How to Design a URL Shortener Service (System Design Interview Guide)

9. Load Balancer (LB)

We can add a Load balancing layer at three places in our system:

1. Between Clients and Application servers
2. Between Application Servers and database servers
3. Between Application Servers and Cache servers

Initially, we could use a simple Round Robin approach that distributes incoming requests equally among backend servers. This LB is simple to implement and does not introduce any overhead. Another benefit of this approach is that if a server is dead, LB will take it out of the rotation and stop sending any traffic to it.

A problem with Round Robin LB is that we do not consider the server load. As a result, if a server is overloaded or slow, the LB will not stop sending new requests to that server. To handle this, a more intelligent LB solution can be placed that periodically queries the backend server about its load and adjusts traffic based on that.

10. Purging or DB cleanup

Should entries stick around forever, or should they be purged? If a user-specified expiration time is reached, what should happen to the link?

If we chose to continuously search for expired links to remove them, it would put a lot of pressure on our database. Instead, we can slowly remove expired links and do a lazy cleanup. Our service will ensure that only expired links will be deleted, although some expired links can live longer but will never be returned to users.

• Whenever a user tries to access an expired link, we can delete the link and return an error to the user.
• A separate Cleanup service can run periodically to remove expired links from our storage and cache. This service should be very lightweight and scheduled to run only when the user traffic is expected to be low.
• We can have a default expiration time for each link (e.g., two years).
• After removing an expired link, we can put the key back in the key-DB to be reused.
• Should we remove links that haven’t been visited in some length of time, say six months? This could be tricky. Since storage is getting cheap, we can decide to keep links forever.

11. Telemetry

How many times a short URL has been used, what were user locations, etc.? How would we store these statistics? If it is part of a DB row that gets updated on each view, what will happen when a popular URL is slammed with a large number of concurrent requests?

Some statistics worth tracking: country of the visitor, date and time of access, web page that referred the click, browser, or platform from where the page was accessed.

12. Security and Permissions

Can users create private URLs or allow a particular set of users to access a URL?

We can store the permission level (public/private) with each URL in the database. We can also create a separate table to store UserIDs that have permission to see a specific URL. If a user does not have permission and tries to access a URL, we can send an error (HTTP 401) back. Given that we are storing our data in a NoSQL wide-column database like Cassandra, the key for the table storing permissions would be the ‘Hash’ (or the KGS generated ‘key’). The columns will store the UserIDs of those users that have permission to see the URL.

12. Summary

In my experience, every successful software developer has followed a systematic approach to solve a system design question during an interview. The current interview process requires us to present a reasonable solution within 45 minutes and the key to success is being organized during the system design interview. Hopefully, this step-by-step approach will help you stay on track during the interview.

Please take a look at Grokking the System Design Interview for more system design interview questions like:

1. Designing a file sharing service like Google Drive or Dropbox.
2. Designing popular messaging service like Facebook Messenger.
3. Designing popular social network sites like Twitter or Facebook.
4. Designing global video streaming service like YouTube.
5. Designing a global ride hailing service like Uber.

To learn software architecture and practice advanced system design interview questions take a look at Grokking the Advanced System Design Interview.

Want to learn more about system design interviews, check followings posts from Design Gurus:
[1] System Design Interviews: A Step-By-Step Guide
[2] System Design Interview Basics: CAP vs. PACELC
[3] Mastering the System Design Interview: A Complete Guide

