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

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Jun 2026

Summary

Apple system design round for a software engineer role. The whole session was basically one deep problem about constrained hardware, and they really wanted you to think through every layer of it rather than just sketch a high-level architecture.

Questions Asked (1)

Design an inventory management system that runs on a machine with no SSD and very limited RAM, relying entirely on spinning disk storage. The system needs to support reads, updates, and conditional reservations (e.g. reserve a unit only if available quantity is greater than zero). Walk through data layout, indexing, caching, read path, write path, and latency considerations.

System DesignTechnical Trade-offsData Modeling

Author's notes

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints (e.g., data size, read/write ratio, consistency needs), then design a disk-optimized data layout with append-only logs and LSM-tree indexing to minimize random I/O. Walk through the read and write paths, emphasizing caching strategies and latency trade-offs, and explain how conditional reservations are handled atomically using write-ahead logging and in-memory indexes.

Pro tip: Explicitly discuss how you would handle the 'reserve if available' condition atomically without relying on fast storage—e.g., using a write-ahead log and a single-writer model to serialize updates, and leveraging Bloom filters to avoid unnecessary disk reads.

1. Clarify Requirements and Constraints

Ask about data volume, read/write ratio, latency targets, and consistency requirements to tailor the design. Confirm that spinning disk means high random I/O cost and limited RAM means small cache.

2. Design Data Layout and Indexing

Propose an append-only log for durability and an LSM-tree or B-tree variant optimized for disk. Use sparse indexes and Bloom filters to reduce disk seeks.

3. Define Read and Write Paths

Describe how reads traverse cache, index, and disk, and how writes are batched and appended. Explain how conditional reservations are implemented with atomic operations and logging.

4. Plan Caching and Memory Management

Outline a caching strategy (e.g., LRU for hot items) and how to manage limited RAM, possibly using memory-mapped files or direct I/O with careful buffer management.

5. Analyze Latency and Trade-offs

Discuss expected latencies for reads and writes, and trade-offs between consistency, durability, and performance. Mention techniques like group commit and read-ahead to mitigate disk latency.

Key Points to Mention

Append-only log-structured storage to convert random writes into sequential writes
LSM-tree with compaction and Bloom filters to reduce read amplification
Write-ahead logging (WAL) for atomicity and durability of conditional reservations
Caching strategy: LRU or LFU for hot data, with careful eviction policies due to limited RAM
Batching and group commit to amortize disk seek costs
Trade-offs between consistency (e.g., strong vs. eventual) and latency in reservation operations

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