Design Slack-like messaging platform

Quick Overview

This question evaluates a candidate's ability to design scalable, secure, real-time messaging systems, testing competencies in distributed systems, data modeling, API design, storage and sharding strategies, search indexing, and notification delivery.

Design Slack-like messaging platform

Company: OpenAI

Role: Software Engineer

Category: System Design

Difficulty: medium

Interview Round: Technical Screen

Design a Slack-like team collaboration product. Core features: - Workspaces (tenants), users, and channels (public/private) - Direct messages (1:1 and small groups) - Send/receive messages in real time (web + mobile) - Message history persistence and sync across devices - Search messages within a workspace - Notifications (mentions, DMs, channel activity) Non-functional requirements: - High availability and low latency for message delivery - Scales to many workspaces and very large channels - Reasonable consistency guarantees (ordering within a channel) - Security/isolation across workspaces Deliver: - High-level architecture - Key APIs and data model - Real-time delivery mechanism - Storage/sharding strategy - How search and notifications work - Major trade-offs and bottlenecks

Overview: This question evaluates a candidate's ability to design scalable, secure, real-time messaging systems, testing competencies in distributed systems, data modeling, API design, storage and sharding strategies, search indexing, and notification delivery.

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OpenAI
Oct 31, 2025
mediumSoftware EngineerTechnical ScreenSystem Design
17
0

Design a Slack-like team collaboration product.

Core features:

  • Workspaces (tenants), users, and channels (public/private)
  • Direct messages (1:1 and small groups)
  • Send/receive messages in real time (web + mobile)
  • Message history persistence and sync across devices
  • Search messages within a workspace
  • Notifications (mentions, DMs, channel activity)

Non-functional requirements:

  • High availability and low latency for message delivery
  • Scales to many workspaces and very large channels
  • Reasonable consistency guarantees (ordering within a channel)
  • Security/isolation across workspaces

Deliver:

  • High-level architecture
  • Key APIs and data model
  • Real-time delivery mechanism
  • Storage/sharding strategy
  • How search and notifications work
  • Major trade-offs and bottlenecks