System Overview - Search functionality design
This system allows users to search for information quickly and accurately. It must handle many users at once and return results fast, even when the data is large and frequently updated.
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Search functionality design in LLD - Architecture Diagram
Architecture Diagram
User | v Load Balancer | v API Gateway | v Search Service <-> Cache | v Search Index | v Primary Database
Components
User
client
Initiates search requests
Load Balancer
load_balancer
Distributes incoming requests evenly to API Gateway instances
API Gateway
api_gateway
Routes requests to Search Service and handles authentication
Search Service
service
Processes search queries, checks cache, queries search index
Cache
cache
Stores recent search results for fast retrieval
Search Index
search_index
Optimized data structure for fast full-text search
Primary Database
database
Stores the original data and updates the search index
Request Flow - 11 Hops
User → Load Balancer
Load Balancer → API Gateway
API Gateway → Search Service
Search Service → Cache
Cache → Search Service
Search Service → Search Index
Search Index → Search Service
Search Service → Cache
Search Service → API Gateway
API Gateway → Load Balancer
Load Balancer → User
Failure Scenario
Component Fails:Cache
Impact:Search Service cannot retrieve cached results, causing increased load on Search Index and higher latency
Mitigation:System continues to function by querying Search Index directly; cache is rebuilt as new queries come in
Architecture Quiz - 3 Questions
Test your understanding
Which component is responsible for distributing incoming user requests evenly?
Design Principle
This design uses caching to reduce load on the search index and speed up responses. The load balancer and API gateway ensure requests are managed efficiently and securely. Separating the search index from the primary database allows optimized search performance without affecting data storage.