Problem Statement
Design a URL shortener service like bit.ly that can shorten long URLs and redirect users to original URLs when they access the short link.
Requirements Gathering
Functional Requirements
- Shorten long URLs
- Redirect short URLs to original URLs
- Custom aliases (optional)
- Link expiration (optional)
Non-Functional Requirements
- High availability
- Low latency (redirect should be fast)
- Scalable to billions of URLs
- URLs should be as short as possible
Capacity Estimation
Assume 100M new URLs per month. That's about 40 URLs per second for writes. For reads, assume 100:1 read:write ratio = 4,000 reads/second.
System Design
URL Encoding
Use base62 encoding (a-z, A-Z, 0-9) to generate short URLs. With 6 characters, we can store 62^6 = 56.8 billion URLs.
Database Schema
Store mappings of short URL to original URL. Use NoSQL for better scalability or SQL with proper indexing.
Architecture
- Load balancer to distribute traffic
- Application servers to handle requests
- Database to store URL mappings
- Cache (Redis) for frequently accessed URLs
Key Design Decisions
- Use hash function or counter for URL generation
- Cache popular URLs to reduce database load
- Use database sharding for scale
- Implement rate limiting to prevent abuse
Conclusion
This case study combines cache-aside caching with database sharding and replication. Practice designing other systems like Twitter, Instagram, or Uber to strengthen the same trade-off-driven approach.
A Practical Mental Model for Designing a URL Shortener
A URL shortener maps a compact, unique code to a destination URL and redirects reads with very low latency. The definition matters, but the more useful skill is connecting it to a user-visible goal and a measurable operating limit. A design is convincing when it explains what improves, what becomes more complex, and what evidence would trigger the next change.
The design needs an ID-generation strategy, a durable mapping store, a redirect API, caching for popular codes, abuse controls, and clear behavior for expiration and deletion. Draw the critical request path first. For every hop, name the work performed, the state read or changed, and the way that hop can fail. This prevents a diagram full of boxes from hiding the actual behavior.
A simple way to reason about designing a url shortener is to separate four concerns: correctness, performance, availability, and operability. Correctness protects user and business invariants. Performance defines latency and capacity. Availability describes degradation during failure. Operability covers deployment, observation, recovery, and cost. Improving one concern can make another harder, so every design choice needs a stated priority.
Worked Example and Capacity Reasoning
Estimate 100 million new links per month and a 100:1 read-to-write ratio. Generate a unique numeric ID, encode it in Base62, store the code-to-URL mapping, and cache popular mappings. Redirect with 302 when analytics or destination changes matter; use 301 only for intentionally permanent mappings.
Turn the narrative into numbers before selecting infrastructure. Estimate average and peak request rates, the read-to-write ratio, payload size, retained data, and acceptable response time. Add headroom for traffic bursts and failures, but show the arithmetic. The goal is not a perfect forecast; it is to distinguish a design that needs one machine from one that needs partitioning, replication, or asynchronous processing.
Next, trace one successful request and one failed request. The successful trace validates the normal data flow. The failed trace forces decisions about timeouts, retries, idempotency, stale data, and user feedback. If the system can only be explained while every dependency is healthy, the design is incomplete.
Design Decisions to Make Explicit
Choose random codes, range-allocated sequence IDs, or a distributed ID service based on collision handling and predictability requirements. In production, validate this with a small experiment or load test, then expose a metric and an alert that show whether the decision still holds. In an interview, state the trade-off plainly instead of presenting the choice as universally correct.
Partition mappings by a stable hash of the short code so popular creation times do not hotspot one shard. In production, validate this with a small experiment or load test, then expose a metric and an alert that show whether the decision still holds. In an interview, state the trade-off plainly instead of presenting the choice as universally correct.
Keep redirect reads on a short path with cache-aside lookup and negative caching for invalid codes. In production, validate this with a small experiment or load test, then expose a metric and an alert that show whether the decision still holds. In an interview, state the trade-off plainly instead of presenting the choice as universally correct.
