System requirements

Functional:

1. The system should be able to generate a tinyURL for a given URL
2. The system should be able to re-direct to the original URL
3. May be monitor which one is a popular URL which is being shortened

Non-Functional:

1. Low latency, there should be no latency , it should be easy to create a shortURL and seemless to re-direct to the full URL
2. Scalable
3. Highly available -- the system should be able to function even where are failures, to ensure fault-tolerance and high reliability

Capacity estimation

Let's assume total customer size is 1M

And 10% of the customer size uses the system on a daily basis ==> roughly 10000 users/ day

In which lets say there 5 reads per 1 write

Data I will store:

1. For shortening purposes: I will need the timeStamp, user IP, bigURL and tinyURL ( 200 + 10 ) roughly 500bytes , let's call this DB1
2. For Monitoring purposes: I will userId which is there timestamp, IP , count max of 100 bytes, let's call this DB2

Let's say all 10000 users create tinyURL ==> 10000 * 500= 5 MB/ day for DB1.

For DB2 100* 10000 is roughly 1MB/ day

that is DB1 will be 300MB/ month in peak times we can estimate like (300 MB * 1000/ month) roughly 300GB

and for DB2 1MB * 30 ==> 30MB/ month and in peak time it will 30 GB

Both are not large boundaries, so I want to use in-memory data base for the caching layer owing to its high availability and low latency which are very important for this system and then use NoSQL in the back ground to persist the database

API design

1. create API -- this will let us create a tinyURL for the given URL using some kind of hashing algorithm (output will be tinyUrl.co/<tiny-url>
2. redirect API -- this API should send a response of 302 with the actual URL for the corresponding tinyURL so that the browser can redirect the request to that URL
3. analysis -- mainly tell how many users have used this create a new tinyURL in a day (more for monitoring purposes)

Database design

The prefect database for this will be a persistent key-value store (Redis or memcached); because we need to account for peak traffics we need to have NoSQL in the background which will ensure seemless scalabilty while leveraging the benefits of memcached/Redis in the caching layer

• As the data does not change often , a worker service will periodically move the data from cache to the backend NoSQL and remove expired URLs

High-level design

You should identify enough components that are needed to solve the actual problem from end to end. Also remember to draw a block diagram using the diagramming tool to augment your design. If you are unfamiliar with the tool, you can simply describe your design to the chat bot and ask it to generate a starter diagram for you to modify...

Request flows

Explain how the request flows from end to end in your high level design. Also you could draw a sequence diagram using the diagramming tool to enhance your explanation...

Detailed component design

Dig deeper into 2-3 components and explain in detail how they work. For example, how well does each component scale? Any relevant algorithm or data structure you like to use for a component? Also you could draw a diagram using the diagramming tool to enhance your design...

Trade offs/Tech choices

Explain any trade offs you have made and why you made certain tech choices...

Failure scenarios/bottlenecks

Try to discuss as many failure scenarios/bottlenecks as possible.

Future improvements

What are some future improvements you would make? How would you mitigate the failure scenario(s) you described above?