Design street-view image ingestion and storage system

## Prompt Design a system to ingest, store, and process street-level images for a "Street View"-like product. ### Scenario - A fleet of taxis is equipped with cameras. - Each taxi periodically captures photos (optionally with sensor metadata like GPS, timestamp, heading) and uploads them to your backend over unreliable mobile networks. - Stored images are consumed by downstream systems for: - Image understanding / feature extraction - Map generation (stitching/selection) - Display to end users (serving tiles/panoramas or individual frames) ### What to cover 1. **Requirements gathering** - Functional requirements (ingestion, storage, retrieval, processing hooks) - Non-functional requirements (durability, availability, latency, cost, privacy/security) - Scale assumptions (taxis, images per taxi, image size, retention) 2. **High-level architecture** - Main services and data stores - Data flow from taxi → ingestion → durable storage → processing pipeline → serving 3. **Upload API design** - How the taxi uploads images (single-shot vs chunked/resumable) - Response semantics (sync/async), idempotency, retries - Handling bad networks, offline buffering, and partial uploads 4. **Security / authentication** - How devices authenticate (tokens/certs) - How to prevent abuse and secure data in transit/at rest - What to do if a token/device credential is compromised (revocation, rotation, blast radius reduction) 5. **Trade-offs & extensions** - Storage choices and partitioning - Exactly-once vs at-least-once ingestion - If given more time, what additional features or safeguards you would add (and why)