A comprehensive AWS-based solution for monitoring API performance and uptime across multiple regions with automated alerting and visualization.

This system provides:

• Scheduled Monitoring: EventBridge triggers Lambda functions every 5 minutes
• Multi-Region Support: Monitor APIs from us-east-1, eu-west-1, and ap-south-1
• Performance Tracking: Record latency, status codes, and availability metrics
• Automated Alerting: CloudWatch Alarms with SNS notifications
• Data Storage: Metrics in CloudWatch, detailed logs in DynamoDB
• Visualization: CloudWatch Dashboards for trend analysis

• main.tf - Core AWS resources
• variables.tf - Configuration parameters
• outputs.tf - Resource outputs
• terraform.tfvars.example - Example configuration

• src/monitor_api.py - API monitoring logic
• src/requirements.txt - Python dependencies

• config/api_endpoints.json - API endpoints to monitor

1. Prerequisites

   • AWS CLI configured
   • Terraform installed
   • Python 3.9+

2. Setup

   # Clone and navigate to project cd automated-api-health-monitoring # Configure variables cp terraform.tfvars.example terraform.tfvars # Edit terraform.tfvars with your settings # Deploy infrastructure terraform init terraform plan terraform apply

3. Configuration

   • Update config/api_endpoints.json with your APIs
   • Configure SNS notification endpoints
   • Customize CloudWatch alarm thresholds

• HTTP/HTTPS endpoint monitoring
• Response time measurement
• Status code tracking
• Multi-region deployment
• Custom metrics in CloudWatch

• CloudWatch Alarms for latency and availability
• SNS email notifications
• Slack webhook support
• Configurable thresholds

• DynamoDB for detailed monitoring history
• CloudWatch Dashboards
• S3 for log archival
• Trend analysis capabilities

• IAM roles with least privilege
• Encrypted data storage
• VPC endpoints for private APIs
• Resource tagging

┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐ │ EventBridge │───▶│ Lambda (API │───▶│ CloudWatch │ │ (Scheduler) │ │ Monitor) │ │ (Metrics) │ └─────────────────┘ └──────────────────┘ └─────────────────┘ │ │ ▼ ▼ ┌──────────────────┐ ┌─────────────────┐ │ DynamoDB │ │ CloudWatch │ │ (History) │ │ Alarms │ └──────────────────┘ └─────────────────┘ │ ▼ ┌─────────────────┐ │ SNS │ │ (Notifications) │ └─────────────────┘ 

• Availability: Success rate percentage
• Latency: Response time in milliseconds
• Status Codes: HTTP response codes distribution
• Error Rate: Failed requests percentage
• Regional Performance: Cross-region comparison

• Lambda functions use ARM64 architecture for better price/performance
• DynamoDB on-demand pricing for variable workloads
• CloudWatch log retention policies
• S3 lifecycle policies for log archival

• All IAM roles follow least privilege principle
• Encryption at rest for DynamoDB and S3
• VPC endpoints for private API monitoring
• Secrets Manager for sensitive configuration

Edit config/api_endpoints.json:

{ "endpoints": [ { "name": "my-api", "url": "https://api.example.com/health", "method": "GET", "timeout": 30, "expected_status": 200 } ] }

Modify variables in terraform.tfvars:

latency_threshold_ms = 2000 error_rate_threshold = 5

1. Lambda Timeout: Increase timeout in variables.tf
2. Permission Errors: Check IAM role policies
3. Network Issues: Verify VPC configuration for private APIs

• CloudWatch Logs for Lambda execution details
• X-Ray tracing for performance analysis
• DynamoDB metrics for storage health

1. Fork the repository
2. Create a feature branch
3. Make changes following AWS best practices
4. Test thoroughly
5. Submit a pull request

MIT License - see LICENSE file for details