Monitoring, Logging, and Operational Visibility Questions

Understand that running systems need constant visibility. Know basic monitoring concepts: metrics (numerical measurements like CPU, memory, request count), logs (detailed event records), and alerts (notifications when issues occur). Know the monitoring tools: CloudWatch (AWS), Azure Monitor (Azure), Cloud Operations/Stackdriver (GCP). Understand what should be monitored: application health (uptime, error rates), infrastructure health (CPU, memory, disk), and security events (access logs, permission denials). Know that proper monitoring enables quick issue detection and troubleshooting. Be familiar with dashboard creation (visualizing metrics) and alert configuration (notifying on problems). Understand log aggregation—collecting logs from multiple sources for centralized analysis.

HardBehavioral

66 practiced

Using the STAR method, describe a time you led an initiative to improve monitoring and reduced incident volume or mean time to resolution. Explain the Situation and Task, the concrete Actions you led (technical and organizational), quantifiable Results, and one thing you would do differently in hindsight.

HardTechnical

64 practiced

Create a fault-injection and chaos engineering plan to validate alert coverage for a distributed payment service. Define experiments (network partition, DB latency, dependency failures), the expected monitoring signals for each experiment, blast radius controls, automation steps to run experiments safely, and metrics to measure improvement in detection and response.

EasyTechnical

50 practiced

Describe the purpose of dashboards in operational visibility. For three audiences (on-call SRE, application developer, and product manager) provide 4–6 panels or metrics each dashboard should show. Explain design choices that prevent misleading visualizations and ensure dashboards remain actionable.

HardTechnical

71 practiced

Write an advanced CloudWatch Logs Insights query (no full solution required here; describe the approach and provide the key query steps) to detect sudden changes in user-agent distribution over the last 72 hours. Assume logs are in combined format. Describe how you'd compute hourly distributions, a moving baseline, and flag significant deviations.

EasyTechnical

69 practiced

Given Apache combined log lines stored in CloudWatch Logs, write a CloudWatch Logs Insights query to find the top 10 client IP addresses generating HTTP 5xx responses in the last 24 hours. Assume log lines look like: '127.0.0.1 - - [date] "GET /path HTTP/1.1" 500 1234 "-" "user-agent"'.

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