Design a large-scale Task Scheduling Platform
Last updated: December 12, 2025
Quick Overview
Design a event-driven task scheduling system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Plaid
December 12, 20258
13
4,733 solved
Design a event-driven task scheduling system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during System Design Round at Plaid. 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. Plaid 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
- How would you handle a region-wide outage?
- How would you implement rate limiting to protect the system?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
Functional Requirements
- Task Creation: Users can submit tasks with specific parameters (e.g., type, priority, execution time).
- Task Scheduling: The system must schedule tasks based o...
Capacity Estimation
For capacity estimation, let’s assume Plaid processes an average of 10 million tasks daily.
- Tasks per second: 10 million tasks / 86400 seconds = ~115.74 tasks/second.
- Concurrent Users: ...
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