What high level design encompasses in HLD - Scalability & System Analysis

Scalability Analysis - What high level design encompasses

Growth Table: What Changes at Each Scale

Users	System Components	Design Focus	Challenges
100 users	Single server, simple database	Basic architecture, clear modules	Basic reliability and usability
10,000 users	Multiple servers, load balancer, database replicas	Scalability, fault tolerance	Handling concurrent requests, data consistency
1 million users	Distributed services, caching layers, sharded databases	High availability, performance optimization	Data partitioning, network latency, failover
100 million users	Global data centers, CDN, microservices, event-driven systems	Global scalability, disaster recovery	Data synchronization, cost management, complex monitoring

First Bottleneck

At the start, the database is usually the first bottleneck because it handles all data storage and queries. As users grow, the single database server struggles with read/write operations and connection limits.

Scaling Solutions

• Vertical Scaling: Upgrade server hardware to handle more load temporarily.
• Horizontal Scaling: Add more servers behind load balancers to distribute traffic.
• Caching: Use caches like Redis or Memcached to reduce database load.
• Database Replication: Use read replicas to spread read queries.
• Sharding: Split database into parts to handle more data and queries.
• Content Delivery Network (CDN): Cache static content closer to users to reduce latency.

Back-of-Envelope Cost Analysis

Assuming 10,000 users with 1 request per second each:

• Requests per second: 10,000 QPS
• Database: Needs to handle ~10,000 QPS (likely requires replicas and caching)
• Storage: Depends on data size per user; e.g., 1MB/user -> 10GB total
• Bandwidth: 10,000 QPS * 100KB response ≈ 1GB/s (8Gbps network needed)

Interview Tip

Start by explaining the main components of high level design: modules, data flow, and interactions. Then discuss how these components change as the system scales. Always mention bottlenecks and your approach to solve them step-by-step.

Self Check Question

Your database handles 1000 QPS. Traffic grows 10x. What do you do first?

Answer: Add read replicas and implement caching to reduce load on the main database before considering more complex solutions.

Key Result

High level design starts simple but must evolve with user growth by adding scalability, fault tolerance, and performance optimizations to handle bottlenecks like databases and servers.