The current evidence rules out sustained CPU/RAM pressure, but it does not yet distinguish a Railway ingress delay from an application process waiting on an I/O dependency. Railway now exposes enough per-request timing to make that distinction without guessing.

Use one slow request ID and build this correlation:

1. In Railway HTTP Logs, filter the affected paths and slow requests, for example:

   • @path:/api/auth/login @totalDuration:>5000
   • @path:/api/forms/:id/publish @totalDuration:>5000 (use the concrete path shown in the log)

   Record @requestId, @responseTime, @upstreamRqDuration, @totalDuration, @edgeRegion, @rxBytes, status and @responseDetails.

2. Add a first-line Express middleware before JSON parsing/auth that logs only non-secret metadata: X-Railway-Request-Id, X-Request-Start, X-Railway-Edge, RAILWAY_REPLICA_ID, RAILWAY_REPLICA_REGION, local receive time, and the finish/close time. Railway documents X-Request-Start as the Unix-millisecond time the request was received and the request ID as the HTTP-log correlation key.

3. Compute Date.now() - Number(req.get('x-request-start')) at that first middleware:

   • A large delta (for example 30-200s) before the first app log, or an HTTP log with no matching app receive log, is evidence of edge/upstream delivery delay.
   • A small delta followed by a long handler duration means the request reached Node promptly; instrument body parsing, auth/session lookup, Mongo connection checkout/query and every outbound HTTP call separately. Low CPU is fully compatible with a blocked socket/pool or an unbounded network wait.

4. From the same client, compare the Railway-provided domain and the custom domain with a unique harmless request while sending X-Railway-Debug: 1. Capture response headers and timings. X-Railway-Edge identifies the ingress POP and the debug response's X-Railway-Upstream-Zone identifies the deployment zone. If slow samples cluster on one POP/path while the same request is fast through another, include those request IDs in the escalation.

5. Log RAILWAY_REPLICA_ID on every request. If all slow samples correlate to one replica, restart/replace that replica and inspect its Mongo/socket pools. If they occur before all replicas equally, the evidence points back to the network path. Keep Socket.IO polling separated from REST by path in the log query; its long-lived requests should not be used to explain away slow REST request IDs.

For the app-side branch, add finite timeouts to Atlas/outbound calls and log Mongo pool checkout duration. A 499 only says the client disconnected; the phase timings above identify what it was waiting for.

This produces the exact support packet Railway can act on: UTC timestamp, request ID, edge region, upstream zone, deployment/replica ID, request-start-to-app delta, HTTP-log timings and whether a matching first middleware log exists. It also avoids another blind redeploy.

Official references:

• https://docs.railway.com/observability/logs
• https://docs.railway.com/networking/public-networking/specs-and-limits
• https://docs.railway.com/networking/edge-networking
• https://docs.railway.com/deployments/optimize-performance