How to view real-time logs in Replit

Replit has three distinct places where output appears, and each shows different information. The Console tab shows output from the Run button — it displays structured entries with stdout, stderr, execution duration, and status metadata. The Shell tab is an interactive terminal for running commands manually — its output is separate from the Console. The deployment Logs tab (in the Deployments pane) shows output from your production application. Client-side JavaScript logs (from console.log in browser code) do NOT appear in any of these — they only show in the Preview pane's browser DevTools (right-click Preview, Inspect, Console tab).

Press the Run button to start your application. All server-side output — print() in Python, console.log() in Node.js — appears in the Console tab. The Console shows each entry with the command that was run, the output text, and whether it went to stdout or stderr. If your app crashes, the error traceback or stack trace appears here. You can scroll through the Console to see historical output from the current session. Output clears when you stop and restart the app.

1# Python — server-side logging visible in Console:
2print("Server started on port 3000")
3print(f"Received request: {request.path}")
4
5# Node.js — server-side logging visible in Console:
6console.log('Server started on port 3000');
7console.log(`Received request: ${req.path}`);
8console.error('Database connection failed');  // Shows as stderr

Plain print() and console.log() work for quick debugging but become hard to read in production. Add structured logging with timestamps, severity levels, and context information. For Python, use the built-in logging module. For Node.js, use winston or pino. Structured logs make it much easier to filter for errors, trace request flows, and diagnose timing issues in the deployment Logs tab.

1# Python — structured logging:
2import logging
3
4logging.basicConfig(
5    level=logging.INFO,
6    format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
7    datefmt='%Y-%m-%d %H:%M:%S'
8)
9logger = logging.getLogger('myapp')
10
11logger.info('Server started on port 3000')
12logger.warning('Slow response: 2.5 seconds')
13logger.error('Database query failed: connection timeout')
14
15# Output:
16# 2026-03-27 10:30:00 [INFO] myapp: Server started on port 3000
17# 2026-03-27 10:30:05 [WARNING] myapp: Slow response: 2.5 seconds
18# 2026-03-27 10:31:00 [ERROR] myapp: Database query failed: connection timeout

For web applications, log every incoming request with the method, path, status code, and response time. This creates an audit trail that helps you understand traffic patterns and identify slow endpoints. For Flask apps, use the after_request decorator. For Express apps, use middleware. These logs appear in both the Console during development and the deployment Logs tab in production.

1# Python Flask — request logging:
2import time
3import logging
4from flask import Flask, request, g
5
6app = Flask(__name__)
7logger = logging.getLogger('myapp')
8
9@app.before_request
10def start_timer():
11    g.start_time = time.time()
12
13@app.after_request
14def log_request(response):
15    duration = (time.time() - g.start_time) * 1000
16    logger.info(
17        f"{request.method} {request.path} → {response.status_code} "
18        f"({duration:.0f}ms)"
19    )
20    return response
21
22# Output:
23# 2026-03-27 10:30:00 [INFO] myapp: GET /api/users → 200 (45ms)
24# 2026-03-27 10:30:01 [INFO] myapp: POST /api/login → 401 (120ms)

After deploying your application (Autoscale, Reserved VM, or Scheduled), open the Deployments pane and click the Logs tab. This shows real-time output from your production application including all print(), console.log(), and logging output. Use the Logs tab to verify your app started correctly, monitor for errors, and track request patterns. Logs stream in real time — new entries appear automatically as they are generated. If no logs appear, your app may have crashed during startup; check for missing Secrets or port binding issues.

The deployment Logs tab does not send notifications when errors occur. To get alerted about production issues, add error reporting to your logging setup. The simplest approach is to send a webhook to Slack or Discord when a critical error occurs. Wrap your main request handler in a try/except that catches unhandled exceptions and sends an alert before returning an error response. Store the webhook URL in Tools → Secrets.

1import os
2import json
3import logging
4import urllib.request
5
6logger = logging.getLogger('myapp')
7
8def send_alert(message):
9    """Send error alert to Slack webhook."""
10    webhook_url = os.getenv('SLACK_WEBHOOK_URL')
11    if not webhook_url:
12        return
13    try:
14        payload = json.dumps({'text': f':rotating_light: {message}'}).encode()
15        req = urllib.request.Request(
16            webhook_url,
17            data=payload,
18            headers={'Content-Type': 'application/json'}
19        )
20        urllib.request.urlopen(req)
21    except Exception as e:
22        logger.error(f'Failed to send alert: {e}')
23
24# Use in error handling:
25try:
26    result = process_request(data)
27except Exception as e:
28    logger.exception('Unhandled error in process_request')
29    send_alert(f'Production error: {e}')
30    return {'error': 'Internal server error'}, 500