Trace any request to the exact step that failed, then debug it with real production inputs.
A request just failed. What did the system do? Most stacks answer three layers down, in container logs and metrics, and leave the correlation to you. As AI writes more of your logic, “nobody knows what it does” stops being a figure of speech.

Every API request, recorded: inputs, outputs, timing, and the path it took through your logic.

Because Xano runs the whole backend, a trace lands on the failing function and step—not on a container ID you then have to correlate by hand.

Every recorded request carries its real production inputs. One click re-runs them through the debugger and steps the stack, statement by statement.

Every change is attributable: who changed it, when, on which branch, and what the change was. The evidence trail your reviewers and auditors follow.

Errors are grouped by signature and mapped to the release that introduced them, so you can tell what's new from what's always been there.

Agent runs emit OpenTelemetry, so your agent activity is traceable like any other workload.
The same visual system your team reads while building is the one they read in production. The engineer traces the failure; the reviewer checks what policy held; nobody pages through raw logs to answer “what happened?”

Watching the application is half the job.
Autopilot watches the infrastructure underneath: clusters rightsized for cost, services kept resilient, without growing the DevOps team.
All your services on Autopilot