# DBIS Core Banking System - Monitoring Guide

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

## Monitoring Architecture

```mermaid
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

```mermaid
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

```mermaid
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

```mermaid
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:

```json
{
  "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

```mermaid
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

```mermaid
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

```mermaid
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

```mermaid
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](./RECOMMENDATIONS.md).

---

## Related Documentation

- [Best Practices Guide](./BEST_PRACTICES.md)
- [Recommendations](./RECOMMENDATIONS.md)
- [Development Guide](./development.md)
- [Deployment Guide](./deployment.md)

