When working with Monit across multiple servers in academic or lab environments, the commercial M/Monit interface becomes prohibitively expensive. After evaluating various monitoring solutions like Nagios and Zabbix, I found they don't provide the lightweight simplicity of Monit's approach to process monitoring and recovery.

The Ruby-based monittr (GitHub: karmi/monittr) offers a basic web interface, but lacks some critical features:

# Sample monittr configuration
Monittr.configure do |config|
  config.monitrc = '/etc/monitrc'
  config.port = 3000
  config.auth = { username: 'admin', password: 'secret' }
end

Monit provides an HTTP interface that can be queried directly. Here's a Python script to aggregate status from multiple servers:

import requests
from xml.etree import ElementTree as ET

servers = [
    {'url': 'http://server1:2812', 'auth': ('admin', 'monit')},
    {'url': 'http://server2:2812', 'auth': ('admin', 'monit')}
]

def get_status(server):
    try:
        response = requests.get(f"{server['url']}/_status", auth=server['auth'])
        return ET.fromstring(response.text)
    except Exception as e:
        print(f"Error querying {server['url']}: {str(e)}")
        return None

for server in servers:
    status = get_status(server)
    if status is not None:
        print(f"Status from {server['url']}:")
        for service in status.findall('service'):
            print(f"  {service.find('name').text}: {service.find('status').text}")

The Django community is developing django-monit, which shows promise for multi-server management:

# settings.py configuration
MONIT_SERVERS = [
    {
        'NAME': 'Web Server',
        'URL': 'http://webserver:2812',
        'USERNAME': 'admin',
        'PASSWORD': 'monit'
    }
]

# views.py example
from django.shortcuts import render
from monit.collector import get_monit_status

def dashboard(request):
    statuses = []
    for server in settings.MONIT_SERVERS:
        statuses.append(get_monit_status(server))
    return render(request, 'monit/dashboard.html', {'statuses': statuses})

For those already using Prometheus, the monit_exporter bridges the gap:

# monit_exporter configuration
exporters:
  - name: "web_cluster"
    url: "http://web1:2812/_status"
    username: "admin"
    password: "monit"
    interval: "30s"

For quick visualization, integrate with existing tools:

# Grafana dashboard query example
SELECT
  $__timeEpoch(time),
  value
FROM
  monit_metrics
WHERE
  $__timeFilter(time) AND
  instance =~ /$server/ AND
  metric =~ /$service/
ORDER BY
  time

When implementing any solution, ensure proper security measures:

• Always use HTTPS for Monit's web interface
• Implement IP whitelisting for Monit ports
• Use strong, unique credentials for each server
• Consider SSH tunneling for remote access

When working with Monit in distributed environments, the lack of centralized visualization becomes apparent. The commercial M/Monit solution provides excellent dashboards, but for academic or small-scale deployments, we need FOSS alternatives that can:

• Aggregate status from multiple Monit instances
• Present unified health dashboards
• Maintain lightweight resource usage

From my recent evaluations, here are the most promising approaches:

# Example monittr configuration (Ruby)
Monittr.configure do |config|
  config.servers = [
    { host: 'server1.lab.edu', port: 2812 },
    { host: 'server2.lab.edu', port: 2812, ssl: true }
  ]
  config.interval = 60 # seconds
end

For complete control, we can build a simple aggregator using Monit's built-in HTTP interface:

import requests
from xml.etree import ElementTree

def get_monit_status(host, port=2812, auth=('admin', 'monit')):
    url = f"http://{host}:{port}/_status?format=xml"
    response = requests.get(url, auth=auth)
    return ElementTree.fromstring(response.content)

# Usage example:
server_status = get_monit_status('10.0.1.15')
cpu_usage = server_status.find('.//cpu/system').text

The Django community is developing django-monit-collector (currently in alpha). Key features include:

# settings.py configuration
MONIT_COLLECTOR_SETTINGS = {
    'SERVERS': [
        {'NAME': 'Web Server', 'HOST': 'web1', 'PORT': 2812},
        {'NAME': 'DB Server', 'HOST': 'db1', 'PORT': 2812}
    ],
    'POLL_INTERVAL': 300,
    'STORAGE_BACKEND': 'django_monit_collector.backends.sqlite'
}

For minimal overhead, consider this Node.js implementation:

const monit = require('node-monit');
const servers = [
  { host: '192.168.1.10', user: 'monit', pass: 'secret' },
  { host: '192.168.1.11', user: 'monit', pass: 'secret' }
];

async function checkAll() {
  const results = await Promise.all(
    servers.map(s => monit.getStatus(s))
  );
  return results.map(r => ({
    host: r.host,
    services: r.services.filter(s => s.status !== 'Running')
  }));
}

When rolling your own solution, account for:

• Authentication security (use HTTPS where possible)
• Data retention policies
• Alert threshold configuration
• Cross-platform service naming consistency