Design Image Processing Infrastructure for mobile apps
Last updated: February 13, 2026
Quick Overview
Design a event-driven image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Zscaler
February 13, 202644
5
813 solved
Design a event-driven image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
ML system design at Zscaler goes beyond model selection. This System Design Round question evaluates your ability to design end-to-end ML pipelines, from data collection to model serving, while considering production constraints like latency and reliability.
What the Interviewer Expects
- Design the full ML lifecycle from data collection to model monitoring
- Address cold start, exploration/exploitation, and model freshness
- Discuss multi-objective optimization and ranking systems
- Plan for model debugging, fairness, and bias mitigation
- Design the feature store and training pipeline for scale
- Address model versioning, canary deployments, and rollback strategies
- Discuss the data flywheel and long-term system evolution
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you debug a model that works well offline but poorly online?
- How would you handle a 10x increase in prediction requests?
- How would you handle the cold start problem?
- What is your model retraining strategy?
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Requirements Clarification
Before diving into the architecture, clarify the scope with the interviewer. For Image Processing Infrastructure for mobile apps, key functional requi...
Capacity Estimation
Estimate the scale to drive design decisions. Assume 100M DAU with an average of 10 actions per user per day = 1B requests/day ~ 12K QPS average, ~36K...
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