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HLDsystem_design~12 mins

Why distributed patterns solve common challenges in HLD - Architecture Impact

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System Overview - Why distributed patterns solve common challenges

This system demonstrates how distributed architectural patterns help solve common challenges like scalability, fault tolerance, and latency. It shows how splitting work across multiple services and using components like load balancers, caches, and message queues improves reliability and performance.

Architecture Diagram
User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  +-------------------+
  |                   |
  v                   v
Service A           Service B
  |                   |
  v                   v
Cache A             Cache B
  |                   |
  v                   v
Database A          Database B
  |
  v
Message Queue
  |
  v
Worker Service
Components
User
client
Initiates requests to the system
Load Balancer
load_balancer
Distributes incoming requests evenly to API Gateway instances
API Gateway
api_gateway
Routes requests to appropriate backend services and handles authentication
Service A
service
Handles a subset of business logic and data processing
Service B
service
Handles another subset of business logic and data processing
Cache A
cache
Stores frequently accessed data for Service A to reduce database load
Cache B
cache
Stores frequently accessed data for Service B to reduce database load
Database A
database
Stores persistent data for Service A
Database B
database
Stores persistent data for Service B
Message Queue
message_queue
Queues asynchronous tasks to be processed by worker services
Worker Service
service
Processes background tasks asynchronously from the message queue
Request Flow - 14 Hops
User → Load Balancer
Load Balancer → API Gateway
API Gateway → Service A
Service A → Cache A
Cache A → Service A
Service A → Database A
Database A → Service A
Service A → Cache A
Service A → API Gateway
API Gateway → Load Balancer
Load Balancer → User
Service A → Message Queue
Message Queue → Worker Service
Worker Service → Database A
Failure Scenario
Component Fails:Database A
Impact:Service A cannot write or read fresh data; cache may serve stale data
Mitigation:Reads served from cache if available; database replication and failover can restore availability
Architecture Quiz - 3 Questions
Test your understanding
Why does the system use a load balancer before the API Gateway?
ATo evenly distribute incoming requests and avoid overloading a single API Gateway instance
BTo store frequently accessed data for faster responses
CTo queue background tasks for asynchronous processing
DTo directly connect users to the database
Design Principle
This architecture shows how distributing responsibilities across multiple components like load balancers, API gateways, caches, databases, and message queues helps solve challenges of scalability, fault tolerance, and latency. Each component focuses on a specific role, enabling the system to handle more users, recover from failures, and respond faster.