Python IT Automation & Monitoring Guide

1. Disk Cleanup Automation

Purpose: Automatically remove temporary and log files.

import os

downloads = "C:/Users/jonathan/Downloads"
for file in os.listdir(downloads):
if file.endswith(".tmp") or file.endswith(".log"):
os.remove(os.path.join(downloads, file))

Explanation: Cleans repetitive clutter, freeing space for better performance.

2. Active Process Monitoring

Purpose: Detect high CPU usage processes.

import psutil

for proc in psutil.process_iter(['pid','name','cpu_percent']):
if proc.info['cpu_percent'] > 80:
print(f"High CPU: {proc.info['name']} ({proc.info['cpu_percent']}%)")

Explanation: Helps IT staff proactively address resource hogs.

3. File Backup Automation

Purpose: Backup critical documents daily.

import shutil, datetime

src = "C:/Users/jonathan/Documents"
dst = f"C:/Backup/{datetime.date.today()}"
shutil.copytree(src, dst)

Explanation: Creates timestamped backups to prevent data loss.

4. Network Status Checker

Purpose: Monitor internet or VPN connectivity.

import os

hostname = "8.8.8.8"
response = os.system(f"ping -n 1 {hostname}")
if response != 0:
print("Network down!")

Explanation: Preempts helpdesk tickets for connectivity issues.

5. Email Alert Automation

Purpose: Notify IT team on critical events.

import smtplib

sender = "itadmin@example.com"
receiver = "helpdesk@example.com"
message = "Subject: Alert\n\nDisk space low on Laptop-01"

with smtplib.SMTP('smtp.example.com') as server:
server.sendmail(sender, receiver, message)

Explanation: Reduces manual notification workload.

6. JSON Log Parsing

Purpose: Analyze logs for failures or security events.

import json

with open("sign_in_logs.json") as f:
logs = json.load(f)
failed_signins = [log for log in logs if log["status"]=="Failure"]
print(failed_signins)

Explanation: Useful for auditing and proactive security monitoring.

7. Automated Screenshot Capture

Purpose: Record PC screen for troubleshooting.

import pyautogui, datetime

filename = f"screenshot_{datetime.datetime.now().strftime('%Y%m%d_%H%M')}.png"
pyautogui.screenshot(filename)

Explanation: Visual documentation of issues for support tickets.

8. GUI Interaction / OpenCV Detection

Purpose: Detect application errors visually.

import cv2

img = cv2.imread("screen.png", 0)
template = cv2.imread("error_template.png", 0)
res = cv2.matchTemplate(img, template, cv2.TM_CCOEFF_NORMED)
if res.max() > 0.8:
print("Error detected! Restart app.")

Explanation: Useful for apps without API endpoints.

9. User Provisioning Script (Azure Entra ID)

Purpose: Automate new hire onboarding.

import subprocess

subprocess.run(["powershell", "New-AzureADUser -DisplayName 'John Doe' -UserPrincipalName 'j.doe@example.com' -AccountEnabled $true"])

Explanation: Speeds up account creation.

10. Scheduled Task Creator

Purpose: Automate daily/weekly tasks on PCs.

import subprocess

subprocess.run([
"schtasks", "/create", "/tn", "DailyBackup", "/tr", "C:\\backup.py", "/sc", "daily", "/st", "09:00"
])

Explanation: Reduces errors in manual scheduling.

Master Python Orchestrator

Purpose: Combine all scripts into one automated loop.

import os, shutil, datetime, psutil, json, smtplib, pyautogui, cv2, subprocess

# Configurations omitted for brevity

def log_event(event):
... # JSON logging

def send_email(subject, body):
... # Email alert

def cleanup_files(): ...
def backup_documents(): ...
def monitor_processes(): ...
def network_check(): ...
def capture_screenshot(): ...
def opencv_error_detection(): ...
def parse_json_logs(): ...
def user_provisioning(): ...
def schedule_tasks(): ...

def main():
cleanup_files()
backup_documents()
network_check()
monitor_processes()
capture_screenshot()
opencv_error_detection()
parse_json_logs()
user_provisioning()
schedule_tasks()

if __name__ == "__main__":
main()

Explanation: Orchestrates all automated tasks, logs results, triggers alerts.

Multi-Server HTML + JSON Report Automation

Purpose: Monitor multiple servers, parse metrics, log, and send HTML report.

import requests, json, smtplib, datetime
from bs4 import BeautifulSoup
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText

SERVERS = [ ... ] # List of server dicts
# Functions: fetch_metrics, log_json, send_html_email
# Loop through servers, parse CPU/Memory, generate HTML report
# Send email if thresholds exceeded

Explanation: Centralized monitoring for multiple servers with visual HTML report and alerting.

HTML MIME Emails

Purpose: Send formatted emails via Python.

from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
import smtplib

msg = MIMEMultipart("alternative")
msg.attach(MIMEText(text, "plain"))
msg.attach(MIMEText(html, "html"))
# Send via smtplib

Explanation: Provides rich text and fallback plain text in alerts.

HTML vs HTTP

• 
  HTML: Markup language defining page content.

• 
  HTTP: Protocol to transfer HTML or other data from server to client.

• 
  Python Automation: requests.get() for HTTP, BeautifulSoup for HTML parsing.

Run Commands / Task Scheduler

• 
  Open Task Scheduler: Win + R → taskschd.msc

• 
  Run task immediately: schtasks /run /tn "Python Automation Orchestrator"

• 
  Create scheduled task via command line:

schtasks /create /tn "DailyAutomation" /tr "C:\Python39\python.exe C:\Scripts\master_automation.py" /sc daily /st 09:00

Explanation: Automates execution of Python orchestrator across PCs or remote environments.

Visual Workflow Diagrams

Python Master Orchestrator Workflow

Task Scheduler --> Python Orchestrator --> [Disk Cleanup, Backup, Network Check, Process Monitor, Screenshot, OpenCV, JSON Logging, User Provisioning, Scheduling] --> Email Alerts

Multi-Server Monitoring Workflow

Multiple Servers (HTTP Dashboards) --> Python Fetch & Parse --> JSON Logs + HTML Table Report --> Email Alerts to Helpdesk

Explanation: Visualizes how automated scripts interact with servers, logs, and alerting systems for full IT monitoring.

This document now includes all code, explanations, and workflow diagrams for comprehensive IT automation and monitoring guidance.