Metrics Analysis and Monitoring Fundamentals Questions
Fundamental concepts for metrics, basic monitoring, and interpreting telemetry. Includes types of metrics to track (system, application, business), metric collection and aggregation basics, common analysis frameworks and methods such as RED and USE, metric cardinality and retention tradeoffs, anomaly detection approaches, and how to read dashboards and alerts to triage issues. Emphasis is on the practical skills to analyze signals and correlate metrics with logs and traces.
MediumTechnical
0 practiced
Design how to measure and monitor SLIs during a feature-flag rollout. Explain how to partition metrics by flag variation, how to compute per-variation SLIs and error budgets, and how to automate rollout speed (pause/rollback) based on observed SLI degradation while avoiding excessive false positives.
HardSystem Design
0 practiced
Design a scalable architecture to support per-tenant SLIs and error-budget enforcement in a multi-tenant SaaS where tenants have different SLA tiers. Include how to compute per-tenant SLIs at scale (partitioning and storage), how to alert per-tenant, and how to enforce error-budget exhaustion (throttling or degraded mode). Discuss data isolation, cost implications, and fairness for noisy tenants.
EasyTechnical
0 practiced
What are common pitfalls when instrumenting business metrics such as user_signups or purchases? Discuss issues around idempotency (duplicate events), backfills, timezone or locale handling, event deduplication, partial failures in pipelines, and suggest verification approaches to validate correctness of these business metrics after instrumentation.
HardSystem Design
0 practiced
Design an automated incident playbook that uses metric signals to trigger a safe rollback of a Kubernetes deployment when reliability degrades. Specify which metrics and thresholds should be considered (e.g., p99 latency, 5xx rate, pod restarts), how to avoid false positives during rolling deploys, safety checks before rollback (canary checks, cooldowns), testing strategy, integration with on-call workflows, and how rollback actions affect SLO/error-budget calculations.
HardSystem Design
0 practiced
Your Prometheus federation-based architecture struggles with slow cross-cluster dashboards. Propose an improved architecture to deliver low-latency global queries for SLOs and dashboards. Compare federation tuning, remote_write to central TSDB (Thanos/Cortex), query federation layers, and caching or precomputation, evaluating cost, freshness, latency, and operational complexity.
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