Design the event instrumentation for Acrobat at scale

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 Acrobat is used across individual, team, and enterprise document workflows, including agencies that create, review, secure, share, sign, and deliver high-volume client-facing PDFs. In this interview, you are asked to design the event instrumentation approach for Acrobat at scale so product, engineering, data science, and business teams can understand how users move through critical document workflows without compromising trust, privacy, performance, or enterprise requirements.

Focus on the technical product-management aspects of defining what should be measured, how events should be structured, how data should flow from client and server surfaces, and how the system should support reliable analysis across Acrobat desktop, web, mobile, browser integrations, collaboration features, AI-assisted document experiences, and enterprise-admin contexts. Assume Acrobat operates at very large scale with global users, varied connectivity, multiple subscription tiers, and strict expectations around document confidentiality.

You do not need to design a full analytics platform implementation, but you should scope the requirements, trade-offs, data contracts, rollout approach, governance, and observability needed for a durable instrumentation system. The discussion should make clear how instrumentation enables better product decisions while respecting Adobe’s professional-trust bar and the needs of agency and enterprise customers.

The experience should consider:

- Core Acrobat workflows to instrument, such as open/view, edit, comment, share, export, combine, protect, e-signature handoffs, collaboration, and AI-assisted actions.

- Event taxonomy, naming conventions, required properties, user/session/document context, and how to avoid collecting sensitive document content.

- Client-side versus server-side instrumentation across desktop, web, mobile, offline usage, and cross-device journeys.

- Data quality requirements, including deduplication, schema validation, versioning, backward compatibility, latency, sampling, and missing-event detection.

- Privacy, consent, enterprise controls, data residency, retention, security, and compliance constraints.

- APIs, event pipelines, identity resolution, feature flag integration, experimentation support, and downstream analytics consumers.

- Rollout plan, monitoring, alerting, ownership model, documentation, and processes for adding or changing events safely.

- Product trade-offs around instrumentation depth, app performance, engineering effort, analytical usefulness, and customer trust.

The goal is to evaluate how you would define a scalable, trustworthy instrumentation system for a mature Adobe product, balancing technical architecture, product insight, enterprise constraints, and operational rigor without jumping directly to dashboards or business conclusions.