Each test is 5 questions with varying difficulty.
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Designing a URL shortener is a classic system design interview question that tests your ability to handle high-read-throughput distributed systems. In 2026, this problem remains a staple for assessing how candidates approach unique identifier generation, database schema design, and caching strategies. The core requirement is to map a long URL to a short, unique alias and redirect users efficiently. Junior candidates are expected to propose a basic relational database schema and a simple hashing mechanism. Senior candidates must demonstrate mastery over distributed ID generation, handling massive read-to-write ratios, managing cache stampedes, and ensuring high availability across multiple regions. Interviewers use this topic to evaluate your understanding of trade-offs between storage efficiency, latency, and system reliability under heavy load.
The URL shortener problem is a high-signal interview topic because it forces candidates to confront the realities of scale. A production-grade URL shortener must handle millions of requests per day, where the read-to-write ratio is typically 100:1. This necessitates a robust caching strategy, as hitting the database for every redirect would result in unacceptable latency. Furthermore, the problem exposes a candidate's ability to design for collision-free ID generation—a fundamental challenge in distributed systems. In 2026, with the rise of edge computing, the conversation has shifted toward global distribution and edge-based redirects. A strong answer demonstrates not just knowledge of components, but the ability to reason about the system's performance bottlenecks, such as database write contention or cache eviction policies. Weak answers often fail to address how the system behaves when the cache is empty, how to handle the deletion of expired URLs, or how to scale the ID generation service without creating a single point of failure.
The architecture follows a request-response flow where a client submits a long URL to a load-balanced API gateway. The API service generates a unique ID, converts it to a base62 string, and stores the mapping in a distributed database. For redirects, the service checks a distributed cache (Redis) first; if a miss occurs, it queries the database and populates the cache.
[Client Request]
↓
[Load Balancer]
↓
[API Service Cluster]
↓ ↓
[Distributed Cache] [Database Cluster]
↓ ↓
[ID Generator Service]
↓
[Response to Client]Write data directly to the database and update the cache only on subsequent reads.
Trade-offs: Reduces cache pollution from one-time URLs but increases latency for the first read.
Partition the database by hash range and use local sequences to generate unique IDs.
Trade-offs: Eliminates central bottlenecks but complicates range queries and re-balancing.
Use a Bloom filter to quickly check if a short URL exists before querying the database.
Trade-offs: Reduces unnecessary database hits but introduces a small probability of false positives.
| Reliability | Use database replication and multi-zone deployment to ensure the mapping store remains available during node failures. |
| Scalability | Horizontal scaling of the API service tier and database sharding based on the short URL hash prefix. |
| Performance | Target sub-50ms latency for redirects by keeping the working set in Redis. |
| Cost | Optimize storage by using short-lived TTLs for rarely accessed URLs to reduce database and cache footprint. |
| Security | Implement rate limiting per IP to prevent abuse and URL scanning attacks. |
| Monitoring | Track cache hit ratios, database latency, and ID generation throughput. |
While random strings are easy to generate, they carry a high risk of collisions as the number of URLs grows. A distributed counter combined with base62 encoding ensures uniqueness and a predictable, compact length, which is more scalable for large systems.
A URL shortener is a specific type of application that maps a short alias to a long URL and performs a redirect. A proxy is a general-purpose intermediary that forwards requests between clients and servers, often for security, load balancing, or caching purposes.
The hot key problem occurs when a single URL receives a massive volume of traffic. You can mitigate this by using a multi-level cache, replicating the hot key across multiple cache nodes, or using a local cache on the API servers to reduce the load on the distributed cache.
SQL is often sufficient for moderate scale and provides strong consistency. NoSQL, like Cassandra, is preferred for massive write-heavy workloads where horizontal scalability and high availability are more critical than complex relational queries.
Redirect latency is the primary user-facing metric. If the redirect takes too long, users may abandon the link. Since the redirect is the most frequent operation, even a few milliseconds of delay can significantly impact the user experience.
Base62 encoding maps a large integer to a string using 62 characters (0-9, a-z, A-Z). It is essentially a base conversion algorithm that allows you to represent large numbers in a very compact, URL-safe format.
A Bloom filter is a space-efficient probabilistic data structure used to test whether an element is a member of a set. In a URL shortener, it can quickly tell you if a short URL alias does not exist, preventing unnecessary database lookups.
You can mark URLs as inactive in the database or use a TTL (Time-To-Live) mechanism. For high-performance systems, you might use a background process to clean up expired entries from the database and cache.
HTTP 301 is a permanent redirect, meaning browsers and search engines will cache the redirect target. HTTP 302 is a temporary redirect, which is useful if you want to track every click or change the destination URL in the future.
You can use a distributed ID generation service like Snowflake, which generates unique IDs based on a combination of timestamp, worker ID, and sequence number, ensuring uniqueness across multiple nodes without needing a central coordinator.
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