Estimate infrastructure or operational capacity needed for Frame.io

Problem Statement Description

Product context: Adobe is a creative, document, and marketing software company; its products include Creative Cloud, Photoshop, Illustrator, Acrobat, Adobe Express, Firefly, and Experience Cloud.

Adobe wants to understand the infrastructure or operational capacity required to support Frame.io for marketing teams that collaborate on video and creative assets. In this guesstimate interview, you are being asked to size the capacity needed for a realistic Frame.io workflow, such as uploading campaign videos, sharing review links, collecting feedback, versioning edits, and approving final assets across distributed teams.

Assume the core users are marketers, creative producers, brand managers, agencies, and reviewers working on high-volume campaign content. The estimate may cover technical infrastructure such as storage, upload/download bandwidth, transcoding, preview generation, notifications, and concurrent review sessions, or operational capacity such as support load, onboarding, moderation, or customer success needs. You should clarify which capacity dimension you are estimating before building your model.

This is not a request for an exact internal Adobe number. The focus is on defining a reasonable scope, choosing measurable units, making explicit assumptions, and showing how changes in adoption, asset size, collaboration frequency, and enterprise usage would affect the estimate.

The experience should consider:

- The specific capacity unit being estimated, such as storage per month, peak bandwidth, transcoding jobs, support tickets, or customer success coverage

- The target population, including marketing teams, agencies, enterprise customers, and external reviewers

- Typical Frame.io workflows, including uploads, comments, approvals, versioning, sharing, and archival

- Adoption assumptions, such as number of active teams, projects per team, users per project, and review participants

- Usage frequency, including files uploaded per project, average asset size, number of versions, and review cycles

- Peak versus average demand, especially around campaign launches, agency deadlines, and global collaboration windows

- Sensitivity drivers, such as video resolution, retention policies, AI-assisted workflows, and enterprise governance requirements

- Sanity checks against comparable creative collaboration, video storage, or enterprise marketing workflow products

Your goal is to produce a structured, defensible estimate that an Adobe product or infrastructure team could use for early capacity planning. Clearly state your assumptions, calculate step by step, identify the biggest drivers of uncertainty, and explain how you would validate or refine the estimate with real product data.