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Monitoring & Alerting Documentation

Overview

This document outlines the comprehensive monitoring and alerting strategy for the Dispatch Center Application, covering application performance, infrastructure health, business metrics, and incident response procedures.

Table of Contents

Monitoring Architecture

flowchart TB
    app_insights["Application<br/>Insights"]
    azure_monitor["Azure Monitor<br/>Workspace"]
    alert_manager["Alert<br/>Manager"]
    custom_dashboards["Custom<br/>Dashboards"]
    log_analytics["Log Analytics<br/>Queries"]
    notification_channels["Notification<br/>Channels"]

    app_insights --> azure_monitor
    azure_monitor --> alert_manager
    app_insights --> custom_dashboards
    azure_monitor --> log_analytics
    alert_manager --> notification_channels

Application Performance Monitoring (APM)

Azure Application Insights Configuration

Core Metrics

  • Response Time: 95th percentile under 2 seconds
  • Error Rate: Less than 0.1% for critical operations
  • Availability: 99.9% uptime SLA
  • Throughput: Requests per minute/hour tracking
  • Dependency Performance: External API response times

Custom Telemetry

// Example telemetry tracking
public class TelemetryService
{
    private readonly TelemetryClient _telemetryClient;

    public void TrackServiceRequest(string serviceName, TimeSpan duration, bool success)
    {
        var telemetry = new EventTelemetry("ServiceRequest");
        telemetry.Properties["ServiceName"] = serviceName;
        telemetry.Metrics["Duration"] = duration.TotalMilliseconds;
        telemetry.Metrics["Success"] = success ? 1 : 0;
        _telemetryClient.TrackEvent(telemetry);
    }
}

Performance Counters

  • CPU Usage: Application and system level
  • Memory Consumption: Heap usage and GC statistics
  • Thread Pool: Active threads and queue length
  • Database Connections: Connection pool utilization

Synthetic Monitoring

  • Health Check Endpoints: Automated health verification
  • User Journey Testing: Critical path validation
  • API Availability: External integration monitoring
  • Geographic Testing: Multi-region availability checks

Infrastructure Monitoring

Azure Monitor Integration

Virtual Machine Metrics

  • CPU Utilization: Target < 80% average
  • Memory Usage: Target < 85% utilization
  • Disk Performance: IOPS and latency monitoring
  • Network Throughput: Bandwidth utilization

Azure SQL Database Monitoring

-- Example monitoring query
SELECT 
    database_name,
    avg_cpu_percent,
    avg_data_io_percent,
    avg_log_write_percent,
    max_worker_percent,
    max_session_percent
FROM sys.dm_db_resource_stats
WHERE end_time > DATEADD(hour, -1, GETDATE())
ORDER BY end_time DESC;

Service Bus Monitoring

  • Queue Length: Message backlog tracking
  • Dead Letter Queue: Failed message monitoring
  • Throughput: Messages per second
  • Connection Status: Service health verification

Container Monitoring (if applicable)

  • Container Health: Pod/container status
  • Resource Utilization: CPU/memory per container
  • Scaling Events: Auto-scaling trigger monitoring
  • Image Vulnerabilities: Security scanning results

Business Metrics Monitoring

Key Performance Indicators (KPIs)

Service Level Metrics

  • Average Call Resolution Time: Target < 4 hours
  • First Call Resolution Rate: Target > 85%
  • Customer Satisfaction Score: Target > 4.0/5.0
  • Technician Utilization Rate: Target 75-85%

Business Process Metrics

  • Service Request Volume: Hourly/daily trends
  • Revenue per Service Call: Profitability tracking
  • Equipment Downtime: Impact measurement
  • Geographic Performance: Regional analysis

Custom Business Dashboards

{
  "dashboard_config": {
    "refresh_interval": "5_minutes",
    "widgets": [
      {
        "type": "metric",
        "title": "Active Service Requests",
        "query": "ServiceRequests | where Status in ('Open', 'Assigned', 'InProgress')",
        "threshold": {"warning": 50, "critical": 100}
      },
      {
        "type": "chart",
        "title": "Response Time Trend",
        "query": "ServiceRequests | summarize avg(ResponseTime) by bin(Timestamp, 1h)",
        "chart_type": "line"
      }
    ]
  }
}

Service Level Agreement (SLA) Monitoring

  • Availability SLA: 99.9% uptime tracking
  • Performance SLA: Response time compliance
  • Recovery Time Objective (RTO): Target < 4 hours
  • Recovery Point Objective (RPO): Target < 15 minutes

Alerting

Comprehensive alerting strategy with multi-level severity classification, escalation procedures, and notification channels.

Key Components: - Multi-tier severity levels (P1-P4) with defined response times - Automatic escalation procedures and on-call management - Multiple notification channels (Teams, SMS, Email, Mobile) - Integration with external systems (PagerDuty, ServiceNow) - Alert fatigue prevention and quality metrics

🚨 View Detailed Alerting Documentation

Dashboard Strategy

Executive Dashboard

  • Business KPIs: High-level business metrics
  • SLA Compliance: Service level tracking
  • Revenue Metrics: Financial performance
  • Customer Satisfaction: Satisfaction trends

Operations Dashboard

  • System Health: Infrastructure status
  • Active Incidents: Current issue tracking
  • Performance Metrics: Real-time system performance
  • Capacity Utilization: Resource usage trends

Technical Dashboard

  • Application Performance: Detailed APM metrics
  • Error Analysis: Error trends and analysis
  • Database Performance: SQL performance metrics
  • Integration Status: External system health

Business Process Dashboard

  • Service Request Flow: Request lifecycle tracking
  • Technician Performance: Individual and team metrics
  • Geographic Analysis: Regional performance data
  • Equipment Status: Asset health monitoring

Incident Response

Incident Classification

  1. Severity 1: Complete system outage
  2. Severity 2: Major functionality impaired
  3. Severity 3: Minor functionality affected
  4. Severity 4: Cosmetic or documentation issues

Response Procedures

  1. Detection: Automated alert or manual report
  2. Assessment: Severity determination and impact analysis
  3. Response: Team mobilization and initial response
  4. Resolution: Issue remediation and verification
  5. Post-Incident: Review and improvement identification

Communication Protocol

  • Internal: Teams channels and email updates
  • External: Customer notifications via status page
  • Stakeholder: Executive summary for major incidents
  • Post-Mortem: Detailed incident analysis and lessons learned

Monitoring Best Practices

Data Collection

  • Sampling Strategy: Balance detail with performance impact
  • Retention Policies: Cost-effective data lifecycle management
  • Data Quality: Ensure accurate and reliable metrics
  • Privacy Compliance: Protect sensitive data in monitoring

Alert Management

  • Alert Fatigue Prevention: Proper threshold tuning
  • Actionable Alerts: Ensure all alerts require action
  • Context Enrichment: Provide relevant troubleshooting information
  • Regular Review: Periodic alert effectiveness assessment

Performance Optimization

  • Query Optimization: Efficient log queries and aggregations
  • Resource Management: Monitor monitoring system resource usage
  • Automation: Automated response for common issues
  • Continuous Improvement: Regular monitoring strategy updates

Document Version: 1.0
Last Updated: January 2026
Next Review: April 2026