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I’ve been trying to implement a proper logging strategy for my API service, but I’m struggling with how to structure the log messages themselves. I want them to be useful for debugging without being overwhelming, but I’m not sure what information is essential to include in each log entry.

From my experience, essential fields are timestamp, level, and a clear message, plus a per request id. Then add method, path, status_code, and duration_ms. Include trace_id or correlation_id for distributed traces. Log user_id if you have it, but avoid dumping whole request bodies. Use a structured format like JSON so you can filter later, and log host and environment. Keep error objects around for failures, but don’t sprinkle stack traces in every line.

I added a simple per request id and a duration field on every log line, and switched to structured JSON. It paid off: we could filter by endpoint and see latency trends, and it helped debug failures faster. We also learned to redact sensitive payloads; full bodies in production were a no-go. We kept a separate log path for stack traces when needed.

Is the real problem the volume of logs or the difficulty of searching them for the fault you’re chasing?

Sometimes I drifted into chasing the perfect schema and then realized maintenance would win. So I kept it boring: one line per request, a couple of core fields, and a basic correlation id. Then we added fields only when incidents showed they were truly needed. Not a polished plan, just what stuck after a few weeks.

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