maintainx-observability
Adds metrics, structured logging, and alerting specifically for MaintainX API integrations.
Install
mkdir -p .claude/skills/maintainx-observability && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7946" && unzip -o skill.zip -d .claude/skills/maintainx-observability && rm skill.zipInstalls to .claude/skills/maintainx-observability
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Implement comprehensive observability for MaintainX integrations.Key capabilities
- →Record API request counts and status codes
- →Measure API latency using histograms
- →Track rate limit hits and synchronization lag
- →Expose metrics via a Prometheus scrape endpoint
- →Log operations as structured JSON entries
How it works
It uses an instrumented Axios client to intercept requests and responses, recording metrics and logging activity, while providing an Express server to expose these metrics for scraping.
Inputs & outputs
When to use maintainx-observability
- →Set up Prometheus metrics
- →Monitor API latency
- →Configure rate limit alerts
- →Log API activity
About this skill
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
/metricsendpoint 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' });
When not to use it
- →When the integration is a simple script without long-running processes
- →When the environment lacks a monitoring platform like Prometheus or Datadog
Prerequisites
Limitations
- →Metrics endpoint requires prom-client initialization
- →Debug logging can create excessive log volume in production
- →Sync lag alerts depend on the sync job schedule
How it compares
This method provides automated, standardized observability for every API call, rather than relying on manual, ad-hoc logging or console statements.
Compared to similar skills
maintainx-observability side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| maintainx-observability (this skill) | 0 | 27d | Review | Intermediate |
| sentry-install-auth | 0 | 27d | Review | Beginner |
| perplexity-observability | 1 | 27d | No flags | Intermediate |
| documenso-observability | 0 | 27d | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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