Build a event-driven Payment Pipeline

Last updated: February 12, 2026

Quick Overview

Design a event-driven payment system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Atlassian
System Design
Software Engineer
Atlassian
February 12, 2026
Software Engineer
Onsite
System Design
Easy

216

15

2,965 solved


Design a event-driven payment system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

This ML system design question from Atlassian's Onsite tests your ability to think about ML systems at scale. The interviewer expects discussion of data quality, feature stores, model serving infrastructure, and A/B testing strategy.

What the Interviewer Expects
  • Map the business problem to a concrete ML objective
  • Propose reasonable features and a baseline model
  • Discuss basic model evaluation metrics
  • Outline a simple serving architecture
Key Topics to Cover
A/B testing and experimentation
Feature engineering and feature stores
ML objective formulation and metric selection
Data collection and labeling strategy
Online vs offline evaluation
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 debug a model that works well offline but poorly online?
  • How would you handle the cold start problem?
  • What would you do if model performance degrades over time?
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Sample Answer
Requirements Clarification

Before diving into the architecture, clarify the scope with the interviewer. For event-driven Payment Pipeline, key functional requirements include: w...

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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