replit-observability
Sets up health endpoints, performance monitoring, and alerting for Replit-hosted services.
Install
mkdir -p .claude/skills/replit-observability && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7594" && unzip -o skill.zip -d .claude/skills/replit-observability && rm skill.zipInstalls to .claude/skills/replit-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.
Monitor Replit deployments with health checks, uptime tracking, resourceKey capabilities
- →Implement health endpoints with detailed metrics
- →Configure structured JSON logging
- →Set up external uptime monitoring
- →Detect cold starts in Autoscale deployments
- →Configure Slack alerting for memory and error rates
How it works
The skill provides patterns for exposing health metrics via an Express endpoint and integrating with external monitoring services to track uptime and performance. It also includes middleware for structured logging and cold start detection.
Inputs & outputs
When to use replit-observability
- →Implementing application health endpoints
- →Setting up uptime and availability alerts
- →Monitoring resource consumption
- →Building health dashboards for Replit apps
About this skill
Replit Observability
Overview
Monitor Replit deployment health, track cold starts, measure resource usage, and set up alerting. Covers Replit's built-in monitoring, external health checking, structured logging, and integration with monitoring services.
Prerequisites
- Replit app deployed (Autoscale or Reserved VM)
- Health endpoint implemented (
/health) - External monitoring service (UptimeRobot, Better Stack, or Prometheus)
Instructions
Step 1: Health Endpoint with Detailed Metrics
// src/routes/health.ts — comprehensive health check
import { Router } from 'express';
import { pool } from '../services/postgres';
const router = Router();
const startTime = Date.now();
router.get('/health', async (req, res) => {
const checks: Record<string, any> = {
status: 'ok',
uptime: process.uptime(),
bootTime: ((Date.now() - startTime) / 1000).toFixed(1) + 's ago',
timestamp: new Date().toISOString(),
repl: process.env.REPL_SLUG,
region: process.env.REPLIT_DEPLOYMENT_REGION,
env: process.env.NODE_ENV,
};
// Database check
if (process.env.DATABASE_URL) {
const dbStart = Date.now();
try {
await pool.query('SELECT 1');
checks.database = {
status: 'connected',
latencyMs: Date.now() - dbStart,
pool: { total: pool.totalCount, idle: pool.idleCount },
};
} catch (err: any) {
checks.database = { status: 'disconnected', error: err.message };
checks.status = 'degraded';
}
}
// Memory metrics
const mem = process.memoryUsage();
checks.memory = {
heapMB: Math.round(mem.heapUsed / 1024 / 1024),
totalMB: Math.round(mem.heapTotal / 1024 / 1024),
rssMB: Math.round(mem.rss / 1024 / 1024),
percent: ((mem.heapUsed / mem.heapTotal) * 100).toFixed(1),
};
// Node.js info
checks.runtime = {
node: process.version,
platform: process.platform,
pid: process.pid,
};
res.status(checks.status === 'ok' ? 200 : 503).json(checks);
});
// Lightweight ping for uptime monitors
router.get('/ping', (req, res) => res.send('pong'));
export default router;
Step 2: Structured Logging
// src/utils/logger.ts — structured JSON logging
const IS_PROD = process.env.NODE_ENV === 'production';
type LogLevel = 'debug' | 'info' | 'warn' | 'error';
function log(level: LogLevel, message: string, data?: Record<string, any>) {
if (level === 'debug' && IS_PROD) return;
const entry = {
timestamp: new Date().toISOString(),
level,
message,
repl: process.env.REPL_SLUG,
...data,
};
// JSON format for machine parsing, human-readable in dev
if (IS_PROD) {
consolelevel === 'error' ? 'error' : 'log');
} else {
consolelevel === 'error' ? 'error' : 'log'}] ${message}`,
data || ''
);
}
}
export const logger = {
debug: (msg: string, data?: any) => log('debug', msg, data),
info: (msg: string, data?: any) => log('info', msg, data),
warn: (msg: string, data?: any) => log('warn', msg, data),
error: (msg: string, data?: any) => log('error', msg, data),
};
// Request logging middleware
export function requestLogger(req: any, res: any, next: any) {
const start = Date.now();
res.on('finish', () => {
logger.info('request', {
method: req.method,
path: req.path,
status: res.statusCode,
durationMs: Date.now() - start,
