Build a Comprehensive Server Monitoring System with BlipHQ

In this tutorial, we'll walk you through building a comprehensive server monitoring system using BlipHQ. You'll learn how to track various server metrics and receive real-time alerts for critical events.

Step 1: Set Up BlipHQ

1. Sign up for a BlipHQ account at https://bliphq.com
2. Obtain your API key from the dashboard
3. Set up your preferred notification channels (e.g., Telegram, Discord) and nickname it "serveralert"
4. Create a new project named "ServerMonitor"

Step 2: Implement Basic Server Monitoring

Let's create a Python script to monitor basic server metrics:

import psutil
import requests
import time

BLIPHQ_API_KEY = "YOUR_API_KEY_HERE"
PROJECT_NAME = "ServerMonitor"

def send_metric(metric_name, value):
    url = "https://bliphq.com/api/push"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {BLIPHQ_API_KEY}"
    }
    payload = {
        "message": f"{metric_name}: {value}",
        "project": PROJECT_NAME,
        "tags": ["server_metric", metric_name],
        "data": {"value": value}
    }
    requests.post(url, json=payload, headers=headers)

def monitor_basic_metrics():
    cpu_percent = psutil.cpu_percent()
    memory_percent = psutil.virtual_memory().percent
    disk_percent = psutil.disk_usage('/').percent

    send_metric("cpu_usage", cpu_percent)
    send_metric("memory_usage", memory_percent)
    send_metric("disk_usage", disk_percent)

while True:
    monitor_basic_metrics()
    time.sleep(60)  # Check every minute

Step 3: Monitor Server Requests

Let's add functionality to track server requests using a Flask middleware:

from flask import Flask, request
import time

app = Flask(__name__)

@app.before_request
def track_request():
    request.start_time = time.time()

@app.after_request
def send_request_metric(response):
    total_time = time.time() - request.start_time
    send_metric("request_time", total_time)
    return response

# Your Flask routes go here

Step 4: Monitor Processes and Containers

Now, let's add process and Docker container monitoring:

import docker

def monitor_processes():
    for proc in psutil.process_iter(['pid', 'name', 'cpu_percent', 'memory_percent']):
        send_metric(f"process_{proc.info['name']}", {
            "cpu": proc.info['cpu_percent'],
            "memory": proc.info['memory_percent']
        })

def monitor_containers():
    client = docker.from_env()
    for container in client.containers.list():
        stats = container.stats(stream=False)
        cpu_usage = stats['cpu_stats']['cpu_usage']['total_usage']
        memory_usage = stats['memory_stats']['usage']
        send_metric(f"container_{container.name}", {
            "cpu": cpu_usage,
            "memory": memory_usage
        })

while True:
    monitor_basic_metrics()
    monitor_processes()
    monitor_containers()
    time.sleep(60)  # Check every minute

Step 5: Set Up Real-Time Alerts

Configure your BlipHQ account to send notifications for critical events. For example:

def check_critical_levels():
    if psutil.cpu_percent() > 90:
        send_alert("High CPU Usage", "CPU usage exceeds 90%")
    if psutil.virtual_memory().percent > 95:
        send_alert("Low Memory", "Available memory below 5%")

def send_alert(title, message):
    url = "https://bliphq.com/api/push"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {BLIPHQ_API_KEY}"
    }
    payload = {
        "message": f"ALERT: {title} - {message}",
        "project": PROJECT_NAME,
        "nickname": "serveralert",
        "tags": ["alert", title.lower().replace(" ", "_")]
    }
    requests.post(url, json=payload, headers=headers)

Step 6: Analyze Server Performance

Regularly review your BlipHQ dashboard to gain insights into:

• Server resource utilization trends
• Request patterns and response times
• Process and container performance
• Frequency and types of critical alerts

Conclusion:

By following this tutorial, you've created a comprehensive server monitoring system using BlipHQ. You can now track various server metrics, receive real-time alerts, and access detailed analytics through the BlipHQ dashboard. This setup allows you to proactively manage your server infrastructure and quickly respond to potential issues.

Note:

Remember to secure your monitoring script and consider the performance impact of frequent monitoring. Adjust the monitoring frequency and metrics collected based on your specific needs and server capabilities.