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maintainx-observability Implement comprehensive observability for MaintainX integrations.
Use when setting up monitoring, logging, tracing, and alerting
for MaintainX API integrations.
Trigger with phrases like "maintainx monitoring", "maintainx logging",
"maintainx metrics", "maintainx observability", "maintainx alerts".
الانتقال إلى التثبيت سوق المهارات اكتشف واستكشف مهارات الذكاء الاصطناعي التي بناها المجتمع.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
نسخ Promptعرض تفاصيل Prompt يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill maintainx-observabilityيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
تحميل Zip جاري التحميل... المهن ذات الصلة SOC
استنادا إلى تصنيف SOC المهني
المزيد من هذا المستودع Implement user sign-up and sign-in flows with Clerk.
Use when building authentication UI, customizing sign-in experience,
or implementing OAuth social login.
Trigger with phrases like "clerk sign-in", "clerk sign-up",
"clerk login flow", "clerk OAuth", "clerk social login".
Implement session management and middleware with Clerk.
Use when managing user sessions, configuring route protection,
or implementing token refresh and custom JWT templates.
Trigger with phrases like "clerk session", "clerk middleware",
"clerk route protection", "clerk token", "clerk JWT".
Configure enterprise SSO, role-based access control, and organization management.
Use when implementing SSO integration, configuring role-based permissions,
or setting up organization-level controls.
Trigger with phrases like "clerk SSO", "clerk RBAC",
"clerk enterprise", "clerk roles", "clerk permissions", "clerk organizations".
name maintainx-observability description Implement comprehensive observability for MaintainX integrations.
Use when setting up monitoring, logging, tracing, and alerting
for MaintainX API integrations.
Trigger with phrases like "maintainx monitoring", "maintainx logging",
"maintainx metrics", "maintainx observability", "maintainx alerts".
allowed-tools Read, Write, Edit, Bash(npm:*) version 1.11.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> tags ["saas","maintainx","api","monitoring","observability"] compatibility Designed for Claude Code, also compatible with Codex and OpenClaw
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
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 ],
: [register],
}),
: ({
: ,
: ,
: [register],
}),
: ({
: ,
: ,
: [ , ],
: [register],
}),
: ({
: ,
: ,
: [register],
}),
};
{ register };
registers
rateLimitHits
new
Counter
name
'maintainx_rate_limit_hits_total'
help
'Times rate limited by MaintainX API'
registers
workOrdersProcessed
new
Counter
name
'maintainx_work_orders_processed_total'
help
'Work orders processed'
labelNames
'action'
'status'
registers
syncLag
new
Gauge
name
'maintainx_sync_lag_seconds'
help
'Seconds since last successful sync'
registers
export
Step 2: Instrumented API Client
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
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,
};
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' );
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
import express from 'express' ;
import { register, metrics } from './metrics' ;
const app = express ();
app.get ('/metrics' , async (req, res) => {
res.set ('Content-Type' , register.contentType );
res.end (await register.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)
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
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.' });
dogstatsd.increment ('api.requests' , 1 , { endpoint : '/workorders' , status : '200' });
dogstatsd.histogram ('api.latency' , 0.45 , { endpoint : '/workorders' });