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Reliability, Observability, and Incident Response Questions

Covers designing, building, and operating systems to be reliable, observable, and resilient, together with the operational practices for detecting, responding to, and learning from incidents. Instrumentation and observability topics include selecting and defining meaningful metrics and service level objectives and service level agreements, time series collection, dashboards, structured and contextual logs, distributed tracing, and sampling strategies. Monitoring and alerting topics cover setting effective alert thresholds to avoid alert fatigue, anomaly detection, alert routing and escalation, and designing signals that indicate degraded operation or regional failures. Reliability and fault tolerance topics include redundancy, replication, retries with idempotency, circuit breakers, bulkheads, graceful degradation, health checks, automatic failover, canary deployments, progressive rollbacks, capacity planning, disaster recovery and business continuity planning, backups, and data integrity practices such as validation and safe retry semantics. Operational and incident response practices include on call practices, runbooks and runbook automation, incident command and coordination, containment and mitigation steps, root cause analysis and blameless post mortems, tracking and implementing action items, chaos engineering and fault injection to validate resilience, and continuous improvement and cultural practices that support rapid recovery and learning. Candidates are expected to reason about trade offs between reliability, velocity, and cost and to describe architectural and operational patterns that enable rapid diagnosis, safe deployments, and operability at scale.

MediumSystem Design
53 practiced
Design a canary deployment strategy for a Kubernetes-hosted stateless microservice handling 1000 RPS. Specify how you'd shift traffic over time, what health metrics and thresholds gate promotion or rollback (both system and user-facing), how to automate the gates in CI/CD, and how to handle database migrations or schema changes safely during a canary.
EasyTechnical
49 practiced
What is a correlation ID and why is it important in distributed systems? Describe how you would implement correlation ID propagation across HTTP, gRPC and message-queue boundaries in a polyglot environment, how you would surface the ID in logs and traces, and how you would handle legacy services that do not forward headers.
MediumTechnical
69 practiced
Compare blackbox (synthetic) and whitebox (application-internal) monitoring. Propose a synthetic monitoring strategy for a globally distributed system to detect regional outages and degraded user experience: where to place probes, what user journeys to exercise, probe frequency, and which metrics to track to detect regional degradation quickly.
HardTechnical
63 practiced
An incident analysis shows repeated client retries caused cascading overload and resulted in duplicate records in a downstream system. Analyze likely root causes and propose architectural and operational mitigations: idempotency tokens, deduplication windows, transactional outbox pattern, backpressure and circuit breakers. Explain trade-offs for each mitigation.
MediumTechnical
68 practiced
Describe how you'd implement an automated enforcement policy for error budgets across teams: when burn rate exceeds thresholds, restrict risky rollouts and throttle non-essential background jobs. Explain how you would surface budget consumption in dashboards, who owns approval for overrides, and how enforcement integrates with CI/CD or feature-flag tooling.

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