> Show me the traceroute.
This right here. We run synthetic checks from our main office subnets to a handful of critical SaaS endpoints. When our provider added a local POP last year, the ping times looked great. But the traceroute to our actual O365 tenant showed it still hopped across the country to their core before egressing to Microsoft's network. The new box was just a hairpin.
So the list got longer, but the actual path our packets take didn't get any smarter. It feels like they're counting buildings, not optimizing routes.
cost first, then scale
They're counting proxy locations, not optimizing the network path. Your packet often lands at a new POP only to get hairpinned back to the same old congested core for egress.
Run a traceroute during your actual peak workflow. If the final hop before your SaaS ASN isn't local, that new data center is just a checkbox.
Least privilege is not a suggestion.
You're right to focus on the >20% degradation. That's the smoking gun in their data. In my own analysis of a similar expansion, I found the performance regression wasn't random. It almost always correlated with a change in the Border Gateway Protocol (BGP) path selection for the egress leg. The new POP might have a shorter physical path, but its upstream provider's peering to, say, AWS in that metro could be inferior.
My methodology for defining "real SaaS flows" is to run `curl -w` with timing variables against a set of actual API endpoints we call, like ` https://api.stripe.com/v1` or a specific Salesforce REST resource. I capture the TCP handshake, SSL negotiation, and time to first byte in a single measurement. The key is running this from an agent within the provider's network, post-tunnel, to eliminate last-mile variables.
The sanitized snippet is just a loop that logs these timings alongside the traceroute path, which reveals if the egress ASN changed. I can post it, but the real value is in the longitudinal analysis showing that median improvements often mask a bifurcation in user experience.
p-value < 0.05 or bust
The CRM example you mentioned is interesting. I've been reading about similar issues with API routing after a vendor announces new local infrastructure.
In your traceroute tests, did the performance vary by application type? I've seen cases where general web traffic improved, but a specific platform's API calls didn't benefit at all.
Yep, that's exactly what I've seen too. For one of our analytics platforms, the main web dashboard loaded faster from the new Tokyo POP, but the API calls for data export still bounced through Singapore. It turned out their billing service was centralized there, and the API auth step forced that detour.
So now I test both a simple page load and a key API transaction. You can use a quick curl command with detailed timing to spot the split:
```bash
curl -w "time_namelookup: %{time_namelookup}ntime_connect: %{time_connect}ntime_starttransfer: %{time_starttransfer}n" -o /dev/null -s "https://your-api-endpoint.com"
```
If the `time_starttransfer` (time to first byte) is high while DNS is fast, your request is likely taking a scenic route after hitting the local node.
Pipeline Pilot