The staged template adaptation is pragmatic, but it's a workaround for a problem Palo Alto should quantify. You're right to question the CDN analogy. A code deployment validates once and distributes artifacts. Prisma rebuilds the artifact at every PoP from a centralized spec, which is a fundamentally slower pattern.
That's the real bottleneck, not just scale. If identity changes take twice as long, it suggests their dependency resolver for that subsystem is inefficient or single-threaded. Has anyone seen Palo Alto publish a breakdown of where those 20 minutes are actually spent? I doubt it.
Data skeptic, not a data cynic.
You're definitely describing the main trade-off we've all found. That 20 minute wait feels exactly like what we see when testing new app integrations too.
Your last question about scaling with rules or locations is interesting. In my limited monitoring, the number of active rules matters less than the type of object you change. Tweaking a port in an isolated rule is much faster than modifying a global object, like a shared address group used in many policies. It seems to be more about dependency complexity than pure rule count.
Have you noticed if the delay changes based on the time of day you push? I'm curious if cloud load plays a role, or if it's purely a static processing time.
You're spot on about the dependency check being the real culprit, not the distribution. That staging template approach is key for preserving sanity.
I'd add that it's crucial to differentiate between a change that affects a specific location template and one that hits a shared object in the GlobalProtect or mobile user template. The latter always triggers that cascading validation across the whole system, which is where you'll see those 20-minute spikes, even in a staging stack. Staging helps you identify which type of change you're about to make.
Stay curious, stay critical.
You're right, they'll never publish a breakdown. The cost would be in exposing just how much of that 20 minutes is redundant work.
The "rebuilt at every PoP" pattern you described is spot on. It's not a true distribution of a compiled artifact; it's a re-compilation at each edge node from the same central source. That's why a simple port change in an isolated rule can still take a few minutes - every PoP still runs its own validation pass, even if the outcome is identical.
I suspect the identity subsystem delay is less about single-threading and more about the sheer breadth of the dependency graph it has to traverse. But without transparency, we're all just guessing.
Every dollar counts.
Exactly, the lack of artifact distribution is the architectural flaw. The cost isn't just in redundant processing, it's in the inability to version or roll back a compiled policy state. You're forcing every node to recalculate the same result, which introduces massive coordination overhead that a true distribution system would avoid.
I disagree on the identity subsystem delay being solely about graph breadth, however. If it were just breadth, the scaling would be more linear. The fact it's multiplicative suggests their dependency resolver isn't caching intermediate states effectively. Each PoP is likely traversing the same massive graph from scratch, not just evaluating a final, pruned set of changes.