dbis_core/docs/monitoring.md

DBIS Core Banking System - Monitoring Guide

This guide provides comprehensive monitoring strategies, architecture, and best practices for the DBIS Core Banking System.

Monitoring Architecture

graph TB
    subgraph "Application Layer"
        APP1[App Instance 1]
        APP2[App Instance 2]
        APPN[App Instance N]
    end
    
    subgraph "Monitoring Infrastructure"
        METRICS[Metrics Collector]
        LOGS[Log Aggregator]
        TRACES[Distributed Tracer]
        ALERTS[Alert Manager]
    end
    
    subgraph "Storage & Analysis"
        METRICS_DB[Metrics Database<br/>Prometheus/InfluxDB]
        LOG_DB[Log Storage<br/>ELK/Splunk]
        TRACE_DB[Trace Storage<br/>Jaeger/Zipkin]
    end
    
    subgraph "Visualization"
        DASHBOARDS[Dashboards<br/>Grafana/Kibana]
        ALERT_UI[Alert Dashboard]
    end
    
    APP1 --> METRICS
    APP2 --> METRICS
    APPN --> METRICS
    
    APP1 --> LOGS
    APP2 --> LOGS
    APPN --> LOGS
    
    APP1 --> TRACES
    APP2 --> TRACES
    APPN --> TRACES
    
    METRICS --> METRICS_DB
    LOGS --> LOG_DB
    TRACES --> TRACE_DB
    
    METRICS_DB --> DASHBOARDS
    LOG_DB --> DASHBOARDS
    TRACE_DB --> DASHBOARDS
    
    METRICS_DB --> ALERTS
    ALERTS --> ALERT_UI

Key Metrics to Monitor

Application Metrics

graph LR
    subgraph "Application Metrics"
        REQ[Request Rate]
        LAT[Latency]
        ERR[Error Rate]
        THR[Throughput]
    end
    
    subgraph "Business Metrics"
        PAY[Payment Volume]
        SET[Settlement Time]
        FX[FX Trade Volume]
        CBDC[CBDC Transactions]
    end
    
    subgraph "System Metrics"
        CPU[CPU Usage]
        MEM[Memory Usage]
        DISK[Disk I/O]
        NET[Network I/O]
    end

Critical Metrics

1. API Response Times

   • p50, p95, p99 latencies
   • Per-endpoint breakdown
   • SLA compliance tracking

2. Error Rates

   • Total error rate
   • Error rate by endpoint
   • Error rate by error type
   • 4xx vs 5xx errors

3. Request Throughput

   • Requests per second
   • Requests per minute
   • Peak load tracking

4. Business Metrics

   • Payment volume (count and value)
   • Settlement success rate
   • FX trade volume
   • CBDC transaction volume

Database Metrics

graph TD
    subgraph "Database Metrics"
        CONN[Connection Pool]
        QUERY[Query Performance]
        REPL[Replication Lag]
        SIZE[Database Size]
    end
    
    CONN --> HEALTH[Database Health]
    QUERY --> HEALTH
    REPL --> HEALTH
    SIZE --> HEALTH

Key Database Metrics

1. Connection Pool

   • Active connections
   • Idle connections
   • Connection wait time
   • Connection pool utilization

2. Query Performance

   • Slow query count
   • Average query time
   • Query throughput
   • Index usage

3. Replication

   • Replication lag
   • Replication status
   • Replica health

4. Database Size

   • Table sizes
   • Index sizes
   • Growth rate

Infrastructure Metrics

1. CPU Usage

   • Per instance
   • Per service
   • Peak usage

2. Memory Usage

   • Per instance
   • Memory leaks
   • Garbage collection metrics

3. Disk I/O

   • Read/write rates
   • Disk space usage
   • I/O wait time

4. Network I/O

   • Bandwidth usage
   • Network latency
   • Packet loss

Logging Strategy

Log Levels

graph TD
    FATAL[FATAL<br/>System Unusable]
    ERROR[ERROR<br/>Error Events]
    WARN[WARN<br/>Warning Events]
    INFO[INFO<br/>Informational]
    DEBUG[DEBUG<br/>Debug Information]
    TRACE[TRACE<br/>Detailed Tracing]
    
    FATAL --> ERROR
    ERROR --> WARN
    WARN --> INFO
    INFO --> DEBUG
    DEBUG --> TRACE

Structured Logging

All logs should be structured JSON format with the following fields:

{
  "timestamp": "2024-01-15T10:30:00Z",
  "level": "INFO",
  "service": "payment-service",
  "correlationId": "abc-123-def",
  "message": "Payment processed successfully",
  "metadata": {
    "paymentId": "pay_123",
    "amount": 1000.00,
    "currency": "USD",
    "sourceAccount": "acc_456",
    "destinationAccount": "acc_789"
  }
}

