Design the event instrumentation for Insurance at scale

Problem Statement Description

Product context: Tesla is an electric vehicle, energy, and software company; its products include EVs, charging, vehicle software, Autopilot/FSD features, energy storage, and solar products.

Tesla Insurance relies on connected vehicle data, mobile app interactions, policy lifecycle events, billing, claims, and safety-related signals to create a reliable insurance experience for customers. In this technical PM question, you are asked to design event instrumentation that can work at scale across Tesla’s hardware-software ecosystem while supporting safety-conscious families who expect transparent, fair, and dependable coverage.

The focus is not to design the insurance product itself, but to define how the product and engineering teams should capture, validate, govern, and use events across the insurance journey. Consider moments such as quote exploration, enrollment, policy changes, driving behavior signals, premium updates, claims initiation, customer support, and renewal. The instrumentation should support product analytics, pricing operations, compliance needs, debugging, experimentation, and customer trust.

Because this is a Tesla context, your design should account for connected vehicles, mobile apps, backend services, real-time or near-real-time data flows, and strict expectations around reliability, privacy, and security. You should also think about the trade-offs between granular telemetry and customer sensitivity, especially when driving behavior and family safety are involved.

The experience should consider:

- The key users and stakeholders for instrumentation, including customers, product teams, data science, actuarial/pricing teams, claims operations, engineering, compliance, and customer support.

- The core insurance workflows and lifecycle stages that need reliable event coverage.

- Event taxonomy, naming conventions, required properties, identity resolution, timestamps, and source-of-truth ownership.

- APIs, data pipelines, storage, validation, deduplication, latency, and failure-handling requirements.

- Privacy, consent, data minimization, access controls, retention, auditability, and regulatory considerations.

- Observability needs such as data quality monitoring, missing-event detection, schema changes, and incident response.

- Rollout strategy across vehicle software, mobile app, and backend systems, including versioning and backward compatibility.

- Product trade-offs between instrumentation completeness, system cost, customer trust, and operational complexity.

The goal is to evaluate how you would structure a scalable, trustworthy instrumentation system for Tesla Insurance, ensuring teams can make accurate decisions and operate the product safely without over-collecting data or creating fragile dependencies.