Move compute only when the first hop is guilty
The co-location pitch is easy to sell: put the scraper near the proxy gateway and everything gets faster. The practical version is narrower. You move compute when workers are spending real time reaching the gateway, not when the target is slow, the parser has a bug, or the route is getting soft-blocked after the proxy has already done its job.
Split the timing before making any infrastructure decisions. Each worker row should log connect_ms (worker-to-gateway), first_byte_ms (gateway-to-first-byte from target), status, retry count, and bytes billed. A normal row looks like worker=dw-04 connect_ms=21 first_byte_ms=1480 status=200 rows=36 provider_mb=18.4. If moving the worker cuts connect_ms from 90 to 20 but first_byte_ms stays near 1500, the gateway was not the bottleneck.
Keep one variable when testing
Test with the same connection string, target, country route, worker count, timeout, and parser. The only thing that changes between the before and after sample is compute location. If anything else shifts, a route change gets credited to the server move, or a parser fix hides a real regression.
This is boring. It also saves people from buying a machine to solve a problem they never isolated.
Dashboard logs show what the worker counters skip
Worker-side counters report what the application observes: saved rows, successful responses, explicit retries. The proxy network logs show what happened underneath: redirect chains, failed HTTP CONNECT attempts, challenge pages, and every byte the provider metered regardless of whether the worker counted it.
The Usage Logs in the Proxynade dashboard show host, outcome, latency, and byte totals and export as CSV. Comparing those columns against connect_ms and first_byte_ms from the worker log shows whether wasted bytes are coming from the first hop or from the target side. App-level counters usually look cleaner than the bandwidth bill for exactly this reason.
A dedicated server helps when queue jitter is the real problem
A dedicated server starts making economic sense when the job runs long enough for small stalls to become queue problems. Ten Playwright workers competing on a noisy VM can lose hours to tiny waits and half-failed retries without any individual failure looking serious. A dedicated host removes the compute layer as a variable, which makes the remaining failures attributable to proxy class, route quality, or target behavior.
The question is not whether the ping to the gateway is prettier. The question is whether a cleaner host produces fewer worker deaths, steadier queue age, and enough completed records to justify another fixed monthly bill.
Proxy class still decides the target side
Co-location shortens the worker-to-gateway hop. It does nothing for what happens after the gateway. Datacenter is appropriate when the target accepts hosting ranges and throughput matters. Volume Residential at $0.89/GB is the cheaper broad test. Premium Residential at $5.00/GB is where to switch when the cheaper route returns soft blocks, odd body sizes, or retry rates that don't improve with session tuning. Co-location only helps the worker reach the gateway cleanly; each proxy class survives the target on its own terms.
Co-location FAQ
How do I know if the first hop is actually the bottleneck? Log connect_ms and first_byte_ms separately. If connect_ms is high relative to first_byte_ms, the first hop may be guilty. If first_byte_ms dominates, the target or route is the constraint, and moving compute will not help.
What should I keep constant when testing co-location? Same target, same country route, same worker count, same timeout, same parser. Change only compute location. Otherwise a route change or parser fix gets credited to the server move.
Does co-location help with proxy block rates? No. Co-location only shortens the worker-to-gateway hop. Block rates depend on proxy class, exit IP reputation, and request behavior — not which data center the worker runs in.
When does a dedicated server make economic sense for proxy work? When the job runs long enough for small stalls to become queue problems. Browser workers on a noisy VM can lose hours to jitter and partial retries. A dedicated box removes the host as a variable.
How do the proxy usage logs help with co-location decisions? The dashboard network logs show host, outcome, latency, and byte totals. Comparing those against worker-side connect_ms and first_byte_ms shows whether wasted bytes are coming from the first hop or from the target.
Decision checklist
- Log
connect_msandfirst_byte_msseparately before moving anything. - Run the before sample with unchanged route, worker count, and parser.
- Compare dashboard byte totals against worker-side counters.
- Move compute only if
connect_msis the dominant cost. - Track queue age and retry noise after the move, not just ping.