Fundamentals of Backend Architecture - How to Design Scalable Software — Summary & Key Points

TiagoJun 8, 202648:1298K views

TL;DR

Tiago traces the architectural evolution of a Google Drive clone from a single server to a distributed microservices system, explaining how to decouple data from machines, manage traffic with load balancers, and handle file uploads using object storage and message queues. The core lesson is that good architecture supports business scalability, not just code implementation.

Key Quotes

"Data coupled to the machine equals no scale and no resilience."
Tiago

Steps

Separate data from the server

Move data from the server instance to a relational database to ensure persistence and resilience. If the server dies, the data remains in the database.

Implement a load balancer

Add a load balancer to distribute traffic across multiple server instances using algorithms like round robin or sticky sessions to handle increased load.

Scale horizontally or vertically

Add more machines for horizontal scaling or upgrade a single machine for vertical scaling, utilizing autoscalers like Kubernetes to adjust resources dynamically.

Introduce microservices and an API gateway

Break the application into specialized services (files, auth, notifications) and use an API gateway to route, aggregate, and authenticate requests while keeping services private.

Use object storage for files

Generate a presigned upload URL from the file service and redirect the client to upload directly to S3 or a cloud bucket instead of sending bytes to your server or database.

Adopt an event-driven architecture

Use a message broker like Kafka or RabbitMQ to asynchronously notify services (like thumbnail generation) when files are uploaded, ensuring reliability even if a service is down.

Optimize with caching and CDNs

Cache file metadata in Redis for fast access and serve large assets via a Content Delivery Network (CDN) to reduce latency for users around the world.

Apply rate limiting

Use a cache-based rate limiter to track request counts per user or IP and block abuse to protect infrastructure resources from malicious actors.

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