# API Gateway Metrics - Deployment Guide

## Quick Start

### 1. Run the Monitoring Stack

```bash
cd monitoring
docker-compose up -d
```

This starts:
- **Prometheus** on `http://localhost:9099` (metrics collection)
- **Grafana** on `http://localhost:3000` (visualization)
- **AlertManager** on `http://localhost:9093` (alert routing)
- **PostgreSQL Exporter** on `http://localhost:9187`
- **Redis Exporter** on `http://localhost:9121`
- **Node Exporter** on `http://localhost:9100`

### 2. Access Grafana Dashboard

1. Open `http://localhost:3000`
2. Login: `admin` / `foxhunt2025`
3. Navigate to **Dashboards** → **API Gateway - Authentication & Performance**

### 3. Run Example to Generate Metrics

```bash
cd services/api_gateway
cargo run --example metrics_example
```

This will:
- Generate 100 successful auth events
- Record 4 auth failures
- Simulate 50 trading service requests
- Simulate 30 backtesting requests
- Update health status for all backends
- Expose metrics at `http://localhost:9090/metrics`

### 4. View Metrics in Prometheus

Open `http://localhost:9099/graph` and try these queries:

**Authentication Success Rate:**
```promql
100 * rate(api_gateway_auth_requests_success[1m]) / rate(api_gateway_auth_requests_total[1m])
```

**Auth Latency p99:**
```promql
histogram_quantile(0.99, rate(api_gateway_auth_total_duration_microseconds_bucket[1m]))
```

**Backend Request Rate by Service:**
```promql
rate(api_gateway_backend_requests_total[1m])
```

**Cache Hit Rate:**
```promql
100 * rate(api_gateway_jwt_cache_hits[1m]) / (rate(api_gateway_jwt_cache_hits[1m]) + rate(api_gateway_jwt_cache_misses[1m]))
```

## Production Integration

### API Gateway Service

```rust
use api_gateway::metrics::{GatewayMetrics, metrics_router};
use axum::Server;

#[tokio::main]
async fn main() -> Result<()> {
    // Initialize metrics
    let metrics = GatewayMetrics::new()?;

    // Start Prometheus exporter on separate port
    let metrics_addr = "0.0.0.0:9090".parse()?;
    let metrics_router = metrics_router(metrics.registry());

    tokio::spawn(async move {
        Server::bind(&metrics_addr)
            .serve(metrics_router.into_make_service())
            .await
            .expect("Metrics server failed");
    });

    // Create auth interceptor with metrics
    let auth_interceptor = AuthInterceptor::new(
        jwt_service,
        revocation_service,
        authz_service,
        rate_limiter,
        audit_logger,
    );

    // Instrument auth interceptor to record metrics
    let instrumented_auth = InstrumentedAuthInterceptor::new(
        auth_interceptor,
        metrics.auth.clone(),
    );

    // Create gRPC server with metrics
    let server = Server::builder()
        .layer(instrumented_auth)
        .add_service(trading_proxy)
        .add_service(backtesting_proxy)
        .add_service(ml_training_proxy)
        .serve(addr)
        .await?;

    Ok(())
}
```

### Docker Deployment

Add metrics port to `docker-compose.yml`:

```yaml
services:
  api-gateway:
    image: foxhunt/api-gateway:latest
    ports:
      - "50051:50051"  # gRPC
      - "9090:9090"    # Prometheus metrics
    environment:
      - GATEWAY_BIND_ADDR=0.0.0.0:50051
      - METRICS_BIND_ADDR=0.0.0.0:9090
      - JWT_SECRET_FILE=/run/secrets/jwt_secret
      - REDIS_URL=redis://redis:6379
    networks:
      - foxhunt-monitoring
```

Update Prometheus to scrape API Gateway:

```yaml
# monitoring/prometheus/prometheus.yml
scrape_configs:
  - job_name: 'api_gateway'
    static_configs:
      - targets: ['api-gateway:9090']
```

## Metrics Overview

### Key Metrics to Monitor

| Metric | Target | Alert Threshold | Description |
|--------|--------|-----------------|-------------|
| `api_gateway_auth_total_duration_microseconds` (p99) | <10μs | >10μs | Total auth latency SLA |
| `api_gateway_auth_requests_success` / `total` | >99% | <95% | Auth success rate |
| `api_gateway_circuit_breaker_state` | 0 (closed) | 2 (open) | Backend health |
| `api_gateway_health_status` | 1 (healthy) | 0 (unhealthy) | Service availability |
| `api_gateway_notify_listener_connected` | 1 | 0 | Config hot-reload |

### Performance Targets

**Authentication (HFT Requirements):**
- JWT extraction: <0.5μs
- JWT validation: <1μs
- Revocation check: <500ns
- RBAC check: <100ns
- Rate limit check: <50ns
- **Total auth: <10μs (p99)**

**Backend Proxy:**
- Trading Service: <50ms (p99)
- Backtesting Service: <500ms (p99)
- ML Training Service: <5000ms (p99)

**Configuration:**
- Config reload: <50ms (p95)
- Config fetch: <25ms (p95)

**Cache Performance:**
- JWT cache hit rate: >99%
- RBAC cache hit rate: >95%
- Config cache hit rate: >90%

## Alerting

### Critical Alerts

1. **AuthLatencySLAViolation**: p99 auth latency >10μs for 1m
2. **CircuitBreakerOpen**: Backend circuit breaker opened
3. **BackendServiceUnhealthy**: Health checks failing for 2m
4. **NotifyListenerDisconnected**: Hot-reload capability lost
5. **RedisConnectionFailure**: JWT revocation unavailable

