Design a large-scale Monitoring Platform

Last updated: December 24, 2025

Quick Overview

Design a multi-tenant monitoring system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Databricks
System Design
Software Engineer
Databricks
December 24, 2025
Software Engineer
Onsite
System Design
Hard

44

3

666 solved


Design a multi-tenant monitoring 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 Databricks. 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. Databricks 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
Load balancing and horizontal scaling
Monitoring, logging, and alerting
High-level architecture and component design
Consistency models and replication
Failure handling and fault tolerance
Requirements gathering and capacity estimation
How to Approach This
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
  • How would you handle a 10x increase in traffic overnight?
  • What monitoring and alerting would you set up on day one?
  • How do you ensure data consistency across multiple services?
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Sample Answer
Requirements

Functional Requirements

  1. Multi-Tenancy: Support multiple clients with data isolation.
  2. Real-Time Monitoring: Provide real-time metrics collection and alerting.
  3. **Custom Dashbo...
Capacity Estimation

Assuming we have 1 million tenants, each generating about 100 metrics per second, we can estimate the following capacity needs:

  • Requests per second: 1,000,000 tenants * 100 metrics = 100,000,0...

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