Capacity estimation

Traffic Estimation:

New URL Shortening Requests:
- Let's assume we expect 500 million new URL shortening requests per month.
- Queries per second (QPS) = 500 million / (30 days * 24 hours * 3600 seconds) ≈ 200 URLs/s
Read/Write Ratio:
- A typical read/write ratio for URL shorteners is around 100:1, meaning 100 redirections (reads) for every 1 new URL creation (write).
- URL redirections per second ≈ 100 * 200 URLs/s = 20,000/s

Storage Estimation:

Data Retention: Let's assume we want to store URL mappings for 5 years.
Total URLs: Over 5 years, we'll store approximately 500 million * 12 months/year * 5 years = 30 billion URLs.
Data per URL:
- Long URL (average 100 characters) = 100 bytes
- Short alias (7 characters) = 7 bytes
- Metadata (timestamps, user ID, etc.) = 50 bytes (estimated)
- Total per URL ≈ 157 bytes
Total Storage: 30 billion URLs * 157 bytes/URL ≈ 4.71 TB
Storage Growth: We need to account for annual growth in data storage needs. Let's assume a 20% annual growth rate.

Memory Estimation (for Caching):

80/20 Rule: Assume 20% of URLs generate 80% of the traffic.
Cache Size: To cache the most frequently accessed URLs, we might need around 20% of 30 billion URLs * 157 bytes/URL ≈ 942 GB of memory.

Bandwidth Estimation:

Ingress (incoming requests): 20,200 requests/s * 150 bytes/request (estimated) ≈ 3 MB/s
Egress (outgoing responses): 20,000 redirections/s * 300 bytes/response (estimated) ≈ 6 MB/s

Key Considerations:

Peak Traffic: These are average estimates. We need to consider peak traffic, which could be significantly higher (e.g., during special events or promotions).
Growth: The system needs to be designed to scale to accommodate future growth in traffic and data storage.
Database Choice: The choice of database (e.g., Redis, DynamoDB, Cassandra) will impact storage and performance considerations.