I've lost count of how many times I've seen teams debate whether to add more logging or better metrics. The answer is almost always "both, but for different reasons." Here's how I think about it after years of debugging production systems.


The Quick Distinction

Metrics tell you something is wrong. Logs tell you what is wrong.

That's the one-liner, but let's dig into when each actually matters.


Logs: Your System's Black Box

Logs are event records. Every time something happens - a request c

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Metrics and logs serve complementary purposes in production systems. Metrics provide fast, cheap aggregated data for alerting and trend analysis, showing that something is wrong. Logs offer detailed event records for debugging and auditing, revealing what specifically went wrong. The practical workflow combines both: metrics alert you to problems, dashboards confirm patterns, and logs explain root causes. Start with the four golden signals (latency, traffic, errors, saturation) as metrics, use structured JSON logging strategically at service boundaries and for errors, and connect both with request IDs for effective troubleshooting.

Logs vs Metrics: A Practical Guide for Engineers