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HLDsystem_design~12 mins

Cache invalidation strategies in HLD - Architecture Diagram

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LearnWhyDeepArchPracticeChallengeDesignRecallScale
System Overview - Cache invalidation strategies

This system explains how cache invalidation strategies work to keep cached data fresh and consistent with the main database. It focuses on common methods to update or remove stale data from the cache to ensure users get accurate information quickly.

Architecture Diagram
User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
Service Layer
  |
  +-------------------+
  |                   |
  v                   v
Cache <------------ Database
  |                   |
  +----> Message Queue <
       (for async updates)
Components
User
client
Initiates requests to the system
Load Balancer
load_balancer
Distributes incoming requests evenly to API Gateway instances
API Gateway
api_gateway
Handles client requests, routes them to appropriate services
Service Layer
service
Processes business logic, manages cache and database interactions
Cache
cache
Stores frequently accessed data for fast retrieval
Database
database
Stores the source of truth data
Message Queue
queue
Handles asynchronous cache invalidation or update messages
Request Flow - 11 Hops
User → Load Balancer
Load Balancer → API Gateway
API Gateway → Service Layer
Service Layer → Cache
Cache → Service Layer
Service Layer → Database
Database → Service Layer
Service Layer → Cache
Service Layer → User
Service Layer → Message Queue
Message Queue → Cache
Failure Scenario
Component Fails:Cache
Impact:Cache misses increase, causing more direct database queries and higher latency
Mitigation:System continues to serve data from database; cache rebuilds on demand; consider cache replication or fallback strategies
Architecture Quiz - 3 Questions
Test your understanding
Which component is responsible for distributing incoming user requests evenly?
ALoad Balancer
BAPI Gateway
CCache
DMessage Queue
Design Principle
This architecture demonstrates the importance of asynchronous cache invalidation to keep cached data fresh without blocking user requests, improving system responsiveness and scalability.