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Design a Distributed File System

Last updated: May 23, 2026

Quick Overview

This question evaluates a candidate's competency in distributed systems and large-scale storage design, covering skills such as hierarchical namespace modeling, API and data model design, metadata management, replication and consistency strategies, fault tolerance, and scalable storage architecture.

  • medium
  • Databricks
  • System Design
  • Backend Engineer

Design a Distributed File System

Company: Databricks

Role: Backend Engineer

Category: System Design

Difficulty: medium

Interview Round: Technical Screen

Design a distributed file system for a cloud service. The system should support: - A hierarchical namespace with directories and files. - File operations: create, read, update, delete, rename, move, and list directory contents. - Large files that may exceed the capacity of a single machine. - Many concurrent clients reading and writing files. - Durability despite machine or disk failures. - Horizontal scalability to billions of files and petabytes of data. Discuss the API, data model, storage architecture, metadata management, replication strategy, consistency model, failure handling, and trade-offs.

Quick Answer: This question evaluates a candidate's competency in distributed systems and large-scale storage design, covering skills such as hierarchical namespace modeling, API and data model design, metadata management, replication and consistency strategies, fault tolerance, and scalable storage architecture.

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Databricks
May 4, 2026, 12:00 AM
Backend Engineer
Technical Screen
System Design
13
0

Design a distributed file system for a cloud service.

The system should support:

  • A hierarchical namespace with directories and files.
  • File operations: create, read, update, delete, rename, move, and list directory contents.
  • Large files that may exceed the capacity of a single machine.
  • Many concurrent clients reading and writing files.
  • Durability despite machine or disk failures.
  • Horizontal scalability to billions of files and petabytes of data.

Discuss the API, data model, storage architecture, metadata management, replication strategy, consistency model, failure handling, and trade-offs.

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