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Design a scalable network I/O service

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's ability to design a scalable, highly available network I/O backend, testing competencies in distributed systems, storage architecture, CDN and caching integration, API and data model design, capacity planning, failure handling, observability, and security.

  • hard
  • Anthropic
  • System Design
  • Software Engineer

Design a scalable network I/O service

Company: Anthropic

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Technical Screen

Design a scalable and reliable backend service that handles high-volume network I/O (e.g., ingesting and serving large files or streaming data) for millions of users. Define functional and non-functional requirements; propose APIs and data models; estimate capacity and perform back-of-the-envelope calculations; design the high-level architecture (load balancing, stateless services, storage, caching, queues, CDN). Explain strategies for horizontal scaling, performance optimization, and cost controls. Address security and privacy (authentication, authorization, encryption in transit/at rest, rate limiting, multi-tenant isolation). Detail failure handling, retries, idempotency, consistency choices, and disaster recovery. Describe deployment, observability (logging/metrics/tracing), incident response, and rollback. Identify corner cases (e.g., partial uploads, duplicate requests, slow clients, network partitions) and how you would test them.

Quick Answer: This question evaluates a candidate's ability to design a scalable, highly available network I/O backend, testing competencies in distributed systems, storage architecture, CDN and caching integration, API and data model design, capacity planning, failure handling, observability, and security.

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Anthropic logo
Anthropic
Sep 6, 2025, 12:00 AM
Software Engineer
Technical Screen
System Design
19
0

System Design: High-Volume Network I/O Backend (Files and Streaming)

Context

Design a backend service that supports millions of users uploading and downloading large files (hundreds of MB to multi-GB) and/or consuming streaming data. The service must be Internet-facing, production-grade, and cost-efficient.

Assume this is a 45–60 minute technical screen. You may make reasonable assumptions; state them explicitly.

Requirements

  1. Functional requirements
    • Upload large files with resumable/multipart support, pause/resume, checksums, and content-type validation.
    • Download files efficiently with range requests, partial reads, and CDN acceleration.
    • Optional: Support a streaming mode (e.g., live video/audio segments) using standard protocols.
    • Metadata management: create/list/get object metadata; versioning; soft delete; lifecycle policies.
    • Access control: per-tenant, per-user permissions; audit logging.
  2. Non-functional requirements
    • High availability across zones; durability appropriate for long-term storage.
    • Horizontal scalability to millions of users; low tail latency for control-plane APIs.
    • Cost-aware architecture (storage, egress, CDN, compute).
    • Security and privacy by default.
  3. Deliverables
    • Clearly state assumptions and SLOs.
    • Define functional and non-functional requirements.
    • Propose external APIs (endpoints, request/response) and core data models.
    • Capacity estimates and back-of-the-envelope calculations.
    • High-level architecture: load balancing, stateless services, storage, caching, queues, CDN.
    • Strategies for horizontal scaling, performance optimizations, and cost controls.
    • Security and privacy: authentication, authorization, encryption in transit/at rest, rate limiting, multi-tenant isolation.
    • Failure handling: retries, idempotency, consistency choices, disaster recovery.
    • Deployment, observability (logging/metrics/tracing), incident response, rollback.
    • Corner cases (e.g., partial uploads, duplicate requests, slow clients, network partitions) and how to test them.

Solution

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