Starting with your own project sounds easy but it's actually a trap for overthinking.
Choose a project you know deeply and structure your answer around requirements, high-level design, deep dives, and trade-offs. Tailor the explanation to DoorDash's domain by emphasizing scalability, reliability, and real-time data handling, and quantify impact where possible.
Pro tip: Show maturity by proactively discussing what you would change or improve in hindsight, and tie your technical decisions to business outcomes like delivery time or cost savings.
Start by stating the project's goal, key functional and non-functional requirements (e.g., scale, latency, consistency), and any constraints. This sets context and shows you think before designing.
Sketch the main components (e.g., clients, services, databases, queues) and how they interact. Keep it simple and focus on the core flow.
Pick 1-2 areas where you made significant technical decisions (e.g., data model, sharding, caching, real-time updates) and explain your reasoning and alternatives considered.
Highlight key trade-offs (e.g., consistency vs. availability, latency vs. cost) and how you resolved them. Mention any bottlenecks or failures and how you addressed them.
Summarize the impact (e.g., performance improvements, user growth) and what you learned or would do differently. This shows reflection and growth.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Classic question but there's a lot of surface area.
Start by clarifying functional and non-functional requirements, then estimate scale (users, photos, QPS) to drive design decisions. Focus on the core feed generation and media storage pipeline, and discuss trade-offs between different architectural choices.
Pro tip: At DoorDash, scale and reliability are critical. Emphasize how your design handles high write throughput (photo uploads) and low-latency reads (feed), and discuss how you would monitor and mitigate hotspots.
Ask clarifying questions to define core features (posting, feed, following, likes/comments) and non-functional needs (latency, availability, consistency). Estimate scale: daily active users, photos per user, read/write ratio, and storage needs.
Sketch the main components: mobile clients, API gateway, services for user, media, feed, and interactions. Choose a data store for metadata (e.g., PostgreSQL) and object storage for media (e.g., S3), and a CDN for delivery.
Design schemas for users, follows, posts, and media. Discuss sharding strategies (e.g., by user ID) and indexing for efficient feed queries. Explain how to store media with unique IDs and serve via CDN.
Compare fan-out on write vs. read, and propose a hybrid approach. Detail how to use a message queue (e.g., Kafka) for asynchronous feed updates, and caching (e.g., Redis) for fast feed retrieval.
Identify potential bottlenecks (e.g., celebrity problem, hot partitions) and propose solutions (e.g., sharding, caching, rate limiting). Discuss trade-offs between consistency, latency, and cost.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.