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HLDsystem_design~12 mins

Design a search autocomplete in HLD - Architecture Diagram

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LearnWhyDeepArchPracticeChallengeDesignRecallScale
System Overview - Design a search autocomplete

This system provides search autocomplete suggestions as users type queries. It must return relevant suggestions quickly and handle many users simultaneously. The system should update suggestions based on popular searches and support low latency responses.

Architecture Diagram
User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
Autocomplete Service
  |        |
  v        v
Cache <--> Search Index
  |
  v
Database
Components
User
client
Sends search query input for autocomplete suggestions
Load Balancer
load_balancer
Distributes incoming user requests evenly to API Gateway instances
API Gateway
api_gateway
Receives requests, handles authentication, routing to Autocomplete Service
Autocomplete Service
service
Processes queries, fetches suggestions from cache or search index
Cache
cache
Stores frequently requested autocomplete suggestions for fast retrieval
Search Index
search_index
Maintains indexed data of searchable terms and their popularity
Database
database
Stores raw search data and updates popularity metrics for indexing
Request Flow - 11 Hops
User → Load Balancer
Load Balancer → API Gateway
API Gateway → Autocomplete Service
Autocomplete Service → Cache
Cache → Autocomplete Service
Autocomplete Service → Search Index
Search Index → Autocomplete Service
Autocomplete Service → Cache
Autocomplete Service → API Gateway
API Gateway → Load Balancer
Load Balancer → User
Failure Scenario
Component Fails:Cache
Impact:Cache misses increase, causing higher latency as Autocomplete Service queries Search Index more often
Mitigation:System continues working by querying Search Index directly; cache rebuilds as new queries come in
Architecture Quiz - 3 Questions
Test your understanding
Which component handles distributing user requests to multiple API Gateway instances?
AAutocomplete Service
BLoad Balancer
CCache
DSearch Index
Design Principle
This design uses caching to reduce latency and load on the search index. The load balancer and API gateway ensure scalability and security. The search index enables fast lookup of autocomplete suggestions, while the database supports data updates and popularity tracking.