Add rate limits, malware checks, ownership rules, and asynchronous analytics without delaying redirects. In production, validate this with a small experiment or load test, then expose a metric and an alert that show whether the decision still holds. In an interview, state the trade-off plainly instead of presenting the choice as universally correct.
These decisions should appear next to the component they affect. A short annotation such as “p99 under 250 ms,” “eventual consistency under 30 seconds,” or “survives one availability-zone failure” makes the diagram testable. Without a target, terms such as fast, scalable, and highly available are only aspirations.
Common Failure Modes
- 1. A predictable sequence exposes business volume and makes enumeration easier. For Designing a URL Shortener, document the expected behavior, the capacity assumption behind it, and the fallback when that assumption stops being true.
- 2. A hot viral link overloads one cache node or storage partition. For Designing a URL Shortener, document the expected behavior, the capacity assumption behind it, and the fallback when that assumption stops being true.
- 3. Synchronous click analytics increases redirect latency and availability coupling. For Designing a URL Shortener, document the expected behavior, the capacity assumption behind it, and the fallback when that assumption stops being true.
- 4. Deleted or expired codes are immediately reused and redirect old links to an unrelated destination. For Designing a URL Shortener, document the expected behavior, the capacity assumption behind it, and the fallback when that assumption stops being true.
Do not try to eliminate every failure. Decide which failures must be masked, which can produce a degraded response, and which should reject new work quickly. Bounded queues, deadlines, bulkheads, and circuit breakers are often safer than unlimited retries. Recovery also needs verification: regularly test restores, failovers, rebalancing, and rollback paths before an incident makes them necessary.
Observability and Production Readiness
At minimum, monitor redirect p95 and p99 latency, cache hit ratio, code creation and collision rate, invalid and abusive request rate. Break metrics down by endpoint, dependency, region, or partition where an aggregate could conceal a hotspot. Pair metrics with structured logs for local detail and distributed traces for request paths that cross service boundaries.
Alerts should describe user impact or exhausted safety margin, not every small fluctuation. Use service-level objectives to connect telemetry to a promise: for example, 99.9% of valid requests succeed and 99% finish within the target latency over a rolling window. Add dashboards for traffic, errors, duration, saturation, and deployment markers so an operator can see whether a regression began with load, a dependency, or a release.
Capacity planning is continuous. Record the tested limit, current peak, growth rate, and time required to add capacity. If the system needs thirty minutes to scale safely, an alert at ninety-nine percent utilization is too late. Operational readiness is part of system design because a component that cannot be observed or recovered is not dependable.
How to Explain This in a System Design Interview
- Clarify the requirement. Ask which user action depends on designing a url shortener and define the success target.
- Estimate demand. Calculate peak traffic, data size, and the ratio that drives the design.
- Start simple. Present the smallest architecture that meets the current requirement before adding distributed machinery.
- Find the limit. Explain which resource or failure domain breaks first and how you know.
- Evolve the design. Add the next mechanism, then state its cost, consistency effect, and operational burden.
- Close with failure handling. Walk through one dependency failure and the metrics that reveal it.
This sequence demonstrates judgment. Interviewers usually care less about naming a particular product than about whether you can defend boundaries and adapt when a requirement changes. If a managed service is useful, describe the capability you need first, then mention the product as one implementation.
Review Checklist
- Is the functional scope clear, including what is deliberately excluded?
- Are peak traffic, storage, bandwidth, and latency targets quantified?
- Does every important write have an owner, durability rule, and idempotency strategy?
- Are consistency and staleness visible to the user explained?
- Can the design tolerate one instance, zone, or dependency failure as required?
- Are queues and retries bounded, and is overload rejected or degraded intentionally?
- Can an operator detect, diagnose, roll back, and recover the system?
- Is the next scaling step identified without paying for it prematurely?
Want a guided way to practice these trade-offs? Continue in System Design Fundamentals for Interviews on Udemy, which connects the concepts through complete interview case studies.
Continue Learning
Use the complete System Design interview-preparation guide to place this topic in a four-week roadmap. Then apply the same reasoning to the System Design case-study collection, where requirements, estimates, bottlenecks, and failure modes are combined in end-to-end designs.