I blanked for a second on where to even start.
Break the problem into a top-down estimation: first estimate the total road coverage and number of 360-degree images, then calculate the storage per image based on resolution and compression, and finally multiply to get total storage. Acknowledge that the actual number depends on factors like image resolution, compression, and update frequency, and state your assumptions clearly.
Pro tip: Show product thinking by not just calculating storage but also discussing trade-offs: e.g., how storage costs impact decisions on image resolution, refresh rates, and coverage expansion. Mention that Google likely uses tiered storage (hot vs. cold) and aggressive compression to manage costs.
Estimate the total length of roads covered by Street View globally. Use known figures like total road length worldwide (~64 million km) and assume a coverage percentage (e.g., 30-50% for developed regions).
Determine how many 360-degree images are needed. Assume a capture interval (e.g., every 10 meters) and account for multiple cameras or passes. Multiply total road length by images per km.
Estimate the size of a single 360-degree image. Consider resolution (e.g., 8K), compression (JPEG), and number of faces. Calculate raw size and apply compression ratio.
Multiply number of images by storage per image to get raw storage. Add overhead for metadata, multiple zoom levels, and redundancy (e.g., 2-3x).
Compare your estimate to known data (e.g., Google Maps uses petabytes). Discuss how storage decisions affect product features like refresh rate and coverage.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.