When Nagios doesn't fit your infrastructure monitoring needs, several robust alternatives exist that support both Linux and Windows environments while offering plugin extensibility. These solutions handle critical metrics like CPU, memory, swap, processes, and services while providing threshold-based alerting and external integration capabilities.

Zabbix stands out with its agent-based and agentless monitoring capabilities. Example agent configuration for CPU monitoring:

UserParameter=custom.cpu.load,cat /proc/loadavg | awk '{print $1}'
Trigger expression: {host:custom.cpu.load.last()} > 5

Prometheus excels at time-series monitoring with its powerful query language (PromQL):

- alert: HighMemoryUsage
  expr: (node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes) / node_memory_MemTotal_bytes > 0.9
  for: 10m
  labels:
    severity: critical

Datadog provides comprehensive monitoring with easy Windows/Linux agent deployment. Their API enables custom metric submission:

import requests
from datadog import initialize, statsd

options = {'api_key':'YOUR_API_KEY'}
initialize(**options)

statsd.gauge('custom.memory.usage', get_memory_usage(), tags=["os:linux"])

Netdata offers real-time monitoring with minimal footprint. Configuration for process monitoring:

[plugin:proc]
    comm = yes
    oomkill = yes
    interrupts = yes

Checkmk provides efficient agent-based checks with automatic service discovery. Sample check definition:

define command {
    command_name    check_mk-custom
    command_line    $USER1$/check_mk_agent $HOSTADDRESS$ | grep 'my_custom_metric'
}

Most solutions support webhook integrations for alert forwarding. Here's a Python webhook processor example:

from flask import Flask, request
import subprocess

app = Flask(__name__)

@app.route('/webhook', methods=['POST'])
def handle_alert():
    alert = request.json
    if alert['status'] == 'CRITICAL':
        subprocess.run(['/path/to/handler.sh', alert['host']])
    return '', 200

For single-host monitoring scenarios, solutions like Netdata or Telegraf+InfluxDB provide minimal overhead while maintaining extensibility through their plugin ecosystems.

While Nagios remains a popular monitoring solution, many administrators seek modern alternatives that offer better scalability, lower resource consumption, and more flexible integration capabilities. The ideal replacement should handle both Linux and Windows environments while supporting custom metrics collection and threshold-based alerting.

Zabbix stands out with its agent-based and agentless monitoring capabilities. Its distributed monitoring architecture makes it suitable for various deployment scenarios:

# Example Zabbix agent configuration for CPU monitoring
UserParameter=custom.cpu.load,cat /proc/loadavg | awk '{print $1}'
UserParameter=custom.memory.used,free -m | awk '/Mem:/ {print $3}'

Prometheus excels at time-series monitoring with its powerful query language (PromQL) and alert manager:

# Sample alert rule for memory threshold
ALERT HighMemoryUsage
  IF node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes * 100 < 10
  FOR 5m
  LABELS { severity = "critical" }
  ANNOTATIONS {
    summary = "Memory shortage on {{ $labels.instance }}",
    description = "Available memory is below 10% for 5 minutes"
  }

PRTG Network Monitor offers a comprehensive Windows-first approach with 200+ built-in sensors. Its REST API enables integration with custom applications:

// Sample PRTG API call to retrieve sensor data
GET /api/getobjectstatus.htm?id=1234&username=demo&password=demo

Datadog provides cloud-native monitoring with extensive third-party integrations. Its agent can be customized through Python checks:

# Datadog check example for custom metric collection
from datadog_checks.base import AgentCheck

class CustomCheck(AgentCheck):
    def check(self, instance):
        self.gauge('system.custom.metric', 42, tags=['environment:dev'])

Netdata offers real-time monitoring with negligible performance impact. Its plugin architecture supports custom collectors:

# Netdata python.d plugin example
update_every = 5
priority = 90000

def get_data():
    return {'dimension_name': {'value': 42}}

Monit works well for single-host monitoring with its simple configuration syntax:

check system $HOST
    if loadavg (1min) > 4 then alert
    if memory usage > 75% then alert

Most modern monitoring solutions support webhook integration for custom event processing. Here's a Python Flask example for handling Zabbix webhooks:

from flask import Flask, request
import json

app = Flask(__name__)

@app.route('/webhook', methods=['POST'])
def handle_alert():
    data = request.json
    if data['status'] == 'PROBLEM':
        # Custom event processing logic
        pass
    return 'OK'