### Warning Alerts

1. **HighAuthFailureRate**: Auth failure rate >10% for 2m
2. **HighBackendLatency**: Backend p99 >100ms for 3m
3. **ConnectionPoolExhaustion**: Pool utilization >90% for 5m
4. **LowCacheHitRate**: RBAC cache hit rate <90% for 5m
5. **ExcessiveRateLimiting**: Rate limit rejections >10/s for 5m

## Grafana Dashboard Panels

### Row 1: Authentication Overview
- **Auth Requests**: Total/Success/Failure rate
- **Auth Success Rate**: Percentage gauge with thresholds
- **Auth SLA Compliance**: <10μs target compliance

### Row 2: Layer Latency Breakdown
- **JWT Extraction p99**: Sub-microsecond target
- **JWT Validation p99**: <1μs target
- **Revocation Check p99**: <500ns target
- **RBAC Check p99**: <100ns target
- **Rate Limit Check p99**: <50ns target
- **Total Auth p99**: <10μs SLA

### Row 3: Error Analysis
- **Errors by Type**: Missing JWT, expired, revoked, etc.
- **Cache Performance**: JWT and RBAC cache hit rates

### Row 4: Backend Services
- **Request Latency**: p99 by service
- **Circuit Breaker States**: Open/closed status
- **Health Status**: Table view of service health
- **Connection Pool**: Utilization percentage

### Row 5: Configuration
- **Reload Events**: By type (auth, routing, rate_limit, backend)
- **Hot-Reload Latency**: p95 reload time
- **NOTIFY Listener**: Connection status indicator

### Row 6: Rate Limiting
- **Top 10 Rate-Limited Users**: Highest rejection rates
- **Active Entries**: Total users being tracked

## Troubleshooting

### Metrics Not Appearing in Prometheus

1. Check API Gateway metrics endpoint:
   ```bash
   curl http://localhost:9090/metrics | grep api_gateway
   ```

2. Verify Prometheus target:
   ```bash
   curl http://localhost:9099/api/v1/targets | jq '.data.activeTargets[] | select(.job=="api_gateway")'
   ```

3. Check Prometheus logs:
   ```bash
   docker logs foxhunt-prometheus
   ```

### Grafana Dashboard Not Loading

1. Verify Prometheus data source:
   - Grafana → Configuration → Data Sources
   - URL should be `http://prometheus:9090`

2. Import dashboard manually:
   - Grafana → Dashboards → Import
   - Upload `monitoring/grafana/api_gateway_dashboard.json`

### High Metrics Cardinality

If Prometheus memory usage is high:

```bash
# Check metric cardinality
curl http://localhost:9099/api/v1/label/__name__/values | jq '. | length'

# Identify high-cardinality metrics
curl 'http://localhost:9099/api/v1/query?query=count({__name__=~".+"}) by (__name__)' | jq '.data.result | sort_by(.value[1] | tonumber) | reverse | .[0:10]'
```

**Solutions:**
- Reduce `user_id` label cardinality in per-user metrics
- Use recording rules for aggregated metrics
- Decrease retention period in Prometheus config

### Alerts Not Firing

1. Verify alert rules syntax:
   ```bash
   docker exec foxhunt-prometheus promtool check rules /etc/prometheus/alerts/api_gateway_alerts.yml
   ```

2. Check active alerts:
   ```bash
   curl http://localhost:9099/api/v1/alerts | jq '.data.alerts'
   ```

3. Verify AlertManager:
   ```bash
   curl http://localhost:9093/api/v2/alerts | jq
   ```

## Performance Impact

### Metrics Overhead

- Counter increment: **~50ns**
- Histogram observation: **~200ns**
- Label lookup: **~10ns** (cached)

**Total overhead per authenticated request: <500ns (<0.005% of 10μs SLA)**

### Memory Usage

- Prometheus TSDB: ~50MB per million data points
- Grafana: ~200MB base + 10MB per dashboard
- API Gateway metrics: ~5MB per 100k requests

### Network Bandwidth

- Metrics scrape: ~50KB per scrape
- Scrape interval: 5s
- Bandwidth: ~10KB/s per target

## Production Checklist

- [ ] Prometheus deployed with persistent storage
- [ ] Grafana deployed with API Gateway dashboard
- [ ] AlertManager configured with notification channels
- [ ] PostgreSQL exporter connected to config database
- [ ] Redis exporter connected to revocation cache
- [ ] API Gateway metrics endpoint exposed on :9090
- [ ] Firewall rules allow Prometheus scraping
- [ ] HTTPS/TLS configured for Grafana
- [ ] Alert routing tested (Slack/PagerDuty)
- [ ] Metric retention policy configured (30 days default)
- [ ] Backup configured for Prometheus/Grafana data
- [ ] Monitoring stack monitored (meta-monitoring)

## Next Steps

1. **Configure Alerting**:
   - Update Slack webhook in `alertmanager.yml`
   - Configure PagerDuty for critical alerts
   - Test alert routing

2. **Customize Dashboard**:
   - Add panels for business metrics
   - Configure alerts for your SLAs
   - Set up user-specific views

3. **Integrate with CI/CD**:
   - Add metrics checks to deployment pipeline
   - Canary deployments based on error rates
   - Automated rollback on SLA violations

4. **Advanced Features**:
   - Recording rules for complex queries
   - Federation for multi-cluster setup
   - Long-term storage (Thanos/Cortex)

## Support

For issues or questions:
- Check logs: `docker logs foxhunt-prometheus`
- Review Grafana docs: https://grafana.com/docs/
- Prometheus docs: https://prometheus.io/docs/
- Internal docs: `services/api_gateway/src/metrics/README.md`