Metrics - Complete API Reference

Monitor system health, track performance metrics, and analyze telemetry data.

Chat Commands

System Metrics

/metrics Show current metrics /metrics system CPU, memory, latency /metrics api API performance stats /metrics ws WebSocket health

Trading Metrics

/metrics trades Trade execution stats /metrics fills Fill rate metrics /metrics latency Order latency stats /metrics errors Error rates

Custom Metrics

/metrics track <name> <value> Track custom metric /metrics query <name> Query metric history /metrics alert <name> > 100 Set metric alert

Export & Reports

/metrics export csv Export to CSV /metrics report daily Generate daily report /metrics dashboard Open metrics dashboard

TypeScript API Reference

Create Metrics Service

import { createMetricsService } from 'clodds/metrics';

const metrics = createMetricsService({ // Collection collectInterval: 5000, // ms retention: '30d',

// Storage storage: 'sqlite', dbPath: './metrics.db',

// Export enablePrometheus: true, prometheusPort: 9090, });

// Start collection await metrics.start();

System Metrics

const system = await metrics.getSystemMetrics();

console.log('=== System Health ==='); console.log(CPU Usage: ${system.cpuUsage}%); console.log(Memory: ${system.memoryUsed}MB / ${system.memoryTotal}MB); console.log(Uptime: ${system.uptimeHours}h); console.log(Active connections: ${system.activeConnections}); console.log(Event loop lag: ${system.eventLoopLag}ms);

API Metrics

const api = await metrics.getApiMetrics();

console.log('=== API Performance ==='); console.log(Total requests: ${api.totalRequests}); console.log(Requests/sec: ${api.requestsPerSecond}); console.log(Avg latency: ${api.avgLatency}ms); console.log(P50 latency: ${api.p50Latency}ms); console.log(P95 latency: ${api.p95Latency}ms); console.log(P99 latency: ${api.p99Latency}ms); console.log(Error rate: ${api.errorRate}%);

console.log('\nBy Endpoint:'); for (const endpoint of api.byEndpoint) { console.log( ${endpoint.path}: ${endpoint.avgLatency}ms (${endpoint.calls} calls)); }

WebSocket Metrics

const ws = await metrics.getWebSocketMetrics();

console.log('=== WebSocket Health ==='); console.log(Active connections: ${ws.activeConnections}); console.log(Messages/sec: ${ws.messagesPerSecond}); console.log(Avg message size: ${ws.avgMessageSize} bytes); console.log(Reconnections: ${ws.reconnections}); console.log(Dropped messages: ${ws.droppedMessages});

console.log('\nBy Feed:'); for (const feed of ws.byFeed) { console.log( ${feed.name}: ${feed.messagesPerSecond}/s, ${feed.latency}ms lag); }

Trade Execution Metrics

const trades = await metrics.getTradeMetrics();

console.log('=== Trade Execution ==='); console.log(Total orders: ${trades.totalOrders}); console.log(Fill rate: ${trades.fillRate}%); console.log(Partial fills: ${trades.partialFillRate}%); console.log(Rejections: ${trades.rejectionRate}%); console.log(Avg fill time: ${trades.avgFillTime}ms); console.log(Avg slippage: ${trades.avgSlippage}%);

console.log('\nBy Platform:'); for (const platform of trades.byPlatform) { console.log( ${platform.name}:); console.log( Fill rate: ${platform.fillRate}%); console.log( Avg latency: ${platform.avgLatency}ms); }

Latency Breakdown

const latency = await metrics.getLatencyBreakdown();

console.log('=== Latency Breakdown ==='); console.log(Total order latency: ${latency.total}ms); console.log( Signal processing: ${latency.signalProcessing}ms); console.log( Order construction: ${latency.orderConstruction}ms); console.log( Network round-trip: ${latency.networkRoundTrip}ms); console.log( Exchange processing: ${latency.exchangeProcessing}ms); console.log( Confirmation: ${latency.confirmation}ms);

Error Metrics

const errors = await metrics.getErrorMetrics();

console.log('=== Error Rates ==='); console.log(Total errors: ${errors.totalErrors}); console.log(Error rate: ${errors.errorRate}%); console.log(Errors/hour: ${errors.errorsPerHour});

console.log('\nBy Type:'); for (const type of errors.byType) { console.log( ${type.name}: ${type.count} (${type.percentage}%)); }

console.log('\nBy Platform:'); for (const platform of errors.byPlatform) { console.log( ${platform.name}: ${platform.errorRate}%); }

Custom Metrics

// Track custom metric metrics.track('edge_detected', 1, { market: 'trump-2028', edgeSize: 0.05, });

// Increment counter metrics.increment('trades_executed');

// Set gauge metrics.gauge('active_positions', 5);

// Record timing const timer = metrics.startTimer('order_execution'); // ... execute order ... timer.end();

// Histogram metrics.histogram('slippage', 0.003, { platform: 'polymarket', });

Query Metrics

const query = await metrics.query({ metric: 'edge_detected', period: '7d', aggregation: 'sum', groupBy: 'market', });

console.log('Edge Detection by Market:'); for (const row of query.results) { console.log( ${row.market}: ${row.value} detections); }

Metric Alerts

// Set alert threshold metrics.setAlert({ metric: 'error_rate', condition: '>', threshold: 5, // > 5% error rate window: '5m', action: 'notify', });

metrics.setAlert({ metric: 'latency_p99', condition: '>', threshold: 1000, // > 1000ms window: '1m', action: 'escalate', });

// Alert handlers metrics.on('alert', (alert) => { console.log(🚨 Alert: ${alert.metric} ${alert.condition} ${alert.threshold}); console.log( Current value: ${alert.currentValue}); });

Export Metrics

// Export to CSV await metrics.export({ format: 'csv', metrics: ['api_latency', 'trade_fill_rate', 'error_rate'], period: '30d', outputPath: './metrics-export.csv', });

// Export to Prometheus const prometheusFormat = metrics.toPrometheus();

// Export to JSON const jsonMetrics = await metrics.toJSON({ period: '24h', });

Generate Reports

const report = await metrics.generateReport({ type: 'daily', include: ['summary', 'api', 'trades', 'errors'], });

console.log('=== Daily Metrics Report ==='); console.log(Date: ${report.date}); console.log(\nSummary:); console.log( Uptime: ${report.summary.uptime}%); console.log( Total requests: ${report.summary.totalRequests}); console.log( Total trades: ${report.summary.totalTrades}); console.log( Error rate: ${report.summary.errorRate}%); console.log(\nHighlights:); for (const highlight of report.highlights) { console.log( - ${highlight}); }

Real-time Streaming

// Stream metrics in real-time const stream = metrics.stream(['cpu', 'memory', 'latency']);

stream.on('data', (data) => { console.log(CPU: ${data.cpu}%, Memory: ${data.memory}MB, Latency: ${data.latency}ms); });

// Stop streaming stream.stop();

Metric Types

Type Description Example

Counter Monotonic increasing trades_total

Gauge Point-in-time value active_positions

Histogram Distribution latency_ms

Timer Duration measurement order_execution_time

Built-in Metrics

Category Metrics

System cpu_usage, memory_used, uptime, connections

API request_count, latency_p50/p95/p99, error_rate

WebSocket messages_per_sec, lag, reconnections

Trades orders_total, fill_rate, slippage, execution_time

Errors error_count, error_rate_by_type

Best Practices

• Monitor latency percentiles — P99 matters more than average

• Set alerts proactively — Catch issues before users notice

• Track custom metrics — Business-specific KPIs

• Review daily reports — Spot trends early

• Export for analysis — Use external tools for deep dives