Estimate infrastructure or support load created by video meeting experience

Problem Statement Description

You are evaluating the operational footprint of a video meeting experience used by operations managers to coordinate recurring business reviews, incident standups, vendor check-ins, and cross-functional planning meetings. The interviewer wants you to estimate the infrastructure or customer support load generated by this experience at scale.

Frame the estimate around a concrete scope: what “load” means, which users and meeting types are included, what time period you are estimating for, and whether you are focused on compute/network infrastructure, storage, reliability operations, support tickets, or a combination of these. The problem is not to design the video product, but to reason quantitatively about how usage behavior translates into operational demand.

Your estimate should make clear assumptions about user population, meeting frequency, meeting duration, participant count, video quality, recording usage, failure rates, and support contact behavior. You should also show how the estimate could change under different adoption levels or usage patterns.

The experience should consider:

- The target user segment: operations managers and the teams they coordinate with

- The unit of estimation, such as monthly meeting hours, concurrent sessions, bandwidth consumed, recordings stored, or support tickets created

- Population assumptions, including number of organizations, active managers, and meeting participants

- Usage assumptions, including meetings per user, duration, participant count, and peak-time concentration

- Infrastructure drivers such as audio/video streams, screen sharing, recordings, transcription, and regional routing

- Support-load drivers such as failed joins, audio/video quality issues, permissions, calendar integration, and recording access

- Sensitivity checks for high-usage teams, global time zones, enterprise customers, and incident-heavy periods

- Sanity checks against practical constraints such as network capacity, support staffing, and expected enterprise usage patterns

The goal is to produce a structured, defensible estimate that connects product usage to infrastructure or support burden, highlights the most important assumptions, and identifies which variables would matter most for planning capacity and maintaining meeting effectiveness.