Our system would be read-heavy; there would be lots of redirection requests compared to new URL shortenings. Let's assume a 100:1 ratio between read and write.

• Traffic estimates: If we assume that we would have 500 Million new URL shortenings per month, we can expect (100 * 500 Million => 50 Billion) redirections during the same time. What would be Queries Per Second (QPS) for our system?

New URL shortenings per second:

URL redirections per second:

• Storage estimates: Since we expect to have 500M new URLs every month, if we were to keep these objects for five years, the total number of objects we would be storing would be 30 billion:

Let's assume that each object we are storing can be of 500 bytes (just a ballpark figure, we will dig into it later); we would need 15 TB of total storage:

• Bandwidth estimates: For write requests, since every second we expect 200 new URLs, the total incoming data for our service would be 100 KB per second:

For read requests, since every second we expect ~19K URLs redirections, the total outgoing data for our service would be 9 MB per second:

• Memory estimates: If we want to cache some of the hot URLs that are frequently accessed, how much memory would we need to store them? If we follow the 80-20 rule, meaning 20% of URLs generating 80% of traffic, we would like to cache this 20% of hot URLs.

Since we have 19K requests per second, we would be getting 1.7 billion requests per day:

To cache 20% of these requests, we would need 170 GB of memory: