Tutorials System Design Tutorial
Scalability Basics — Complete Guide
Scalability Basics — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of System Design Tutorial on Toolliyo Academy.
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System Design Tutorial · Lesson 3 of 100
Scalability Basics
Basics → Scale → Interview
Basics · 1 — Building blocks · ~6 min · Module 1: System Design Foundations
What is this?
Scalability means handling more load by adding capacity (scale out) or bigger machines (scale up) without rewriting the whole product.
Why should you care?
ShopNest traffic is calm on Tuesday and wild on festival sales. Design for growth before the spike.
See it live — copy this example
Sketch the architecture on paper. These lessons focus on concepts and trade-offs.
Scale up: 1 API VM 4CPU → 1 API VM 16CPU
Scale out: 1 API VM → 4 API VMs + Load Balancer
ShopNest goal: add API replicas without changing Order DB schema.Run Example »
This lesson uses terminal or setup steps. Run commands on your computer — the live editor appears on coding lessons.
What happened?
- Scale up is simple until one machine is maxed.
- Scale out needs a load balancer and usually a shared or partitioned data store.
- Prefer scale out for web tiers.
Practice next
- List ShopNest components that scale out easily (APIs).
- List what is harder (single primary DB).
- Draw before/after with 1 vs 4 API nodes.
- Add a cache so the DB needs less scale.
- Write the max RPS you expect on sale day.
Remember
Scale up vs scale out. Stateless APIs scale out best. Measure before you buy capacity.
Festival API replicas
ShopNest doubles API pods for Diwali week.
Outcome: Checkout latency stays flat as traffic rises.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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