Log Categories

1. Application Logs

   • Business logic execution
   • Service interactions
   • State changes

2. Security Logs

   • Authentication attempts
   • Authorization failures
   • Security events

3. Audit Logs

   • Financial transactions
   • Data access
   • Configuration changes

4. Error Logs

   • Exceptions
   • Stack traces
   • Error context

Alerting Strategy

Alert Flow

sequenceDiagram
    participant Metric as Metric Source
    participant Collector as Metrics Collector
    participant Rule as Alert Rule
    participant Alert as Alert Manager
    participant Notify as Notification Channel
    
    Metric->>Collector: Metric Value
    Collector->>Rule: Evaluate Rule
    alt Threshold Exceeded
        Rule->>Alert: Trigger Alert
        Alert->>Notify: Send Notification
        Notify->>Notify: Email/SMS/PagerDuty
    end

Alert Severity Levels

1. Critical

   • System down
   • Data loss risk
   • Security breach
   • Immediate response required

2. High

   • Performance degradation
   • High error rate
   • Resource exhaustion
   • Response within 1 hour

3. Medium

   • Warning conditions
   • Degraded performance
   • Response within 4 hours

4. Low

   • Informational
   • Minor issues
   • Response within 24 hours

Key Alerts

Critical Alerts

1. System Availability

   • Service down
   • Database unavailable
   • HSM unavailable

2. Data Integrity

   • Ledger mismatch
   • Transaction failures
   • Data corruption

3. Security

   • Authentication failures
   • Unauthorized access
   • Security breaches

High Priority Alerts

1. Performance

   • Response time > SLA
   • High error rate
   • Resource exhaustion

2. Business Operations

   • Payment failures
   • Settlement delays
   • FX pricing errors

Dashboard Recommendations

Executive Dashboard

graph TD
    subgraph "Executive Dashboard"
        VOL[Transaction Volume]
        VAL[Transaction Value]
        SUCCESS[Success Rate]
        REVENUE[Revenue Metrics]
    end

Key Metrics:

• Total transaction volume (24h, 7d, 30d)
• Total transaction value
• Success rate
• Revenue by product

Operations Dashboard

graph TD
    subgraph "Operations Dashboard"
        HEALTH[System Health]
        PERFORMANCE[Performance Metrics]
        ERRORS[Error Tracking]
        CAPACITY[Capacity Metrics]
    end

Key Metrics:

• System health status
• API response times
• Error rates by service
• Resource utilization

Business Dashboard

graph TD
    subgraph "Business Dashboard"
        PAYMENTS[Payment Metrics]
        SETTLEMENTS[Settlement Metrics]
        FX[FX Metrics]
        CBDC[CBDC Metrics]
    end

Key Metrics:

• Payment volume and value
• Settlement success rate
• FX trade volume
• CBDC transaction metrics

Monitoring Tools

Recommended Stack

1. Metrics Collection

   • Prometheus (open source)
   • InfluxDB (time-series database)
   • Grafana (visualization)

2. Log Aggregation

   • ELK Stack (Elasticsearch, Logstash, Kibana)
   • Splunk (enterprise)
   • Loki (lightweight)

3. Distributed Tracing

   • Jaeger (open source)
   • Zipkin (open source)
   • OpenTelemetry (standard)

4. Alerting

   • Alertmanager (Prometheus)
   • PagerDuty (on-call)
   • Opsgenie (incident management)

Implementation Guide

Step 1: Instrumentation

1. Add metrics collection to services
2. Implement structured logging
3. Add distributed tracing
4. Configure health checks

Step 2: Infrastructure Setup

1. Deploy metrics collection service
2. Deploy log aggregation service
3. Deploy tracing infrastructure
4. Configure alerting system

Step 3: Dashboard Creation

1. Create executive dashboard
2. Create operations dashboard
3. Create business dashboard
4. Create custom dashboards as needed

Step 4: Alert Configuration

1. Define alert rules
2. Configure notification channels
3. Test alert delivery
4. Document runbooks

Best Practices

1. Correlation IDs

   • Include correlation ID in all logs
   • Trace requests across services
   • Enable request-level debugging

2. Sampling

   • Sample high-volume metrics
   • Use adaptive sampling for traces
   • Preserve all error traces

3. Retention

   • Define retention policies
   • Archive old data
   • Comply with regulatory requirements

4. Performance Impact

   • Minimize monitoring overhead
   • Use async logging
   • Batch metric updates

Recommendations

Priority: High

1. Comprehensive Monitoring

   • Implement all monitoring layers
   • Monitor business and technical metrics
   • Set up alerting for critical issues

2. Dashboard Standardization

   • Use consistent dashboard templates
   • Standardize metric naming
   • Enable dashboard sharing

3. Alert Tuning

   • Start with conservative thresholds
   • Tune based on actual behavior
   • Reduce false positives

4. Documentation

   • Document all dashboards
   • Document alert runbooks
   • Maintain monitoring playbook

For detailed recommendations, see RECOMMENDATIONS.md.

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Related Documentation

• Best Practices Guide
• Recommendations
• Development Guide
• Deployment Guide