First Move (11~18) - Code, Learn, Build
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First Move (11~18) - Code, Learn, Build

Structured, level-based technology learning paths from foundational exploration to industry mastery.

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  • Python Programming (Active)
  • Computer Science Core
  • Web Development
  • AI & Machine Learning

Platform Architecture

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  • Modular Code Execution Engine
  • Curated Official Resources

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← System Design & Scalable Architecture|Level 1: Scalability Metrics & Load Balancing Patterns

1. System Metrics: Latency, QPS, Availability Nines & Capacity Math

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System Metrics: Latency, QPS, Availability Nines & Capacity Math

Calculate Back-of-the-Envelope QPS math, storage sizing, latency p99 metrics, and evaluate horizontal vs vertical scaling.

Learning Objectives & Back-of-the-Envelope Estimation

### Learning Objectives - Convert Daily Active Users (DAU) into Queries Per Second (QPS) average and peak workloads. - Evaluate SLA availability thresholds (99.9% vs 99.99% "four nines"). - Distinguish between Vertical Scaling (Scale-Up) and Horizontal Scaling (Scale-Out). - Understand Latency percentiles (p50, p95, p99 tail latency). --- ### Back-of-the-Envelope Estimation Rules - $1 ext{ Day} = 86,400 ext{ seconds} approx 10^5 ext{ seconds}$. - **QPS Equation**: $ ext{QPS} = rac{ ext{Daily Active Users} imes ext{Requests per User}}{86,400}$. - **Peak QPS**: $ ext{Average QPS} imes 2$.
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