Table of Contents

Monitoring Architecture

Overview

Comprehensive monitoring and observability architecture for enterprise infrastructure and applications.

Monitoring Stack Architecture

Data Collection Layer

graph TB
    subgraph "Infrastructure Sources"
        Servers[Physical Servers]
        VMs[Virtual Machines]
        Containers[Container Platforms]
        Network[Network Devices]
        Storage[Storage Systems]
    end
    
    subgraph "Application Sources"
        WebApps[Web Applications]
        APIs[API Services]
        Databases[Database Systems]
        Microservices[Microservices]
        CustomApps[Custom Applications]
    end
    
    subgraph "Collection Agents"
        NodeExporter[Node Exporter]
        ContainerAdvisor[cAdvisor]
        SNMPExporter[SNMP Exporter]
        AppMetrics[Application Metrics]
        LogAgents[Log Agents]
    end
    
    Servers --> NodeExporter
    VMs --> NodeExporter
    Containers --> ContainerAdvisor
    Network --> SNMPExporter
    WebApps --> AppMetrics
    APIs --> AppMetrics
    Databases --> LogAgents

Processing and Storage

graph TB
    subgraph "Metric Processing"
        Prometheus[Prometheus]
        InfluxDB[InfluxDB]
        VictoriaMetrics[VictoriaMetrics]
    end
    
    subgraph "Log Processing"
        Logstash[Logstash]
        Fluentd[Fluentd]
        Vector[Vector]
    end
    
    subgraph "Storage Systems"
        TSDB[Time Series Database]
        Elasticsearch[Elasticsearch]
        S3[Object Storage]
    end
    
    subgraph "Stream Processing"
        Kafka[Apache Kafka]
        StreamProcessor[Stream Processor]
    end
    
    Prometheus --> TSDB
    InfluxDB --> TSDB
    Logstash --> Elasticsearch
    Fluentd --> Elasticsearch
    Kafka --> StreamProcessor
    StreamProcessor --> TSDB

Visualization and Alerting

graph TB
    subgraph "Visualization"
        Grafana[Grafana Dashboards]
        Kibana[Kibana]
        CustomUI[Custom Dashboards]
    end
    
    subgraph "Alerting Systems"
        AlertManager[Alert Manager]
        PagerDuty[PagerDuty]
        Slack[Slack Integration]
        Email[Email Notifications]
    end
    
    subgraph "Analysis Tools"
        ML[Machine Learning]
        Anomaly[Anomaly Detection]
        Correlation[Event Correlation]
    end
    
    Grafana --> AlertManager
    Kibana --> AlertManager
    AlertManager --> PagerDuty
    AlertManager --> Slack
    AlertManager --> Email
    ML --> Anomaly
    Anomaly --> Correlation

Monitoring Components

Infrastructure Monitoring

Server and VM Monitoring

# Prometheus Configuration
global:
  scrape_interval: 15s
  evaluation_interval: 15s

rule_files:
  - "infrastructure_rules.yml"
  - "application_rules.yml"

scrape_configs:
  - job_name: 'node-exporter'
    static_configs:
      - targets: ['server1:9100', 'server2:9100']
    
  - job_name: 'windows-exporter'
    static_configs:
      - targets: ['winserver1:9182', 'winserver2:9182']

Network Monitoring

  • SNMP monitoring for switches and routers
  • Flow-based monitoring (NetFlow, sFlow)
  • Network latency and bandwidth tracking
  • Security event correlation

Storage Monitoring

  • Disk usage and performance metrics
  • RAID status monitoring
  • Backup job monitoring
  • Storage array health checks

Application Performance Monitoring

Distributed Tracing

sequenceDiagram
    participant Client
    participant WebApp
    participant API
    participant Database
    participant Cache
    
    Client->>WebApp: HTTP Request
    Note over WebApp: Trace ID: abc123
    WebApp->>API: Service Call
    Note over API: Span: api-call
    API->>Database: Query
    Note over Database: Span: db-query
    API->>Cache: Cache Check
    Note over Cache: Span: cache-lookup
    Cache-->>API: Cache Miss
    Database-->>API: Query Result
    API-->>WebApp: Response
    WebApp-->>Client: HTTP Response

