You mention the fixed cost across three regions. That's interesting, is that latency floor the same even if the regions are peered directly? Or does it go up when traffic has to cross their backbone?
The business process angle someone mentioned earlier seems key. That "bad toll bridge" cost isn't just technical, it's financial on every renewal when the core experience stays slow.
Trying to figure it out.
That CLI example really hits home, it's exactly what made me pause when I was learning the platform last month. That three-step dance for a simple app feels like building with Lego blocks when you just need a single brick.
Your benchmark of 12-18ms overhead is a number I can use. Does that hold true even with their private edges, or does it get worse if you're crossing regions? I'm trying to plan for a microservices setup and that kind of fixed tax makes some patterns impossible.
Containers are magic, but I want to know how the magic works.
Glad that latency number is useful for your planning. That 12-18ms tax is persistent across their public edges in my tests. For private edges, the story can be a bit different.
It often gets worse with cross-region hops, not necessarily from the raw distance, but because of how their broker logic gets tangled in their own backbone routing. The inconsistency is the real problem for microservices. If you're planning for any synchronous, chained calls, that fixed floor gets multiplied across each hop, and the variance in the 95th percentile can cause cascading timeouts.
You mentioned learning the platform. That initial CLI friction is a huge red flag because it doesn't scale with your knowledge. You just end up building a layer of automation to hide their platform's seams, which is extra work you shouldn't own.
catdad
That's a critical observation about the extra work to hide platform seams. It's not just initial setup, it's ongoing maintenance. Every time they update an API or change a flag, your custom automation becomes a liability that needs testing and patching, effectively outsourcing their QA to customers.
You also hit on the microservices cascade risk. That multiplicative latency across chained calls turns their fixed cost into a variable one for your architecture. It makes any distributed tracing data noisy at best and misleading at worst, because so much of the delay is introduced in their opaque broker layer.
Yep, that CLI process is a classic symptom. I built a wrapper script too, but then they changed a flag name in the last update and broke it all. The "simpler admin" they need isn't more UI paint, it's a consolidated backend API.
Also, seeing that same 12-18ms tax on private edges? That's the real proof it's architectural. Means it's baked into their broker's packet path, not just network distance. Makes you wonder what the IoT feature will add on top of that baseline.
measure twice, ship once
Exactly. That broken wrapper script is pure financial waste. My team billed hours for maintenance that should've been spent on actual features.
If the 12-18ms floor is consistent on private edges, it's a tax on our internal traffic, which is unacceptable for the cost. It kills the ROI case for moving internal apps behind it. You're paying for latency twice - once in license fees, once in degraded app performance.
I'd be less concerned about what IoT adds on top, and more about what they're *not* fixing underneath.
—hd
That's a really good point about the double cost, paying for the license and then getting slower apps. I hadn't thought of it as a direct hit to the ROI calculation like that.
When you mention the wrapper script being a waste, does that mean you've given up on automating their CLI? I've been trying to write some Python scripts to handle provisioning, but after reading this thread I'm worried I'm just building a house of cards that'll break on the next update.