> 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
The financial penalty clause is the only thing that works. I've written it into two contracts now, but the execution matters more than the clause. You need to lock down the exact test methodology *before* signing, otherwise you're just negotiating against their own synthetic tests during the audit.
My last one stipulated a measurement using our actual user traffic, sampled from five global office subnets, over a 72-hour business period. We captured TCP connect time and time-to-first-byte for our top five most-used API endpoints. When their new São Paulo POP showed less than 3% improvement on those real workflows, the 15% "infrastructure expansion" fee was struck from the invoice. They fought it, but the pre-agreed metrics held up.
The caveat is you need internal monitoring capable of isolating that traffic, otherwise you're relying on their goodwill to run the test, which never happens.
Exactly. I've been running those exact same traceroutes from our three main office locations for the past quarter. The new Denver POP shows up, sure. But when I hit our actual Salesforce instance, the final hop before the SF ASN is still their Ashburn core. The "data center" is just a proxy stop.
The only real improvement I saw was for generic SaaS apps that aren't geo-specific. For anything with a regional backend, the expansion list is just marketing fluff.
pipeline all the things
> generic SaaS apps that aren't geo-specific
That's the core of it. The new POPs are just a fancy CDN for static assets and login pages. The actual business logic and data are still pinned to a few legacy regions.
Your traceroute shows the hairpin. Try timing a real transaction, like `POST`ing a large Opportunity. You'll see the latency spike when it hits that central auth or billing gateway, which they never move.
The list is for sales decks, not for architects.
Simplicity is the ultimate sophistication
Your point about A/B testing against Zscaler or Netskope is the critical comparison most people skip. I conducted that exact test when a vendor announced a new POP in my metro.
The ping times from our office subnet to the vendor's new POP looked competitive, but the full-stack performance for a real Azure SQL transaction was 40ms slower than Zscaler's path from the same origin. The traceroute revealed the new POP had poor peering to Microsoft's network, requiring two extra hops through a Tier 2 carrier. The expanded list gave them a local IP address, but not a locally optimized network.
A longer data center list often just provides more potential points of failure or suboptimal routing. The benchmark shouldn't be their old architecture, but the current best-in-class path from your users to the actual application backends.
Trust but verify.
Your point about measuring real app latency instead of ping times is spot on. I've got the same problem with a recent expansion they announced for APAC. The new Sydney POP cut ping times in half, but the SSL handshake to our Oracle Cloud region in Melbourne added over 100ms. The route from their new data center to the actual cloud provider was worse than the old one.
The "vanity metric" is the raw geographical count. The meaningful metric is the quality of the BGP adjacencies and peering at each new location. Without that, you're just adding another layer of potential hairpinning, as user200's traceroute showed. Their list grows, but the network path to the business data doesn't change.
Mike