Application Metrics

  • Response time monitoring
  • Error rate tracking
  • Throughput measurements
  • Resource utilization

Log Management

Centralized Logging

graph LR
    subgraph "Log Sources"
        AppLogs[Application Logs]
        SysLogs[System Logs]
        SecurityLogs[Security Logs]
        WebLogs[Web Server Logs]
    end
    
    subgraph "Log Processing"
        Collector[Log Collector]
        Parser[Log Parser]
        Enricher[Log Enricher]
        Forwarder[Log Forwarder]
    end
    
    subgraph "Storage & Analysis"
        LogStore[Log Storage]
        SearchEngine[Search Engine]
        Analytics[Log Analytics]
    end
    
    AppLogs --> Collector
    SysLogs --> Collector
    SecurityLogs --> Collector
    WebLogs --> Collector
    Collector --> Parser
    Parser --> Enricher
    Enricher --> Forwarder
    Forwarder --> LogStore
    LogStore --> SearchEngine
    SearchEngine --> Analytics

Log Analysis Patterns

  • Structured logging implementation
  • Log correlation and aggregation
  • Security event detection
  • Performance issue identification

Alerting Strategy

Alert Classification

  1. Critical Alerts

    • Service outages
    • Security breaches
    • Data loss events
    • Infrastructure failures

  2. Warning Alerts

    • Performance degradation
    • Resource thresholds
    • Capacity planning
    • Maintenance reminders

  3. Informational Alerts

    • Deployment notifications
    • Backup completions
    • Scheduled maintenance
    • System updates

Alert Routing

graph TB
    subgraph "Alert Sources"
        InfraAlerts[Infrastructure Alerts]
        AppAlerts[Application Alerts]
        SecurityAlerts[Security Alerts]
        CustomAlerts[Custom Alerts]
    end
    
    subgraph "Alert Manager"
        Grouping[Alert Grouping]
        Routing[Alert Routing]
        Suppression[Alert Suppression]
        Escalation[Alert Escalation]
    end
    
    subgraph "Notification Channels"
        OnCall[On-Call Engineer]
        Teams[Team Channels]
        Management[Management Reports]
        TicketSystem[Ticket System]
    end
    
    InfraAlerts --> Grouping
    AppAlerts --> Grouping
    SecurityAlerts --> Routing
    CustomAlerts --> Suppression
    Grouping --> OnCall
    Routing --> Teams
    Suppression --> Management
    Escalation --> TicketSystem

Dashboard Design

Executive Dashboards

  • Overall system health
  • Service level indicators
  • Business impact metrics
  • Cost and capacity trends

Operational Dashboards

  • Real-time system status
  • Performance metrics
  • Error tracking
  • Resource utilization

Troubleshooting Dashboards

  • Detailed diagnostic information
  • Historical trend analysis
  • Correlation views
  • Root cause analysis tools

Best Practices

Monitoring Strategy

  1. Define Clear Objectives

    • Service level objectives (SLOs)
    • Key performance indicators (KPIs)
    • Business impact metrics
    • User experience measures

  2. Implement Effective Alerting

    • Avoid alert fatigue
    • Context-rich notifications
    • Proper escalation procedures
    • Regular alert review

Data Management

  1. Retention Policies

    • Hot data (recent, high resolution)
    • Warm data (medium term, reduced resolution)
    • Cold data (long term, archived)
    • Compliance requirements

  2. Performance Optimization

    • Efficient data collection
    • Proper indexing strategies
    • Query optimization
    • Resource scaling

Security Considerations

Monitoring Security

  • Secure communication channels
  • Authentication and authorization
  • Data encryption at rest and in transit
  • Access control and audit trails

Security Monitoring

  • Threat detection and response
  • Compliance monitoring
  • Security event correlation
  • Incident response integration
Edit this page