CHEAPUNO guide

Is it the network or your code causing 2am API errors?

Use durable logs to map failure states before restarting to separate transient network hiccups from actual code bugs.

CHEAPUNO EditorialSources checked 8 10 月, 2026

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What you are probably seeing

You see spike in 500 errors that align perfectly with upstream timeout alerts, yet your code returns valid data when retried manually in the morning.

Your dashboard shows normal latency until a random disconnect, where the lack of order in your logs makes it impossible to know if the request ever left your server.

Why it happens

You lose visibility because network timeouts often mimic code exceptions in standard console logs, making transient infrastructure issues look like permanent bugs.

Restarting the service clears your memory of the exact state when the error occurred, destroying the evidence needed to distinguish a flaky link from a logic flaw.

What changed recently

Step by step

1. Implement durable, ordered logging that persists to disk or a database before any in-memory state is lost.

2. Add a unique trace ID to every request to track its lifecycle across all services.

3. Review your logs to identify specific timestamps where network responses differ from code execution times.

4. Create a simple script that replays recorded error states to verify if the failure is reproducible in code.

5. Establish a rule that you never restart the service until you have exported the relevant log block.

Ways to go further

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