Design a fault-tolerant Analytics System
Last updated: September 15, 2025
Quick Overview
Design a fault-tolerant analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Salesforce
System Design
Software Engineer
Salesforce
September 15, 2025Software Engineer
Technical Screen
System Design
Medium
159
7
189 solved
Design a fault-tolerant analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Salesforce asks this during the Technical Screen to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
What the Interviewer Expects
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
Key Topics to Cover
Partitioning and sharding strategies
Database selection and data modeling
Caching strategies (local, distributed, CDN)
Monitoring, logging, and alerting
Message queues and async processing
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 happens if one of your database nodes goes down?
- What monitoring and alerting would you set up on day one?
- How would you optimize costs as the system scales?
- How would you handle schema migrations with zero downtime?
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Requirements
- Functional Requirements:
- The system must handle millions of requests per day for real-time analytics processing.
- Users should be able to query analytics data with low latency (sub-...
Capacity Estimation
- User Load Estimation:
- Assume 1 million active users, with each user making an average of 10 requests per day.
- Total requests per day = 1,000,000 users * 10 requests/user = 10 milli...
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