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Applovin·Software Engineer·Onsite - System Design / Architecture·Senior

Senior
May 2026

Summary

System design round at Applovin for a software engineer role. Just one question but it had enough surface area to go pretty deep if you let it.

Questions Asked (1)

Q1

How would you design a system for storing and serving videos at scale, similar to YouTube?

System DesignTechnical Trade-offsData Modeling
Author's notes

Classic video storage question but I still fumbled the sequencing a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (scale, features, constraints) and then walk through a high-level design covering upload, storage, processing, and delivery. Dive into key components like CDN, transcoding, and metadata storage, discussing trade-offs and scalability.

Pro tip: Emphasize cost-efficiency and trade-offs, especially since AppLovin deals with massive scale and performance. Mention how you'd handle hot vs. cold storage and optimize for mobile networks.

1. Clarify Requirements

Ask about scale (daily uploads, views), features (resolution, transcoding, recommendations), and constraints (latency, cost).

2. High-Level Design

Outline main components: upload service, storage (blob + metadata), transcoding pipeline, CDN, and playback service.

3. Deep Dive into Key Components

Discuss storage choices (object storage like S3, CDN for delivery), transcoding (parallel, adaptive bitrate), and metadata (sharding, replication).

4. Address Scalability and Reliability

Explain how to scale each component (e.g., CDN edge caching, database sharding) and ensure fault tolerance (replication, retries).

5. Discuss Trade-offs and Optimizations

Compare options (e.g., pre-transcode vs. on-the-fly, storage tiers) and suggest optimizations for cost and performance.

Key Points to Mention

  • Use of CDN for global video delivery and caching
  • Transcoding pipeline for multiple resolutions and formats (e.g., HLS, DASH)
  • Metadata storage with a scalable database (e.g., Cassandra, DynamoDB) and indexing for search
  • Object storage (e.g., S3) for video blobs with lifecycle policies
  • Adaptive bitrate streaming and chunked uploads for reliability
  • Trade-offs between consistency, availability, and cost (e.g., eventual consistency for metadata)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.