userId: req.headers['x-replit-user-id'] || 'anonymous',
});
});
next();
}
Step 3: External Uptime Monitoring
Set up external monitors to detect Autoscale cold starts and outages:
UptimeRobot (free tier: 50 monitors):
1. Create new monitor: HTTP(s)
2. URL: https://your-app.replit.app/ping
3. Interval: 5 minutes
4. Alert contacts: email, Slack webhook
Better Stack / Datadog / Grafana Cloud:
- Same setup, more features
- Track response time trends
- Detect cold start patterns
- Set up PagerDuty integration
Key metrics to monitor externally:
- Uptime percentage (target: 99.9%)
- Response time P95 (target: < 2s)
- Cold start frequency (Autoscale only)
- SSL certificate expiry
Step 4: Cold Start Detection
// Track cold starts for Autoscale deployments
const COLD_START_THRESHOLD_MS = 5000;
let firstRequestTime: number | null = null;
app.use((req, res, next) => {
if (!firstRequestTime) {
firstRequestTime = Date.now();
const bootTime = process.uptime();
if (bootTime < 30) { // Just started
logger.info('cold_start_detected', {
bootTimeMs: Math.round(bootTime * 1000),
path: req.path,
});
}
}
next();
});
Step 5: Alerting Rules
// src/utils/alerts.ts — send alerts to Slack on issues
async function alertSlack(message: string, severity: 'info' | 'warning' | 'critical') {
const webhookUrl = process.env.SLACK_WEBHOOK_URL;
if (!webhookUrl) return;
const emoji = { info: 'information_source', warning: 'warning', critical: 'rotating_light' };
await fetch(webhookUrl, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
text: `:${emoji[severity]}: [${severity.toUpperCase()}] ${process.env.REPL_SLUG}\n${message}`,
}),
});
}
// Monitor memory usage
setInterval(async () => {
const mem = process.memoryUsage();
const heapPercent = (mem.heapUsed / mem.heapTotal) * 100;
if (heapPercent > 90) {
await alertSlack(`Memory critical: ${heapPercent.toFixed(1)}% heap used`, 'critical');
} else if (heapPercent > 75) {
await alertSlack(`Memory warning: ${heapPercent.toFixed(1)}% heap used`, 'warning');
}
}, 60000);
// Monitor error rate
let errorCount = 0;
let requestCount = 0;
app.use((req, res, next) => {
requestCount++;
res.on('finish', () => {
if (res.statusCode >= 500) errorCount++;
});
next();
});
setInterval(async () => {
if (requestCount > 0) {
const errorRate = (errorCount / requestCount) * 100;
if (errorRate > 5) {
await alertSlack(`Error rate: ${errorRate.toFixed(1)}% (${errorCount}/${requestCount})`, 'critical');
}
}
errorCount = 0;
requestCount = 0;
}, 300000); // Check every 5 minutes
Step 6: Replit Dashboard Monitoring
Built-in monitoring in Replit:
1. Deployment Settings > Logs: real-time stdout/stderr
2. Deployment Settings > History: deploy timeline + rollbacks
3. Database pane > Settings: storage usage + connection info
4. Billing > Usage: compute, egress, and storage costs
Check deployment logs:
- Click on active deployment
- View real-time log stream
- Filter by error/warning
- Logs persist across container restarts
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Cold starts undetected | No external monitor | Set up UptimeRobot or similar |
| Deployment logs missing | Container restarted | Use external log aggregator |
| Memory leak unnoticed | No memory monitoring | Add heap tracking + alerts |
| DB pool exhaustion | Too many connections | Monitor pool.totalCount in health |
Resources
Next Steps
For incident response, see replit-incident-runbook.
When not to use it
- →When monitoring non-Replit infrastructure
- →When lacking access to deployment settings
Prerequisites
Limitations
- →Deployment logs are missing if the container restarts
- →Cold starts may remain undetected without external monitoring
How it compares
Unlike manual logging, this approach standardizes health checks and integrates directly with Replit's deployment lifecycle for automated alerting.
Compared to similar skills
replit-observability side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| replit-observability (this skill) | 1 | 27d | Caution | Intermediate |
| distributed-tracing | 5 | 2mo | No flags | Intermediate |
| service-mesh-observability | 5 | 2mo | No flags | Advanced |
| observability-engineer | 12 | 4mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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