Interview Guide & Cheatsheet

┌─────────────────────────────────────────────────────────────────┐
│              System Design Interview Timeline                   │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  0:00 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0:45   │
│                                                                 │
│  ┌─────────┐ ┌─────────┐ ┌───────────────┐ ┌─────────────────┐ │
│  │ Require-│ │  Esti-  │ │  High-Level   │ │   Deep Dive +   │ │
│  │  ments  │ │ mation  │ │    Design     │ │   Bottlenecks   │ │
│  │  5 min  │ │  5 min  │ │    10 min     │ │     25 min      │ │
│  └─────────┘ └─────────┘ └───────────────┘ └─────────────────┘ │
│                                                                 │
│  Don't rush!  Show your   Draw as you     Focus on 2-3        │
│  Ask questions math!      explain         components deeply    │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

# Daily Active Users → QPS
QPS = DAU × actions_per_user / 86400
Peak_QPS = QPS × 3

# Example: 100M DAU, 10 actions/user
QPS = 100M × 10 / 100K = 10,000 QPS
Peak = 30,000 QPS

# Storage
Daily_Storage = DAU × actions × size_per_action
Yearly_Storage = Daily × 365

# Example: 100M users × 2 posts × 500 bytes
Daily = 100GB, Yearly = 36TB

┌─────────────────────────────────────────────────────────────────┐
│                    Generic System Template                      │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│                         ┌──────────┐                           │
│                         │ Clients  │                           │
│                         └────┬─────┘                           │
│                              │                                  │
│                         ┌────▼─────┐                           │
│                         │   CDN    │ (static assets, media)    │
│                         └────┬─────┘                           │
│                              │                                  │
│                         ┌────▼─────┐                           │
│                         │   LB     │ (load balancer)           │
│                         └────┬─────┘                           │
│                              │                                  │
│         ┌────────────────────┼────────────────────┐            │
│         │                    │                    │             │
│    ┌────▼────┐          ┌────▼────┐          ┌────▼────┐      │
│    │ Service │          │ Service │          │ Service │      │
│    │   A     │          │   B     │          │   C     │      │
│    └────┬────┘          └────┬────┘          └────┬────┘      │
│         │                    │                    │             │
│    ┌────▼────┐          ┌────▼────┐          ┌────▼────┐      │
│    │ Cache   │          │ Queue   │          │ Cache   │      │
│    │ (Redis) │          │ (Kafka) │          │ (Redis) │      │
│    └────┬────┘          └────┬────┘          └────┬────┘      │
│         │                    │                    │             │
│         └────────────────────┼────────────────────┘            │
│                              │                                  │
│                    ┌─────────▼─────────┐                       │
│                    │     Database      │                       │
│                    │  (Primary + Replicas)                     │
│                    └───────────────────┘                       │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

Always define 2-3 core APIs:

POST /api/v1/tweets
─────────────────────────────────────────────
Request:
{
  "content": "Hello world",
  "media_ids": ["abc123"]
}

Response:
{
  "tweet_id": "123456",
  "created_at": "2024-01-15T10:30:00Z"
}

─────────────────────────────────────────────

GET /api/v1/feed?user_id=123&cursor=xxx&limit=20
─────────────────────────────────────────────
Response:
{
  "tweets": [...],
  "next_cursor": "yyy"
}

-- Always include:
-- 1. Primary key (usually BIGINT or UUID)
-- 2. Created/updated timestamps
-- 3. Indexes for common queries

CREATE TABLE users (
    id              BIGINT PRIMARY KEY,
    username        VARCHAR(50) UNIQUE NOT NULL,
    email           VARCHAR(255) UNIQUE NOT NULL,
    password_hash   VARCHAR(255) NOT NULL,
    created_at      TIMESTAMP DEFAULT NOW(),
    updated_at      TIMESTAMP DEFAULT NOW()
);

-- Index for login
CREATE INDEX idx_users_email ON users(email);

-- Think about:
-- □ What queries will we run?
-- □ Which columns need indexes?
-- □ How will we shard if needed?
-- □ What's the partition key?

┌─────────────────────────────────────────────────────────────────┐
│                    Bottleneck Checklist                         │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  □ Single Points of Failure                                    │
│    → Add redundancy (multiple servers, replicas)               │
│                                                                 │
│  □ Database Bottleneck                                          │
│    → Read replicas, caching, sharding                          │
│                                                                 │
│  □ Hot Partitions                                               │
│    → Better shard key, consistent hashing                      │
│                                                                 │
│  □ Cascading Failures                                           │
│    → Circuit breakers, bulkheads, timeouts                     │
│                                                                 │
│  □ Network Latency                                              │
│    → CDN, edge caching, geographic distribution                │
│                                                                 │
│  □ Write Amplification                                          │
│    → Async writes, batching, fan-out optimization              │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

Good answer pattern:

"I chose X over Y because [requirement]. 
The trade-off is [downside], but we can 
mitigate this by [solution]."

Example:

"I chose eventual consistency for the timeline 
because low latency is more important than seeing 
tweets immediately. The trade-off is users might 
not see a tweet for a few seconds, but this is 
acceptable for a social feed."

When choosing between options:
  "The trade-off here is [X] vs [Y]. Given our requirement
  for [Z], I'd lean toward [option] because..."

When discussing scale:
  "At this scale, the bottleneck shifts from [compute/storage]
  to [network/coordination]. Let me show you why..."

When considering failures:
  "If we lose this component, the blast radius is [scope].
  We can mitigate this by [strategy]."

When you are unsure:
  "I'm less certain about this part. My intuition says [X]
  because [reasoning], but I'd want to benchmark this in
  production before committing."

When the interviewer pushes back:
  "That's a fair point. Let me reconsider. If [their concern]
  is the priority, we could [alternative approach], though
  we'd lose [trade-off]."

When wrapping up a component:
  "Before we move on -- are there aspects of this component
  you'd like me to go deeper on?"

□ Review the framework (5-5-10-20-5 minutes)
□ Memorize key numbers (QPS, latency, storage)
□ Practice 3-5 problems end-to-end, timed
□ Have a drawing tool ready (Excalidraw, paper)
□ Prepare clarifying questions for common problems
□ Review common trade-offs (SQL vs NoSQL, push vs pull,
  strong vs eventual consistency)
□ Practice capacity estimation out loud (not in your head)
□ Review your own past systems -- interviewers love when
  you reference real experience
□ Get good sleep!