v4.0
Reference
Everything you need to know cold on interview day. Keep this open in another tab.
Universal constants
  • 1 day = 86,400 seconds
  • 1 month ≈ 2.5 M seconds  ·  1 year ≈ 31.5 M seconds
  • Peak multiplier: 5× average (consumer APIs)  ·  10× (notifications / events)
  • Concurrent users ≈ 10% of DAU at any moment
  • Read/write ratio typical: 100:1 for social feeds, 10:1 for e-commerce
The 5-step framework
  • Clarify: state assumptions, scale, consistency, edge cases — out loud
  • Traffic: DAU × actions/day ÷ 86,400 = avg RPS → ×5 (or ×10) = peak
  • Storage: entities/day × bytes/entity × retention days
  • Bandwidth: peak RPS × payload × 8 bits = bps
  • Scale: ops_needed ÷ component_capacity = nodes → ×3 replication
Component throughput
Redis single node~100K ops/s
MySQL / Postgres write5K–10K/s
Cassandra per node~50K writes/s
Kafka single broker~1M msgs/s
Elasticsearch per node~5K writes/s
S3 / object storage~3.5K req/s per prefix
Load balancer (L7)~100K req/s
SSD random IOPS100K IOPS
HDD sequential100 MB/s
Latency numbers (know these cold)
L1 cache reference~0.5 ns
L2 cache reference~7 ns
RAM access~100 ns
SSD random read~150 μs
HDD random read~10 ms
Same-DC network RTT~0.5 ms
Cross-region RTT (US↔EU)~80 ms
Cross-region RTT (US↔Asia)~150 ms
TCP handshake (local)~1 ms
Storage sizes
UUID / GUID16 B
Unix timestamp (int64)8 B
Average user record~1 KB
Tweet / short message~200–500 B
Redis key overhead~60 B
MySQL row overhead~100 B
Photo (JPEG compressed)~300 KB
Video 1 min 720p~50 MB
Video 1 min 4K~375 MB
Powers of 2
210 = 1 KB1,024
220 = 1 MB1,048,576
230 = 1 GB1,073,741,824
240 = 1 TB~1 trillion
250 = 1 PB~1 quadrillion
Quick rules of thumb
  • 1M users × 1 KB = 1 GB storage
  • 1M req/day ÷ 86,400 ≈ 12 RPS
  • 100M DAU × 10 actions = ~12K avg RPS (×5 peak = 60K RPS)
  • 1 TB/day ÷ 86,400 ≈ 12 MB/s ingress
  • Replication factor 3 → multiply raw storage × 3
  • Index overhead ≈ 10–20% on top of data size
Glossary
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