Lyft ETA & Routing System Architecture Questions
Design and architecture of large-scale ride-hailing ETA and routing systems, covering distributed system design, real-time data processing, routing algorithms, fault tolerance, geo-distributed services, data consistency considerations, and integration with external mapping and traffic data sources.
EasyBehavioral
77 practiced
Behavioral: Tell me about a time you were on-call for a production incident where ETA or routing quality significantly regressed during peak hours. Use the STAR format: describe the Situation, Task, Actions you took, and Results including post-incident improvements. Focus on your SRE responsibilities.
MediumTechnical
113 practiced
Implement a rolling-window aggregator in Python that updates per-tile average speed over the last 5 minutes. API: update(tile_id, timestamp_seconds, speed_kph) and query(tile_id, current_time_seconds) -> avg_speed. Keep memory bounded per tile and ensure amortized O(1) update/query.
HardSystem Design
68 practiced
Design an architecture for near-real-time simulation of city-wide routing under hypothetical incidents (e.g., road closures) to estimate ETA impacts and recommend mitigations. Discuss data inputs, compute model fidelity vs speed trade-offs, how to parallelize simulations, and how to integrate results into operations dashboards.
HardSystem Design
80 practiced
Design an observability pipeline for ETA & routing: what telemetry to collect (GPS traces, trip events, API traces), how to index and store for fast per-trip debugging, retention policies for high-cardinality data, sampling strategies, and cost-control measures while keeping required SRE capabilities.
MediumTechnical
80 practiced
Describe a capacity planning exercise for an ETA service before a large city event (e.g., concert). What metrics and historical signals do you analyze, how do you simulate expected load, and what preemptive operational actions would you take?
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