install.sh

#!/bin/bash

# Install required packages
pip install pyvmomi
pip install pandas

# Create the Python script file
cat > vm_performance.py << EOL
import pandas as pd
from pyVim.connect import SmartConnectNoSSL
from pyVmomi import vim
import atexit
import sys
from datetime import datetime, timedelta
import getpass

def main():
    host = input("Enter your vCenter host: ")
    user = input("Enter your vCenter username: ")
    password = getpass.getpass("Enter your vCenter password: ")

    # Connect to vCenter
    si = SmartConnectNoSSL(host=host, user=user, pwd=password)
    atexit.register(si.content.sessionManager.Logout)

    # Get the root folder
    content = si.RetrieveContent()
    container = content.rootFolder

    # Create a view for VMs
    view_manager = content.viewManager
    view = view_manager.CreateContainerView(container, [vim.VirtualMachine], True)

    # Specify the time range
    hours = int(input("Enter the number of hours far back: "))
    end_time = datetime.now()
    start_time = end_time - timedelta(hours=hours)

    # Initialize an empty list to store the data
    data = []

    # Iterate through VMs and collect CPU and memory usage data
    for vm in view.view:
        perf_manager = content.perfManager
        metric_ids = [vim.PerformanceManager.MetricId(counterId=i, instance="*") for i in [2, 24]]  # 2: CPU usage, 24: Memory usage
        query_spec = vim.PerformanceManager.QuerySpec(entity=vm, metricId=metric_ids, intervalId=20, startTime=start_time, endTime=end_time, maxSample=1)
        result = perf_manager.QueryPerf(query_spec=[query_spec])

        for r in result:
            for val in r.value:
                if val.id.counterId == 2:
                    cpu_usage = val.value[0]
                elif val.id.counterId == 24:
                    memory_usage = val.value[0]

        data.append([vm.name, cpu_usage, memory_usage])

    # Cleanup
    view.Destroy()

    # Create a DataFrame and save it to a CSV file
    df = pd.DataFrame(data, columns=["VM Name", "CPU Usage (%)", "Memory Usage (%)"])
    df.to_csv("vm_performance.csv", index=False)
    print("Data saved to vm_performance.csv")

if __name__ == "__main__":
    main()
EOL

echo "Installation complete. Run the script with 'python vm_performance.py'"