Fault Tolerance and System Resilience Questions

Designing systems to anticipate, tolerate, contain, and recover from component and network failures while minimizing customer impact and preserving correctness. Topics include identifying common failure modes and single points of failure, redundancy and isolation patterns at hardware, service, and geographic levels, and failover strategies including active active and active passive. Cover retry policies with exponential backoff, timeouts, circuit breaker and bulkhead patterns, graceful degradation, rate limiting, and backpressure techniques to protect systems during overload. Discuss orchestration of node rejoin and state rebuild, replication strategies and consistency trade offs, leader election and consensus implications, and techniques to avoid and mitigate split brain. Explain monitoring, health checks, alerting, and metrics such as mean time to recovery and mean time between failures to guide operational improvements. Include testing for resilience through chaos engineering and fault injection, handling flaky components in test environments, analysis of past failures and refactoring for resiliency, and operational practices that reduce blast radius and speed recovery.

MediumSystem Design

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Design a replication and distribution strategy for large model artifacts (multiple GBs) so inference endpoints across regions can fetch models quickly while controlling storage costs and freshness. Discuss eager replication, on-demand warming, CDN usage, cache invalidation, and rollback mechanisms.

MediumTechnical

0 practiced

Design observability for a model-serving platform: list concrete SLIs and SLOs you would track (latency percentiles, error rates, model quality metrics, input distribution drift, and feature coverage). Explain alert thresholds, dashboards, and automated mitigations to reduce toil and MTTR.

MediumSystem Design

0 practiced

Design a checkpointing strategy for long-running distributed model training (days/weeks). Include checkpoint frequency policy, incremental versus full checkpoints, storage location (object store vs distributed filesystem), replication, encryption, and resume semantics to minimize wasted work after node failures.

HardTechnical

0 practiced

Describe techniques to detect silent failures where a model server returns plausible but incorrect predictions due to corrupted weights, bitrot, or subtle hardware faults. Propose automated safety checks, canary/verifier pipelines, shadow traffic strategies, and methods to quarantine and roll back affected nodes.

MediumSystem Design

0 practiced

In an active-active multi-region model-serving deployment, how do you ensure model version consistency and configuration synchronization across regions to avoid serving incompatible models or stale configs? Discuss metadata replication, deployment orchestration, and rollback strategies during partial failures.

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