This one has a lot of surface area and I'm not sure I scoped it well.
Start by clarifying requirements and constraints, then outline a high-level design covering core components like namespace, metadata, and data storage. Dive into key operations (create, read, write, delete) and discuss trade-offs around consistency, scalability, and durability, aligning with Amazon's leadership principles.
Pro tip: Proactively discuss how your design handles failure scenarios and scales to millions of users, as Amazon values operational excellence and customer obsession. Also, relate decisions to real-world systems like S3 or DynamoDB to show practical insight.
Ask questions to understand scope: single-node vs distributed, expected scale, consistency needs, and features like permissions or versioning. This ensures you design the right system.
Sketch the architecture: separate metadata (namespace, permissions) from data storage, and define APIs for file operations. Consider using a tree structure for directories and unique IDs for files.
Detail metadata storage (e.g., database choice), data storage (e.g., block storage, object storage), and how operations like read/write work. Discuss caching, indexing, and partitioning for scalability.
Discuss consistency models (strong vs eventual), replication for durability, and sharding for scale. Explain how to handle concurrent access and failures.
Recap key decisions, mention potential bottlenecks, and suggest improvements. Tie back to Amazon's principles like customer obsession and ownership.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.