Scalability

A great generic plan for scaling any app from zero to millions of users.

• Single server setup
• Selection and usage of database
• Vertical scaling vs horizontal scaling approaches. And why you should prefer horizontal
• Adding load balancer for horizontal scaling
• Adding database replication for horizontal scaling
• Adding cache
• Adding CDN
• Stateless vs Stateful architecture and using external state storage
• Adding extra Data Centers
• Adding Message queue
• Adding Logging, Metrics, and Automation
• Scaling database (sharding)
• and futher steps…

All of these is carefully but briefly disclosed in the Chapter 1 of the book:

Introduction into Event-driven microservice (EDM) architecture consists of the following topics:

• two topologies
• content of events
• three types of events
• table-stream duality
• schemas for defining event data
• single writer principle
• features of event broker
• event broker vs message broker
• single source of truth principle
• scaling using containers and VMs
• microservice taxes that we should pay

These topics are disclosed in the Chapter 2 of the book we are currently studying:

Earlier this year the book club of our company has studied excellent book:

Martin Kleppmann - Designing Data-Intensive Applications

This is the best book I have read about building complex scalable software systems. 💪

As usually (to better learn) I prepared an overview and mind-map.

Chapter 1:

• Building blocks of the apps
• What is Reliability, Scalability and Maintainability. Examples and definitions.
  • Faults and Failures
  • Performance, Load, Latency and Response Time
  • Operability, Simplicity, Evolvability
• Why you should randomly kill your servers 😅
• How Twitter delivers 12,000 tweets per second to 300,000 readers per second. (VERY interesting!)
• How much money Amazon loses for each 100ms delay in their response time
• How to quickly calculate percentiles for monitoring response time in PROD

Download full mind map (PDF)