Design a large-scale Analytics Platform
Last updated: March 17, 2026
Quick Overview
Design a event-driven analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
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Design a event-driven analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at Google. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Google values engineers who can think about scalability from day one.
What the Interviewer Expects
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
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
- What would the deployment pipeline look like for this system?
- What monitoring and alerting would you set up on day one?
- How do you ensure data consistency across multiple services?
- What happens if one of your database nodes goes down?
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Requirements
Functional Requirements
- Event Ingestion: The system must be able to ingest event data from various sources (web, mobile, IoT) in real-time.
- Real-time Analytics: Users should be able ...
Capacity Estimation
Assuming the platform needs to handle 1 billion events per day:
- Per Second Calculation: [ 1 ext{ billion events/day} = \frac{1,000,000,000}{86400 \text{ seconds}} \approx 11,574 ext{ eve...
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