I am conducting a preliminary analysis for a global financial application architecture where we are considering consolidating our European user base into a single Prisma Access hub located in Frankfurt. However, a significant portion of our internal users and data sources remain on the US East Coast (specifically, Northern Virginia AWS us-east-1). I am seeking to quantify the inherent latency penalty introduced by Prisma Access's traffic hairpinning in this specific corridor.
The concern is straightforward: a user in London, authenticated via the Frankfurt Prisma Access hub, requesting data from an origin server in us-east-1, would incur the following network path:
`User (London) -> Frankfurt Prisma Access POP -> Origin Server (us-east-1)`.
This is compared to a direct, optimized path like:
`User (London) -> us-east-1`.
My initial back-of-the-envelope calculation, based on public internet light-speed latency, suggests a baseline of approximately 70-80ms for a direct London-to-Northern Virginia path. Routing through Frankfurt could logically add the latency of LondonFrankfurt (approx. 15-20ms) plus Frankfurtus-east-1 (approx. 85-95ms), potentially doubling the RTT.
I am looking for empirical, production-level data from the community. Has anyone performed structured benchmarking or has ongoing monitoring that captures this specific scenario? Vendor-provided "typical latency" figures are insufficient for a performance-sensitive design.
Ideal data points would include:
* **Test Methodology:** e.g., Synthetic ICMP pings, HTTP request/response cycles, or TCP handshake measurements.
* **Source Geography:** Specific city or region of the user/source.
* **Prisma Access Hub Location:** e.g., "Germany" or "Frankfurt".
* **Destination:** Specific cloud region and service (e.g., AWS EC2 in us-east-1, Azure SQL in East US 2).
* **Measured Latency:** Both to the Prisma Access POP (first hop) and to the final destination, highlighting the added latency.
* **Time of Day & Sample Size:** To account for periodic congestion.
For example, a useful benchmark output might look like this (from a hypothetical monitoring script):
```bash
# Direct path from London EC2 instance to us-east-1 RDS
Target: database.us-east-1.rds.amazonaws.com
Min: 72.3ms Avg: 74.1ms Max: 81.5ms Loss: 0%
# Path from same London EC2, via Prisma Access (Frankfurt hub) to same RDS
Target: database.us-east-1.rds.amazonaws.com (via Prisma Tunnel)
Min: 154.8ms Avg: 162.4ms Max: 178.9ms Loss: 0%
Latency Added by Hairpinning: ~88.3ms
```
This data is critical for a trade-off analysis between security posture (single, consolidated inspection point) and application performance. The additional latency directly impacts user experience for real-time applications and influences whether we need to consider a multi-hub architecture or accept the performance tax. Any shared experiences, including the impact of Prisma Access's own network optimizations (like dedicated egress), would be highly valuable.
You're in the right ballpark with those numbers, but the real-world penalty can be much worse than just summed latencies. The hairpin adds a processing penalty at the Frankfurt POP that's variable based on load and traffic inspection profiles. I've seen it add a consistent 8-
15ms on top of the pure network hop in that corridor.
Also, don't forget that the `User -> Frankfurt` leg for someone in London isn't necessarily a clean internet path. It's the corporate VPN tunnel into Prisma Access, which might itself be taking a suboptimal route before it even hits the hub. Your 70-80ms direct baseline is ideal; in practice, I'd start with 95ms as a floor and expect the hairpinned scenario to push 150ms or more for TCP handshakes. For a financial app, that extra 60-80ms on every synchronous request adds up painfully.
APIs are not magic.