JP Morgan·Software Engineer·Onsite - System Design / Architecture·Intermediate

Intermediate

Jul 2026

Summary

System design round at JP Morgan for a software engineering role. Just one question the whole time, which was the URL shortener classic. Felt like a reasonable session but there's not much to say beyond that.

Questions Asked (1)

Design a URL shortening service from scratch.

System DesignTechnical Trade-offsData Modeling

Author's notes

I've seen this one enough times that I wasn't panicking, but I still fumbled the capacity estimation part a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying functional and non-functional requirements (e.g., scale, read/write ratio, latency, availability) and then walk through the high-level design: API, data model, key generation, and storage. Dive into trade-offs for key generation (hash vs. counter), database choice (SQL vs. NoSQL), and caching, while addressing scalability and reliability.

Pro tip: Emphasize the read-heavy nature of URL shorteners and how caching and read replicas can drastically improve performance; also mention that at JP Morgan, security and compliance (e.g., preventing malicious URLs, audit logs) are critical, so include those considerations.

1. Clarify Requirements

Ask about expected traffic (e.g., 100M URLs, 10B redirects/month), read/write ratio, latency, availability, and any security/compliance needs. Define functional requirements: shorten URL, redirect, custom alias, expiration.

2. High-Level Design

Sketch the core components: API gateway, application servers, key generation service, database, cache, and analytics. Explain the flow: client sends long URL, service generates short key, stores mapping, returns short URL; redirect flow: client hits short URL, service looks up long URL and redirects.

3. Data Model & Key Generation

Choose a data model: key (short URL) -> value (long URL, metadata). Discuss key generation strategies: base62 encoding of auto-increment ID, hash (MD5/SHA) with collision handling, or pre-generated keys. Compare trade-offs (e.g., predictability, scalability, complexity).

4. Scalability & Performance

Address scaling: use a distributed counter (e.g., ZooKeeper, Snowflake) or key generation service, shard the database (e.g., by key range or hash), add read replicas, and implement caching (e.g., Redis) for hot URLs. Discuss CDN for redirects if needed.

5. Reliability & Security

Cover fault tolerance: replication, failover, and monitoring. For security: rate limiting, input validation, malware scanning, and audit logs. Mention analytics (click tracking) and expiration policies.

Key Points to Mention

Read-heavy workload: optimize for low-latency redirects with caching and read replicas.
Key generation trade-offs: base62 encoding of sequential IDs (predictable but simple) vs. hash-based (collision handling) vs. pre-generated keys (scalable but complex).
Database choice: NoSQL (e.g., Cassandra, DynamoDB) for scalability and high write throughput, or SQL with sharding for strong consistency.
Caching strategy: use Redis or Memcached to cache hot URLs, with appropriate eviction policies (LRU).
Scalability: sharding, distributed counters, and load balancing to handle growth.
Security and compliance: rate limiting, input sanitization, malware detection, and audit logging (especially important for financial institutions).

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