Monitoring and Observability¶
Comprehensive monitoring and observability strategy for the RCIIS DevOps platform.
Monitoring Stack¶
Core Components¶
- Prometheus: Metrics collection and storage
- Grafana: Visualization and dashboards
- AlertManager: Alert routing and notification
- Jaeger: Distributed tracing
- Elasticsearch: Log aggregation and search
Application Monitoring¶
- Application metrics: Custom business metrics
- Infrastructure metrics: System and container metrics
- Network metrics: Traffic and connectivity monitoring
- Security metrics: Threat detection and compliance
Key Metrics¶
Infrastructure Metrics¶
- Resource Utilization: CPU, memory, disk, network
- Cluster Health: Node status, pod health, service availability
- Storage Performance: IOPS, latency, capacity utilization
- Network Performance: Throughput, latency, packet loss
Application Metrics¶
- Request Metrics: Rate, latency, error rate (RED)
- Business Metrics: Transaction volume, processing time
- Database Metrics: Connection pools, query performance
- Message Queue Metrics: Queue depth, processing lag
Security Metrics¶
- Authentication Events: Login attempts, failures, anomalies
- Access Control: Permission changes, unauthorized access
- Network Security: Intrusion attempts, policy violations
- Compliance Metrics: Audit events, policy compliance
Alerting Strategy¶
Alert Categories¶
- Critical: Service outages, data loss, security incidents
- Warning: Performance degradation, capacity issues
- Info: Deployment events, configuration changes
Alert Routing¶
- On-call: Critical alerts to on-call engineer
- Team: Warning alerts to team channels
- Info: Information alerts to monitoring channels
Alert Fatigue Prevention¶
- Smart grouping: Related alerts bundled together
- Escalation policies: Progressive notification levels
- Alert tuning: Regular review and adjustment
- Runbook integration: Automated response procedures
Log Management¶
Log Sources¶
- Application logs: Service logs, error logs, access logs
- Infrastructure logs: System logs, container logs, audit logs
- Security logs: Authentication logs, security events
- Audit logs: Compliance and regulatory logs
Log Processing¶
- Collection: Centralized log aggregation
- Parsing: Structured log processing
- Enrichment: Context and metadata addition
- Retention: Policy-based log lifecycle
Log Analysis¶
- Real-time monitoring: Live log streaming and alerting
- Historical analysis: Trend analysis and reporting
- Anomaly detection: Pattern recognition and alerting
- Compliance reporting: Regulatory requirement reporting
Distributed Tracing¶
Trace Components¶
- Services: Microservice boundaries
- Operations: Business logic operations
- Dependencies: External service calls
- Performance: Latency and bottleneck identification
Trace Analysis¶
- Service maps: Dependency visualization
- Performance analysis: Latency breakdown
- Error tracking: Error propagation analysis
- Capacity planning: Performance trend analysis
Dashboard Strategy¶
Dashboard Types¶
- Executive dashboards: High-level business metrics
- Operational dashboards: System health and performance
- Troubleshooting dashboards: Detailed diagnostic views
- Security dashboards: Security posture and incidents
Dashboard Best Practices¶
- Clear visualization: Easy-to-understand charts and graphs
- Contextual information: Relevant metadata and annotations
- Drill-down capability: Progressive detail levels
- Real-time updates: Live data refresh
Capacity Planning¶
Resource Monitoring¶
- Current utilization: Real-time resource usage
- Growth trends: Historical usage patterns
- Seasonal patterns: Cyclical demand variations
- Forecast models: Predictive capacity planning
Scaling Decisions¶
- Horizontal scaling: Pod replica adjustments
- Vertical scaling: Resource limit adjustments
- Infrastructure scaling: Node and cluster scaling
- Service optimization: Performance tuning
Troubleshooting Workflows¶
Incident Response¶
- Detection: Automated alert triggers
- Assessment: Impact and severity evaluation
- Investigation: Root cause analysis
- Resolution: Issue remediation
- Post-mortem: Lessons learned documentation
Diagnostic Tools¶
- Metrics correlation: Multi-dimensional analysis
- Log correlation: Event timeline reconstruction
- Trace analysis: Request flow visualization
- Health checks: Service status verification
Performance Optimization¶
Performance Monitoring¶
- Response time tracking: Request latency monitoring
- Throughput measurement: Request rate monitoring
- Resource efficiency: Utilization optimization
- Bottleneck identification: Performance constraint analysis
Optimization Strategies¶
- Code optimization: Application performance tuning
- Resource tuning: CPU and memory optimization
- Caching strategies: Data and response caching
- Database optimization: Query and index optimization
Compliance Monitoring¶
Regulatory Requirements¶
- Data protection: GDPR compliance monitoring
- Financial regulations: SOX compliance tracking
- Security standards: ISO 27001 compliance
- Industry standards: Customs regulation compliance
Audit Trails¶
- Access logging: User and system access tracking
- Change management: Configuration change logging
- Data access: Sensitive data access monitoring
- Security events: Security incident tracking
Monitoring Best Practices¶
Data Quality¶
- Metric accuracy: Reliable and consistent data
- Temporal alignment: Synchronized timestamps
- Data completeness: Comprehensive coverage
- Data validation: Quality checks and verification
Tool Integration¶
- Unified interfaces: Single pane of glass
- Data correlation: Cross-tool data linking
- Workflow automation: Automated response procedures
- Knowledge sharing: Documentation and training
Continuous Improvement¶
- Regular reviews: Monitoring effectiveness assessment
- Tool evaluation: New technology adoption
- Process optimization: Workflow improvement
- Team training: Skills development and knowledge sharing
For implementation details, refer to the specific monitoring tool documentation.