Start by clarifying requirements and constraints (connectivity types, data volumes, hardware variability), then propose a modular pipeline architecture with separate stages for ingestion, processing, and upload. Emphasize trade-offs and justify design choices based on scalability, reliability, and resource efficiency.
Pro tip: Anchor your design around a central orchestrator that abstracts connectivity and hardware differences, and explicitly discuss failure modes and recovery strategies—this shows production maturity.
Ask about data types, volumes, update frequency, connectivity profiles, hardware specs, and SLAs to scope the problem and tailor the design.
Propose a scheduler that adapts to connectivity (e.g., Wi-Fi, cellular, offline) using priority queues, backoff, and incremental sync (e.g., delta updates, chunking).
Outline a tiered storage strategy (hot/cold) with eviction policies, and a modular processing pipeline (e.g., stream/batch) that handles sensor fusion, telemetry aggregation, and map updates.
Incorporate checksums, versioning, and transactional writes; design upload as a separate, resilient service with compression, retries, and prioritization.
Discuss fleet-wide orchestration (e.g., OTA updates, centralized config), hardware abstraction layers, and adaptive resource management to handle diverse vehicle capabilities.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.