FAQs

1. What are the key components of a URL shortener service?

• API Gateway: Acts as the entry point for clients, routing API calls to backend services. It can handle cross-cutting concerns (like logging, rate limiting, or authentication) before requests reach the core application.
• Database: A storage system to persist the mapping from short codes to original URLs. This is often a fast key-value store or NoSQL database to allow quick lookups (Common System Design Interview Examples (With Solutions)). Every short URL code serves as the key to retrieve the full URL.
• Hashing/ID Generator: A mechanism to create unique short codes for URLs. This could be a hashing function or a sequential ID generator (which is then encoded) to ensure each long URL gets a unique short identifier.
• Caching: An in-memory cache (e.g., Redis) for frequently accessed URL mappings. Caching popular links reduces database load and speeds up redirects, since most traffic is read-heavy (many more redirects than new URL shortenings).
• Load Balancer: Distributes incoming requests across multiple servers so no single machine becomes a bottleneck. This improves availability and allows the service to handle more traffic by scaling horizontally.
• CDN: A Content Delivery Network can be used to serve static assets (like the website UI or images) and deliver content from edge locations closer to users, reducing latency and offloading work from origin servers (What is CDN?). (While the redirection itself is a quick lookup, a CDN helps with any static content and can improve global access speeds.)

2. What scalability strategies help a URL shortener handle high traffic?

• Sharding: Partition the URL data across multiple database servers (for example, by hashing the short code or using a range of IDs for each shard). This spreads out the load and storage, allowing the system to handle a massive number of entries without one DB becoming a hotspot.
• Caching: Use an in-memory cache layer to store popular URL mappings and serve frequent redirects quickly. This greatly reduces latency and database reads, as most redirect lookups can be served from cache. Cache invalidation or TTLs ensure the cache doesn’t serve stale data if URLs expire.
• CDN: Leverage a CDN for any static content and to improve response times for users globally. By caching content at the network edge, a CDN reduces the load on core servers and speeds up access for users far from your data center (What is CDN?). This is especially useful if your service provides a web interface or API responses that can be cached.
• Asynchronous Processing: Offload non-critical tasks from the request/response cycle. For instance, logging clicks or updating analytics can be done via message queues and background workers (Kafka, RabbitMQ, etc.), so the user’s request to shorten or redirect isn’t slowed down (What is asked in a system design interview?). This keeps the core operations (generating a short link or looking one up) fast, while heavy processing happens in the background.
• Auto-Scaling: In cloud environments, set up auto-scaling for your service instances. This means the system can automatically add more servers during traffic spikes and remove them during low usage. Auto-scaling ensures the shortener service remains responsive under varying loads without manual intervention, providing elasticity and cost efficiency.

3. SQL or NoSQL – what’s the right database choice for a URL shortener, and why use key-value stores?

A URL shortener’s storage needs are simple (map short code → long URL), and the choice between SQL and NoSQL often comes down to scalability vs. consistency requirements. In practice, many URL shorteners opt for NoSQL or key-value databases for performance:

• NoSQL (Key-Value Store): NoSQL databases like DynamoDB or Cassandra are designed to scale horizontally across many servers, handling high write/read throughput with low latency. They fit this use case well – the data model is a simple key-value mapping. This means lookups by short code are fast and easy to distribute. For example, a NoSQL store can partition data by short code hash, allowing the service to scale to billions of entries. (In short, NoSQL is chosen for scalability and performance, whereas SQL can become a bottleneck at large scale (What is asked in a system design interview?).)
• SQL (Relational DB): A relational database can certainly store URL mappings and ensures strong consistency (ACID properties). However, scaling a single SQL database to internet-scale often requires sharding and careful tuning, which adds complexity. SQL might be used if the system requires complex queries or transactions (which most URL shorteners don’t need) or strict consistency. In most cases, the simpler access patterns of a URL shortener favor a distributed NoSQL solution (What is asked in a system design interview?), using the relational database either for smaller-scale systems or where strong consistency overrides scaling needs.

