Scaling Systems from Zero to Millions of Users

Routes HTTP requests to the load balancer.

Provides the IP address of the requested domain.

Caches static content for faster delivery.

Directly manages connections between users and servers.

It supports relational joins.

It requires less storage space than XML.

It is simple and easy to parse.

It is compatible with relational databases by default.

It does not improve database redundancy.

It requires splitting data into multiple shards.

It increases latency for read operations.

It prevents adding more memory to the server.

It defines relationships between tables in a database.

It determines how data is distributed across shards.

It improves the cache hit ratio for frequently accessed data.

It ensures low latency for all database queries.

By storing session data for web servers.

By caching database queries for faster responses.

By routing traffic to available servers when one fails.

By replacing offline servers with new hardware.

Write-through cache.

Read-through cache.

Write-behind cache.

Cache-first strategy.

It reduces the need for load balancers.

It simplifies scaling and improves fault tolerance.

It allows servers to store session data locally.

It requires fewer web servers to handle traffic.

Increased dependency on CDN services.

All user requests must be routed to the same server.

Difficulty in maintaining database consistency.

Inefficiency in handling write-heavy traffic.

To replicate data across different regions.

To cache data closer to the user.

To route traffic to the nearest data center.

To load balance traffic between multiple servers.

Managing server-side caching policies.

Synchronizing data across data centers.

Adding redundancy to the load balancer.

Handling high write-to-read traffic ratios.

To handle join operations in sharded databases.

To distribute and decouple asynchronous tasks.

To maintain consistency across data centers.

To balance traffic between database shards.

By adding redundancy to the data tier.

By distributing data across multiple servers.

By reducing the number of write operations.

By enabling dynamic joins across databases.

Increasing the CPU capacity of affected shards.

Allocating specific shards to high-traffic users.

Using vertical scaling to handle additional load.

Implementing sticky sessions at the web tier.