Design and operationalize systems and processes that deliver efficiency, cost effectiveness, and resilient service delivery. Cover approaches to cost optimization and right sizing, automation and self healing, monitoring and observability, service level objectives and agreements, incident response and disaster recovery planning, chaos engineering and resilience testing, capacity planning, and continuous improvement practices. Candidates should explain trade offs between cost and reliability, instrumentation and alerting strategies, and how to measure and improve operational maturity.
MediumTechnical
0 practiced
Describe how you would coordinate a major incident that involves an external vendor, legal, and communications teams. Focus on escalation paths, secure information sharing, joint triage procedures, regulatory and disclosure considerations, and customer messaging alignment across multiple organizations.
MediumSystem Design
0 practiced
Design SLOs for a payment processing API. Define three SLIs (e.g., request latency P95, successful payment rate, and end-to-end processing time), propose concrete targets and measurement windows, and explain how you would set and enforce error budget policies (e.g., release blocking, mitigations when budget burns).
MediumTechnical
0 practiced
Design an automated remediation workflow that detects sustained CPU spikes on compute instances or containers and performs safe remediation actions (scale, restart, or throttle). Include detection thresholds, decision rules mapping observations to actions, safeguards to prevent thrashing or cascading restarts, audit logging, and rollback strategies.
MediumTechnical
0 practiced
Design a log retention and tiering policy for a system producing ~50 TB of telemetry per day. Include hot/warm/cold tiers, index vs raw retention strategies, sampling for high-volume events, compliance-driven retention needs, cost estimation approach, and how searchability SLAs differ across tiers.
MediumTechnical
0 practiced
Design a chaos engineering experiment to test database leader failover in a leader-based replication system. Include the hypothesis, steady-state metrics, blast radius controls, pre-checks, automation steps to trigger failover, post-failover validation checks (both functional and data integrity), and rollback criteria.
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