4. What security measures protect a URL shortener service?

• Rate Limiting: Enforce limits on how many requests (or URL-create operations) each user or IP can make in a given time frame. This prevents abuse such as spamming the service with too many URLs or DDoS attacks (Common System Design Interview Examples (With Solutions)). For example, the system might allow only a certain number of shorten requests per minute per user.
• Blacklists: Maintain a blacklist of disallowed URLs or domains. If a user tries to shorten a link known to be malicious, phishing, or otherwise unsafe, the service should reject it. Similarly, you might blacklist abusive users or IPs from using the API if they violate terms. This helps keep the platform free of known spam or malware links.
• Authentication: Require user accounts or API keys for generating URLs, especially for advanced features (like custom aliases or bulk shortening). Authentication ensures accountability and makes it harder for anonymous actors to misuse the service (What is asked in a system design interview?). For instance, only logged-in users might be allowed to create a large number of short URLs, which deters bots and attackers.
• Bot Detection: Implement bot detection and mitigation (e.g., CAPTCHAs or anomaly detection algorithms). If the system notices a single client creating or accessing thousands of short URLs in a short time, it could be an automated bot. The service should flag or throttle such behavior. Techniques include challenge-response tests (CAPTCHA), analyzing request patterns, and integrating bot detection services to differentiate real users from scripts.
• Malware Scanning: Integrate security checks for target URLs. When a new URL is submitted, the shortener can scan it using malware/phishing databases or services (like Google Safe Browsing). This ensures the generated short link doesn’t direct users to a known malicious site. Additionally, on each redirect, the service can perform a quick check against an updated blacklist of URLs/domains to block any that have become unsafe since being shortened.

5. How are short URLs generated (Base62, hashing, counters, etc.)?

Generating unique short codes is a core function of a URL shortener. Several methods are commonly used, each with pros and cons:

• Base62 Encoding: This is a standard way to create compact alphanumeric codes. The idea is to take a number (for example, an auto-incrementing ID) and encode it in a base-62 system (digits 0-9, lowercase a-z, and uppercase A-Z). Base62 can represent large numbers in only a few characters – e.g., a 6-character code in Base62 yields roughly 56 billion combinations. This provides a huge space of unique IDs while keeping the URL short.
• Hashing: In this approach, the service computes a hash of the original URL (using a hash function like MD5 or SHA-256) and then uses a portion of that hash (possibly encoded in Base62) as the short code (Designing a URL Shortening Service like TinyURL). This method ensures the same long URL always maps to the same short code (unless you add randomness). However, hashing can lead to collisions (different URLs yielding the same hash) if not handled carefully, so the system may need to check for collisions and resolve them (for example, by appending an extra character or re-hashing with a salt in case of duplicates).
• Counter/Sequential ID: A simple and popular scheme is to use a global counter or sequence. Each time a new URL needs shortening, increment the counter and use that number as the unique ID. The number is then encoded (often in Base62) to produce the short string. This guarantees unique codes with no collisions and is straightforward to implement. The challenge is ensuring the counter is distributed (if you have multiple servers) or using a centralized service (like a database sequence or a dedicated ID generator service, e.g., Twitter’s Snowflake algorithm) to generate IDs without conflicts.
• UUIDs/Random Strings: Another method is to generate a random unique code for each URL, such as using a UUID or a secure random generator. This doesn’t require keeping a counter, but raw UUIDs are quite long (128 bits). To use them in URLs, they might be Base64/Base62 encoded or truncated. Truly random codes have a very low chance of collision, especially if they are long enough, but you might still check for uniqueness in the database. Some systems pre-generate a list of random codes (or use a Key Generation Service) so that each incoming URL can just pick an unused code. The downside is that purely random or UUID-based codes can be longer than sequential codes and may not be as human-readable, but they are effective for decentralization and avoiding any single point of ID generation.

Each of these methods can be used in real-world URL shorteners, and often a combination is employed (e.g., a counter for most cases and a fallback to random generation if needed, or hashing with a tweak to avoid collisions). The key is to ensure the generated short link is unique, not easily guessable, and sufficiently short. (Designing a URL Shortening Service like TinyURL)

Here are few more related links:

1. What are SOLID design principles?
2. What are the top must-know design patterns?
3. What is the difference between url, urn, and uri?
4. What questions are asked in the system design interview?
5. What are the tradeoffs in system design interviews?