The question sounds broad but they immediately start feeding you context as you go, so it becomes a back-and-forth pretty fast.
Structure your answer as a clear, step-by-step incident response process, starting from alert triage and moving through diagnosis, mitigation, and post-mortem. Emphasize communication, prioritization, and a systematic approach to isolate the root cause while minimizing downtime.
Pro tip: Always mention that you would first check if the issue is widespread or isolated, and communicate status updates to stakeholders early and often—this shows you understand the operational and human side of incident response, not just the technical.
Acknowledge the alert, check monitoring dashboards to understand scope and severity, and determine if it's a full outage or partial degradation. Quickly assess impact on users and business.
Notify the incident response team and stakeholders, establish a communication channel, and assign roles if necessary. Provide initial status updates to manage expectations.
Use logs, metrics, and traces to identify the failing component. Check recent changes (deployments, config changes) and dependencies. Narrow down the root cause by testing hypotheses.
Apply the fastest fix to restore service, such as rolling back a deployment, scaling resources, or failing over to a backup. Verify recovery and monitor for stability.
Conduct a blameless post-mortem to identify root cause and action items. Implement improvements to monitoring, testing, and processes to prevent recurrence.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the scenario and constraints, then walk through a systematic triage to identify what's consuming disk space and what can be safely removed or rotated without impacting live traffic. Emphasize safe, incremental actions like log rotation, compression, and cleanup of temporary files, while monitoring system health and having rollback plans.
Pro tip: Mention that you would first check if the disk is truly full or if it's an inode exhaustion issue, and use tools like `lsof +L1` to find deleted files still held open by processes—freeing those can instantly reclaim space without touching live data.
Quickly determine which disk/partition is full, the rate of growth, and what types of files are consuming space (logs, temp files, core dumps, etc.). Use commands like `df -h`, `du -sh *`, and `lsof +L1` to identify large files and deleted-but-open files.
Prioritize files that are not critical to live traffic: old logs, rotated logs, temporary files, cache, and core dumps. Verify with teams or documentation if unsure, and avoid touching active databases or user data.
Safely free space by truncating or rotating logs (e.g., `logrotate -f`), compressing old logs, deleting temp files, and clearing caches. For deleted-but-open files, restart the holding process gracefully or use `> /proc/<pid>/fd/<fd>` to truncate if safe.
Continuously monitor disk usage and system health (e.g., `df -h`, application metrics) to ensure space is freed and no negative impact on live traffic. Be ready to rollback if issues arise.
After resolving the immediate issue, propose long-term fixes like better log rotation policies, monitoring alerts, and capacity planning to avoid future disk-full incidents.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Covered log rotation, disk threshold alerts, and retention policies.
Show a systematic, blameless approach to post-incident analysis: start with immediate mitigation, then conduct a root cause analysis, implement preventive measures, and verify their effectiveness. Emphasize learning and continuous improvement, and tie your actions to reducing mean time to resolution (MTTR) and preventing recurrence.
Pro tip: Meta values a 'move fast' culture but also expects engineers to build durable systems. Frame your answer around turning a one-off fix into a systemic improvement—e.g., automating detection, adding guardrails, and sharing learnings—so the same class of incident can't happen again.
Ensure the incident is fully resolved and document the timeline, impact, and actions taken. This creates a factual basis for analysis.
Use techniques like 5 Whys or Fishbone to identify the underlying causes, not just the trigger. Focus on process and system gaps, not individuals.
Prioritize fixes that address the root cause: add automated tests, improve monitoring/alerting, enhance system resilience, or update runbooks.
Validate that the fixes work through testing or game days, and share the incident report and lessons learned with the broader team to prevent similar issues elsewhere.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.