Backend Engineering
Observability
6 practice questions. Free questions open a full answer guide; the rest unlock with Pro.
- Your on-call is drowning in alerts — CPU spikes, a pod restarting, a queue depth crossing a threshold — most of which resolve themselves and don't correspond to anything users noticed. How would you redesign alerting around SLOs so the pages that fire are the ones worth waking someone for?
- When a request passes through several backend services and something goes wrong, why is it hard to find the relevant log lines, and how do correlation or trace IDs and structured logging help?Go Pro
- A user reports that one of your API endpoints is intermittently slow, but it calls through five downstream services and you can't reproduce it locally. How would you use the three pillars of observability — logs, metrics, and traces — to find where the time is going?Go Pro
- Your team adds a request_id and customer_id label to a Prometheus metric so you can slice dashboards per customer, and a few weeks later your monitoring backend starts running out of memory and queries time out. Explain what went wrong and how you'd fix the metrics design.Go Pro
- People often describe observability as logs, metrics, and traces. What does each of those tell you, and how do they work together when you're debugging a production issue?Go Pro
- How do you ensure a new feature is properly observable in production before and after launch?Go Pro
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