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HLDsystem_design~12 mins

Alerting thresholds in HLD - Architecture Diagram

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LearnWhyDeepArchPracticeChallengeDesignRecallScale
System Overview - Alerting thresholds

This system monitors application and infrastructure metrics to detect issues early. It uses alerting thresholds to trigger notifications when metrics cross defined limits, helping teams respond quickly to problems.

Architecture Diagram
User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
Metrics Collector ---> Cache
  |                    |
  v                    v
Alerting Engine <---- Database
  |
  v
Notification Service
  |
  v
User
Components
User
user
Receives alerts and configures thresholds
Load Balancer
load_balancer
Distributes incoming API requests evenly
API Gateway
api_gateway
Routes requests to Metrics Collector and Alerting Engine
Metrics Collector
service
Collects real-time metrics from monitored systems
Cache
cache
Stores recent metrics for fast access
Database
database
Stores historical metrics and alert configurations
Alerting Engine
service
Evaluates metrics against alerting thresholds
Notification Service
service
Sends alerts to users via email, SMS, or other channels
Request Flow - 9 Hops
User → Load Balancer
Load Balancer → API Gateway
API Gateway → Database
Metrics Collector → Cache
Metrics Collector → Database
Alerting Engine → Cache
Alerting Engine → Database
Alerting Engine → Notification Service
Notification Service → User
Failure Scenario
Component Fails:Database
Impact:New threshold configurations cannot be saved or read; historical metrics unavailable; alerting engine may use stale data
Mitigation:Use database replication and failover; alerting engine relies on cache for recent metrics and thresholds temporarily
Architecture Quiz - 3 Questions
Test your understanding
Which component stores recent metrics for fast access?
ADatabase
BAPI Gateway
CCache
DNotification Service
Design Principle
This architecture uses caching to reduce latency for metric reads and alert evaluation. It separates concerns by using dedicated services for metrics collection, alert evaluation, and notifications. Load balancing and API gateway ensure scalability and routing. The system handles failures by relying on cache and replication to maintain availability.