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Design a Netflix-like streaming platform

Last updated: Apr 18, 2026

Quick Overview

Design a Netflix-like streaming platform evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • hard
  • HubSpot
  • System Design
  • Software Engineer

Design a Netflix-like streaming platform

Company: HubSpot

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Onsite

Design a Netflix-like video streaming platform. Cover user authentication and profiles, content catalog and metadata, search and personalized recommendations, video ingestion and transcoding pipeline, DRM and adaptive bitrate streaming (HLS/DASH), CDN and edge caching strategy, storage and geo-replication, playback session management, APIs and service discovery, multi-region failover and data consistency, observability and A/B testing, and cost optimization for millions of concurrent viewers.

Quick Answer: Design a Netflix-like streaming platform evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/System Design/HubSpot

Design a Netflix-like streaming platform

HubSpot logo
HubSpot
Jul 31, 2025, 12:00 AM
hardSoftware EngineerOnsiteSystem Design
18
0

Design a Netflix-like streaming platform

System Design: Netflix‑Like Video Streaming Platform

Context

Design a large-scale video streaming platform that supports web, mobile, and TV clients for millions of concurrent viewers worldwide. The system should prioritize availability, low-latency playback, security, and cost efficiency.

Assume:

  • Peak: 5–10 million concurrent streams globally.
  • Target startup latency < 2 seconds; low rebuffering; 99.9%+ availability for playback.
  • Mix of on-demand VOD content; live not required (optional considerations welcome).

Requirements

Design the system and cover the following components:

  1. User Authentication and Profiles
  • Sign-in, sessions, MFA, device limits, parental controls, multiple profiles per account.
  1. Content Catalog and Metadata
  • Titles, seasons/episodes, genres/tags, availability windows, rights/regions, subtitles/audio tracks.
  1. Search and Personalized Recommendations
  • Full-text search, browse pages, personalized rows, cold-start handling.
  1. Video Ingestion and Transcoding Pipeline
  • Secure uploader, QC, per-title encoding, thumbnails, captions, packaging to HLS/DASH.
  1. DRM and Adaptive Bitrate Streaming
  • Widevine/FairPlay/PlayReady, license services, CMAF, HLS/DASH manifests, LL-HLS optional.
  1. CDN and Edge Caching Strategy
  • Multi-CDN, edge authorization, origin shielding, cache warming/purges.
  1. Storage and Geo-Replication
  • Masters vs renditions, object storage layout, lifecycle tiers, cross-region replication.
  1. Playback Session Management
  • Session creation, concurrency enforcement, heartbeats, QoE metrics, resume playback.
  1. APIs and Service Discovery
  • External API gateway, internal gRPC, schema, rate limits, idempotency, service mesh.
  1. Multi-Region Failover and Data Consistency
  • Active-active vs active-passive, routing, data models with consistency choices.
  1. Observability and A/B Testing
  • Metrics/traces/logs, QoE SLOs, experimentation platform, guardrails.
  1. Cost Optimization
  • Encoding ladder strategy, codec choices, storage lifecycle, CDN offload, compute efficiency.

Deliver a high-level architecture and justify key trade-offs. Include back-of-the-envelope capacity estimates and call out pitfalls and edge cases.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask Guidance

  • Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
  • State explicit assumptions before making sizing or architecture decisions.
  • Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers Guidance

  • A scoped requirements summary with concrete non-goals and success metrics.
  • API, data model, architecture, consistency, capacity, and operations.
  • Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
  • A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions Guidance

  • What breaks first at 10x traffic or data volume?
  • How would you degrade gracefully during dependency failures?
  • What metrics and alerts would prove the design is healthy after launch?

Submit Your Answer to Earn 20XP

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