Solution Approach & Modeling Strategy Questions
Techniques for approaching system design problems and architectural modeling in distributed systems, including problem framing, requirement elicitation, modeling abstractions (data flows, component boundaries, API interactions), trade-off analysis, and evaluation criteria for scalability, reliability, and maintainability.
HardSystem Design
0 practiced
Design an online learning architecture for personalization that updates models in near real-time (seconds to minutes). Address: safe update pipelines (validation, canarying), feature pipelines and atomicity, isolation to prevent feedback loops, rollback strategies, metrics to validate updates, and how to handle stateful per-user models at scale while ensuring reproducibility.
MediumTechnical
0 practiced
Design a real-time monitoring and alerting pipeline to detect model performance drift and data distribution shift for a fraud-detection model. Specify which metrics to compute (PSI, KS, model-score distribution, false-positive rate), aggregation windows, thresholds, training vs serving comparison baselines, and where this logic should reside (embedded in service vs separate monitoring system).
MediumSystem Design
0 practiced
Design an inference platform to support 50k QPS of small NLP models (~100MB) with a 99th-percentile latency SLO of 50ms. Describe resource allocation (CPU vs GPU), autoscaling strategy, request batching, request routing, warm pool management, cold start mitigation, and cost controls. Provide a component diagram showing request flow from ingress through model instances and cache.
EasyTechnical
0 practiced
Explain how resilience patterns such as circuit breakers, retries with exponential backoff, and bulkheads apply to a model-serving microservice. Provide an example sequence where a downstream vector DB times out and describe how each pattern prevents systemic failure, plus pitfalls specific to GPU-backed inference (e.g., queuing requests causing GPU starvation).
EasyTechnical
0 practiced
You're asked to design an AI-driven image moderation service for a large social platform. Describe the step-by-step approach you would take to frame the problem before designing the system: how you would identify stakeholders, elicit functional and non-functional requirements (throughput, latency, false-positive/negative tolerances, legal constraints), list success metrics, and state key assumptions. Also include example clarifying questions you would ask product, safety, and ops teams.
Unlock Full Question Bank
Get access to hundreds of Solution Approach & Modeling Strategy interview questions and detailed answers.
Sign in to ContinueJoin thousands of developers preparing for their dream job.