Agent Skills: MaintainX Observability

MaintainX Observability

Overview

Implement metrics, structured logging, and alerting for MaintainX integrations to ensure reliability and rapid issue detection.

Prerequisites

• MaintainX integration deployed
• Node.js 18+
• Monitoring platform (Prometheus/Grafana, Datadog, or CloudWatch)

Instructions

Step 1: Prometheus Metrics

// src/observability/metrics.ts
import { Counter, Histogram, Gauge, Registry } from 'prom-client';

const register = new Registry();

export const metrics = {
  apiRequests: new Counter({
    name: 'maintainx_api_requests_total',
    help: 'Total MaintainX API requests',
    labelNames: ['method', 'endpoint', 'status'],
    registers: [register],
  }),

  apiLatency: new Histogram({
    name: 'maintainx_api_latency_seconds',
    help: 'MaintainX API request latency',
    labelNames: ['method', 'endpoint'],
    buckets: [0.1, 0.25, 0.5, 1, 2.5, 5, 10],
    registers: [register],
  }),

  rateLimitHits: new Counter({
    name: 'maintainx_rate_limit_hits_total',
    help: 'Times rate limited by MaintainX API',
    registers: [register],
  }),

  workOrdersProcessed: new Counter({
    name: 'maintainx_work_orders_processed_total',
    help: 'Work orders processed',
    labelNames: ['action', 'status'],
    registers: [register],
  }),

  syncLag: new Gauge({
    name: 'maintainx_sync_lag_seconds',
    help: 'Seconds since last successful sync',
    registers: [register],
  }),
};

export { register };

Step 2: Instrumented API Client

// src/observability/instrumented-client.ts
import axios, { AxiosInstance } from 'axios';
import { metrics } from './metrics';

export function createInstrumentedClient(apiKey: string): AxiosInstance {
  const client = axios.create({
    baseURL: 'https://api.getmaintainx.com/v1',
    headers: { Authorization: `Bearer ${apiKey}`, 'Content-Type': 'application/json' },
    timeout: 30_000,
  });

  client.interceptors.request.use((config) => {
    (config as any).__startTime = process.hrtime.bigint();
    return config;
  });

  client.interceptors.response.use(
    (response) => {
      const elapsed = Number(process.hrtime.bigint() - (response.config as any).__startTime) / 1e9;
      const endpoint = response.config.url?.split('?')[0] || 'unknown';

      metrics.apiRequests.inc({
        method: response.config.method?.toUpperCase() || 'GET',
        endpoint,
        status: String(response.status),
      });
      metrics.apiLatency.observe(
        { method: response.config.method?.toUpperCase() || 'GET', endpoint },
        elapsed,
      );
      return response;
    },
    (error) => {
      const status = error.response?.status || 0;
      const endpoint = error.config?.url?.split('?')[0] || 'unknown';

      metrics.apiRequests.inc({
        method: error.config?.method?.toUpperCase() || 'GET',
        endpoint,
        status: String(status),
      });

      if (status === 429) {
        metrics.rateLimitHits.inc();
      }
      throw error;
    },
  );

  return client;
}

Step 3: Structured Logging

// src/observability/logger.ts

type LogLevel = 'debug' | 'info' | 'warn' | 'error';

interface LogEntry {
  level: LogLevel;
  message: string;
  service: string;
  timestamp: string;
  [key: string]: any;
}

class StructuredLogger {
  private service: string;

  constructor(service: string) {
    this.service = service;
  }

  private log(level: LogLevel, message: string, data?: Record<string, any>) {
    const entry: LogEntry = {
      level,
      message,
      service: this.service,
      timestamp: new Date().toISOString(),
      ...data,
    };
    // JSON output for log aggregation (ELK, CloudWatch, Datadog)
    console.log(JSON.stringify(entry));
  }

  info(message: string, data?: Record<string, any>) { this.log('info', message, data); }
  warn(message: string, data?: Record<string, any>) { this.log('warn', message, data); }
  error(message: string, data?: Record<string, any>) { this.log('error', message, data); }
  debug(message: string, data?: Record<string, any>) { this.log('debug', message, data); }
}

export const logger = new StructuredLogger('maintainx-integration');

// Usage
logger.info('Work order created', { workOrderId: 12345, priority: 'HIGH' });
logger.error('API call failed', { endpoint: '/workorders', status: 500, retryCount: 2 });

Step 4: Health and Metrics Endpoints

// src/observability/server.ts
import express from 'express';
import { register, metrics } from './metrics';

const app = express();

// Prometheus scrape endpoint
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', register.contentType);
  res.end(await register.metrics());
});

// Health check with metrics
app.get('/health', async (req, res) => {
  const health = {
    status: 'healthy',
    uptime: process.uptime(),
    metrics: {
      totalRequests: await metrics.apiRequests.get(),
      rateLimitHits: await metrics.rateLimitHits.get(),
      syncLagSeconds: (await metrics.syncLag.get()).values[0]?.value || 0,
    },
  };
  res.json(health);
});

app.listen(9090, () => logger.info('Metrics server on :9090'));

Step 5: Alerting Rules (Prometheus)

# prometheus/alerts.yml
groups:
  - name: maintainx
    rules:
      - alert: MaintainXHighErrorRate
        expr: rate(maintainx_api_requests_total{status=~"5.."}[5m]) > 0.1
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "MaintainX API error rate > 10%"

      - alert: MaintainXHighLatency
        expr: histogram_quantile(0.95, rate(maintainx_api_latency_seconds_bucket[5m])) > 5
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "MaintainX API p95 latency > 5s"

      - alert: MaintainXRateLimited
        expr: rate(maintainx_rate_limit_hits_total[5m]) > 0
        for: 1m
        labels:
          severity: warning
        annotations:
          summary: "MaintainX API rate limiting detected"

      - alert: MaintainXSyncStale
        expr: maintainx_sync_lag_seconds > 900
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "MaintainX sync lag > 15 minutes"

Output

• Prometheus metrics (request count, latency histogram, rate limit counter, sync lag gauge)
• Instrumented axios client automatically recording metrics on every API call
• Structured JSON logging for all operations
• /metrics endpoint for Prometheus scraping
• Alerting rules for error rate, latency, rate limits, and sync staleness

Error Handling

| Issue | Cause | Solution | |-------|-------|----------| | Metrics endpoint 500 | prom-client not initialized | Ensure Registry is created before metrics | | Missing labels | Metric name mismatch | Check labelNames match inc()/observe() calls | | Log volume too high | Debug logging in production | Set LOG_LEVEL=info in production | | Stale sync alert | Sync job stopped | Check cron schedule, restart sync process |

Resources

• MaintainX API Reference
• prom-client -- Prometheus metrics for Node.js
• Prometheus Alerting Rules

Next Steps

For incident response, see maintainx-incident-runbook.

Examples

Datadog integration using DogStatsD:

import StatsD from 'hot-shots';

const dogstatsd = new StatsD({ prefix: 'maintainx.' });

// Record API call
dogstatsd.increment('api.requests', 1, { endpoint: '/workorders', status: '200' });
dogstatsd.histogram('api.latency', 0.45, { endpoint: '/workorders' });