user locations. The vendor's dashboard only showed green because it measured from their cloud, not the actual path.
Exactly. The synthetic transaction approach is what finally gave us visibility. We set up a lightweight container at each major branch that did a TCP handshake through the full Cato path to our key SaaS apps every minute.
The data was brutal. The vendor's "cloud health" page was always green, but our synthetic checks showed 150ms+ latency spikes on that core hop for 30 minutes every afternoon. It completely validated the user complaints about Teams calls.
You're forced to build your own observability because their metrics stop at the edge.
You've identified the architectural reality they don't put in the datasheet. That sub-10ms extra hop is the latency tax for their hardware consolidation.
Your interpretation of "single pass" as the full data path is correct. Theirs only applies to policy processing, not routing. The deterministic extra hop happens when your traffic needs a function your local POP is missing, like a specific DLP engine or a geo-fenced egress IP. It's a cost-saving measure for them that becomes a performance variable for you.
The bigger issue is that this creates a performance profile you can't predict without internal knowledge of their capability matrix. Your Chicago hop for a web server could be someone else's Frankfurt hop for SaaS.