I went straight to dashboards and alerting thresholds and the interviewer kept pushing on 'but how do you know something's wrong before a user tells you.' Had to backtrack and talk through health check endpoints, synthetic probes, and what good on-call rotations actually look like.
Structure your answer around the three pillars: monitoring, alerting, and on-call. Emphasize a proactive, data-driven approach that balances automation with human judgment, and tie it to Meta's scale and reliability expectations.
Pro tip: Show that you understand the trade-offs between sensitivity and noise in alerting, and that you've thought about reducing toil through automation and blameless postmortems.
Explain what metrics you track (e.g., latency, error rates, saturation, traffic) and how you use dashboards and logs to detect anomalies. Mention tools like Prometheus, Grafana, or Meta's internal systems.
Describe how you set thresholds and use anomaly detection to trigger alerts. Emphasize reducing false positives and ensuring alerts are actionable, with clear runbooks.
Outline your on-call rotation, escalation policies, and how you handle incidents. Highlight the importance of clear communication, documentation, and blameless postmortems.
Discuss how you use incident reviews and monitoring data to improve systems, automate responses, and reduce toil. Mention capacity planning and load testing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Pretty conversational, I just walked through error rates, latency spikes, then logs.
Start by describing how you quickly assess impact and scope using monitoring dashboards and alerts, then walk through a systematic triage process from detection to root cause. Emphasize a calm, data-driven approach that prioritizes mitigation and learning.
Pro tip: Mention that you first check if the issue is customer-facing and how many users are affected, because at Meta's scale, even a small percentage means millions of users. This shows you prioritize impact and can communicate effectively under pressure.
Check monitoring dashboards (e.g., Grafana, Datadog) and alerts to determine what's broken, how many users are affected, and whether it's a critical service. Quickly gauge severity to decide if it's an all-hands incident.
Look at recent deployments, configuration changes, or feature flags that might have triggered the issue. Correlate the timing of the break with any changes to narrow down the cause.
Inspect error logs, distributed traces, and metrics for anomalies (e.g., spikes in latency, error rates). Use tools like Splunk, ELK, or Jaeger to pinpoint where failures originate.
If possible, isolate the faulty component (e.g., rollback a deployment, disable a feature flag) to mitigate user impact. Communicate status to stakeholders and incident response team.
After mitigation, perform a post-mortem to identify the underlying cause and prevent recurrence. Document findings and action items.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the scenario (e.g., is it a single request or all requests?) to narrow the scope. Then systematically walk through the layers of the stack—client, network, server, application, and dependencies—identifying likely causes and corresponding diagnostic techniques. Emphasize a methodical, evidence-based approach rather than jumping to conclusions.
Pro tip: Mention that you would first check for recent changes or deployments, as most hangs are caused by recent code or configuration changes. Also, highlight the importance of having proper observability (logs, metrics, traces) in place to quickly pinpoint the issue.
Ask whether the hang affects one user, all users, or specific requests, and check monitoring dashboards for anomalies. This helps determine if the issue is systemic or isolated.
Rule out client-side problems (e.g., browser hang, slow network) by testing from different clients or using curl. Inspect network latency, packet loss, and DNS resolution.
Check server resource utilization (CPU, memory, disk I/O), thread dumps, and application logs for errors or deadlocks. Look for signs of thread pool exhaustion or garbage collection pauses.
Verify if the request is waiting on a downstream service, database, or external API. Use tracing tools to identify slow or hanging calls, and check for timeouts and retries.
Based on evidence, confirm the cause (e.g., deadlock, slow query, network partition) and suggest immediate mitigation and long-term prevention.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Mentioned ps aux, then systemctl list-units, then poking at /etc/init.d for older systems.
Start by outlining a systematic process: first identify listening ports and associated processes, then inspect running processes and services, and finally check logs and configuration for deeper context. Emphasize using standard Linux tools like netstat, ss, ps, systemctl, and lsof, and mention how you'd prioritize findings based on the server's role.
Pro tip: Mention that you'd cross-reference port-to-process mappings with service configurations to avoid false positives, and always consider security implications—like checking for unauthorized services—before making changes.
Use commands like `ss -tulpn` or `netstat -tulpn` to list all listening TCP/UDP ports and the processes bound to them. This quickly reveals exposed services and their PIDs.
Run `ps aux` or `top`/`htop` to see all active processes, focusing on high resource usage or unusual names. Use `pstree` to understand parent-child relationships.
Use `systemctl list-units --type=service --state=running` to see managed services. For older systems, check `/etc/init.d/` or `service --status-all`.
Look at `/var/log/` (e.g., syslog, auth.log) and service-specific configs in `/etc/` to understand what's running and why. Tools like `journalctl` can help.
Map ports to processes to services, and assess criticality based on the server's role. Document findings and flag anything unexpected for further investigation.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Structure your answer by categorizing finite resources into compute, memory, storage, network, and OS-level limits. For each, describe the resource, how it gets exhausted, and the observable symptoms (e.g., errors, latency, crashes). Emphasize that exhaustion often cascades, so monitoring and backpressure are key.
Pro tip: Mention that resource exhaustion is rarely isolated—it often triggers a chain reaction (e.g., memory pressure causing swapping, which spikes CPU and I/O). Showing you understand these interdependencies demonstrates senior-level thinking.
Group finite resources into CPU, memory, disk, network, and OS-level limits (file descriptors, processes, ephemeral ports). This ensures comprehensive coverage.
For each category, describe what exhaustion looks like: CPU saturation (high load, throttling), memory exhaustion (OOM killer, swapping), disk full (write failures), network saturation (packet loss, latency), and OS limits (connection refused, fork failures).
Discuss how exhaustion in one resource can impact others, e.g., memory pressure causing swap I/O, which increases CPU wait and disk usage.
Briefly mention strategies like rate limiting, backpressure, resource quotas, and monitoring key metrics (CPU load, memory usage, disk space, network throughput, open file descriptors).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by acknowledging the non-technical person's perspective and the common pitfalls they face. Then, structure your advice around practical, low-effort steps that prioritize security, reliability, and simplicity. Emphasize using managed platforms and automating backups to avoid overwhelming them.
Pro tip: Recommend they treat their website like a critical business asset: invest in a managed hosting provider with built-in security and backups, and never self-host or manually manage servers unless they want a second job.
Advise them to use a managed hosting service like WordPress.com, Squarespace, or Shopify that handles updates, security, and scaling automatically.
Stress the importance of enabling automatic backups, using strong passwords, and keeping software updated to prevent data loss and hacks.
Encourage them to launch with essential pages (home, about, contact) and avoid over-engineering with unnecessary plugins or features.
Suggest using free tools like Google Analytics and UptimeRobot to track visitors and get alerts if the site goes down.
Advise them to hire a professional for complex tasks like custom development or security audits, rather than risking costly mistakes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.