System Design Course – APIs, Databases, Caching, CDNs, Load Balancing & Production Infra
TL;DR
This course outlines the architectural mindset shift required to advance from mid-level to senior engineering, covering foundational system components from single-server setups to database selection (SQL vs. NoSQL) and scaling strategies (vertical vs. horizontal with load balancing).
🎯 The Senior Engineer Mindset & Single-Server Foundations 3 insights
Architectural thinking separates seniors from mid-level developers
Companies pay senior engineers for designing systems from scratch and making trade-off decisions, not just writing code to existing specifications.
Start with a single-server architecture to understand core components
Begin with one server handling web tier, database, and cache to visualize request flow from DNS resolution through HTTP requests before adding complexity.
Web and mobile clients interact with servers differently
Web browsers receive HTML/CSS/JS for rendering while mobile apps typically consume JSON API responses over HTTP for lightweight data interpretation.
🗄️ Database Architecture: Relational vs. Non-Relational 3 insights
SQL databases excel at structured data and transactional integrity
Relational databases like PostgreSQL and MySQL use ACID-compliant transactions and complex joins, making them ideal for banking systems and structured e-commerce data.
NoSQL offers four specialized database types for different use cases
Document stores (MongoDB), wide-column (Cassandra), graph (Neo4j), and key-value (Redis) databases provide flexibility and speed for unstructured data at massive scale.
Choose databases based on data structure and consistency requirements
Use SQL for structured data requiring strong consistency and NoSQL for low-latency, flexible storage of semi-structured data like user activity logs.
⚖️ Scaling Strategies and Load Distribution 3 insights
Vertical scaling hits hard limits and creates single points of failure
Adding CPU/RAM to a single server is simple but eventually reaches hardware caps and offers no redundancy if the server crashes.
Horizontal scaling enables fault tolerance through multiple servers
Distributing load across multiple servers allows continuous operation during individual server failures and supports growth by adding nodes rather than upgrading hardware.
Load balancers distribute traffic using algorithms like round robin
Load balancers sit between clients and server pools to route requests sequentially across available servers and automatically stop sending traffic to failed nodes.
Bottom Line
Master system design by starting with simple single-server architectures, choosing SQL for transactional consistency or NoSQL for flexibility and scale, and implementing horizontal scaling with load balancers to handle production traffic reliably.
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