System Health
System Health provides comprehensive monitoring and analysis of your MIP system's performance, health metrics, and component status. This feature enables real-time tracking of system components, response times, and overall system performance.
Overview
The System Health dashboard offers a centralized view of your integration platform's health status, allowing administrators and developers to:
- Monitor system components in real-time
- Track response times and performance metrics
- Analyze peak usage periods
- View AI-powered health scores
- Identify potential bottlenecks and issues
Key Features
System Components Monitoring
Monitor the health and status of all system components including:
- Integration Flows: Track the status and performance of active integration flows
- Connectors: Monitor connector health and availability
- Message Processing: View message processing statistics
- Resource Utilization: Track CPU, memory, and other resource usage
Response Times Analysis
Analyze response times for different system components:
- View historical response time data
- Identify slow-performing components
- Track response time trends over time
- Compare performance across different time periods
AI Score
The AI-powered health score provides:
- Overall system health rating
- Predictive analysis of potential issues
- Recommendations for optimization
- Trend analysis and forecasting
System Statistics
Comprehensive system statistics including:
- Message Throughput: Total messages processed
- Success/Failure Rates: Processing success and error rates
- Average Response Times: Performance metrics across components
- Resource Usage: System resource consumption
Peak Points Analysis
Identify and analyze peak usage periods:
- View peak traffic times
- Analyze resource consumption during peak periods
- Plan capacity based on historical peak data
- Optimize system performance for high-load scenarios
Date Range Selection
The System Health dashboard supports flexible date range selection:
- Predefined Presets: Today, Yesterday, Last 7 Days, Last 30 Days
- Custom Date Range: Select specific start and end dates
- Real-time Updates: Automatic refresh of metrics
Pod Selection
In multi-pod deployments, you can:
- Select specific pods for monitoring
- Compare performance across different pods
- View pod-specific health metrics
- Aggregate data across all pods
Use Cases
Performance Monitoring
Monitor system performance in real-time to ensure optimal operation and quickly identify any degradation in service quality.
Capacity Planning
Use historical data and peak point analysis to plan for future capacity needs and scale your infrastructure accordingly.
Troubleshooting
Quickly identify problematic components or time periods when issues occur, enabling faster root cause analysis and resolution.
Optimization
Leverage AI-powered insights and detailed metrics to optimize system configuration and improve overall performance.
Best Practices
- Regular Monitoring: Check system health regularly to catch issues early
- Set Baselines: Establish performance baselines for comparison
- Analyze Trends: Review historical data to identify patterns
- Act on Insights: Use AI recommendations to optimize system performance
- Monitor During Changes: Track system health before and after configuration changes