Explain metrics, logs and traces. How does each help you run a cloud application?
What the interviewer wants to hear
- Metrics are numeric time series, cheap to store, good for dashboards and alerts
- Logs are detailed event records, good for debugging specific errors
- Traces follow one request across services and show where time is spent
- Use them together: alert on metrics, then drill into traces and logs
- Tools such as CloudWatch, Prometheus, Grafana and OpenTelemetry
Model answer
Metrics are numbers measured over time, like request rate, error rate, latency and CPU. They are cheap to store and query, so I use them for dashboards and alerts, for example in Prometheus with Grafana or in CloudWatch. Logs are detailed records of individual events, such as an error with a stack trace and request ID; they answer what exactly happened. Traces follow a single request as it moves through load balancers, services and databases, and show how long each step took, which is the fastest way to find a slow dependency in a microservice system. They work best together: a metric alert tells me the error rate jumped, a trace shows which service is failing, and that service logs explain why. I usually instrument with OpenTelemetry so all three share the same request context.
Can you answer it under time pressure?
Take a timed easy round and get scored on every answer.
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