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Troubleshoot a website outage with disk full

Last updated: Mar 29, 2026

Quick Overview

This question evaluates operational incident response and systems troubleshooting skills, including understanding of disk/storage behavior, log and metric analysis, and architecture-level impact assessment within the Software Engineering Fundamentals domain.

  • medium
  • Meta
  • Software Engineering Fundamentals
  • Software Engineer

Troubleshoot a website outage with disk full

Company: Meta

Role: Software Engineer

Category: Software Engineering Fundamentals

Difficulty: medium

Interview Round: Technical Screen

You are on-call for a production web service. Users report the website is down (timeouts/5xx). You are told the incident turns out to involve **a full disk** on one or more machines. Walk through how you would: 1. Triage and confirm impact/scope. 2. Identify the failing component(s) and the immediate cause. 3. Debug “disk full” deeply (what to check next and why). 4. Mitigate quickly and safely. 5. Prevent recurrence (monitoring, alerting, operational changes). Assume a typical setup (load balancer → web/app tier → DB/cache; logs/metrics available). Explain what commands/signals you would look at, what hypotheses you would test, and what pitfalls you’d avoid.

Quick Answer: This question evaluates operational incident response and systems troubleshooting skills, including understanding of disk/storage behavior, log and metric analysis, and architecture-level impact assessment within the Software Engineering Fundamentals domain.

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Meta
Jan 5, 2026, 12:00 AM
Software Engineer
Technical Screen
Software Engineering Fundamentals
1
0
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You are on-call for a production web service. Users report the website is down (timeouts/5xx). You are told the incident turns out to involve a full disk on one or more machines.

Walk through how you would:

  1. Triage and confirm impact/scope.
  2. Identify the failing component(s) and the immediate cause.
  3. Debug “disk full” deeply (what to check next and why).
  4. Mitigate quickly and safely.
  5. Prevent recurrence (monitoring, alerting, operational changes).

Assume a typical setup (load balancer → web/app tier → DB/cache; logs/metrics available). Explain what commands/signals you would look at, what hypotheses you would test, and what pitfalls you’d avoid.

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