How to Monitor Your ESX CPU and RAM Resources from Python

In this article, I’ll show you how to monitor your ESX CPU and RAM resources from Python. To do this, we’ll use a Python script that will allow us to monitor the resources used on our ESX hypervisor.

Before we get started, it’s important to note that monitoring your ESX resources is crucial to ensuring that your infrastructure is running efficiently and avoiding performance and downtime issues. Additionally, by automating this process with a Python script, you can save time and effort by not having to do it manually.

Now, to begin the process of monitoring your ESX resources from Python, you’ll need to install the following libraries:

pyVmomi: a Python library that provides an API for interacting with vSphere and ESX.
ssl: a Python library that provides socket layer security functionality.

Once you have installed these libraries, you can start writing your script to monitor your ESX resources. The script we’ll be using in this article will connect to your ESX and retrieve the host hardware information, as well as the information for running virtual machines. It will then calculate the total amount of CPU and RAM assigned to the virtual machines and display the results in the output.

But don’t worry if all of this seems a bit complicated! I’ll explain how the script works step by step.

First, we import the necessary libraries and set the login credentials for our ESX hypervisor:

import ssl
from pyVim.connect import SmartConnect, Disconnect
from pyVmomi import vim

# ESX hypervisor login information
hostname = 'esx_hostname_or_ip'
username = 'username'
password = 'password'

Next, we create a custom SSL context that will allow us to connect to the ESX hypervisor:

# Create a custom SSL context
context = ssl.create_default_context()
context.check_hostname = False
context.verify_mode = ssl.CERT_NONE

# Connect to the ESX hypervisor with the custom SSL context
si = SmartConnect(host=hostname, user=username, pwd=password, sslContext=context)
content = si.RetrieveContent()

Then, we retrieve the host hardware information using the content object we created in the previous step:

# Get the host hardware information
host_system = content.rootFolder.childEntity[0].hostFolder.childEntity[0].host[0].summary.hardware
num_cpu_cores = host_system.numCpuCores
num_cpu_threads = host_system.numCpuThreads
total_memory = host_system.memorySize / (1024 ** 3)
cpu_model = host_system.cpuModel

After that, we retrieve the information for running virtual machines using the content object again:

# Get information for running virtual machines
vm_properties = ['name', 'config.hardware.numCPU', 'config.hardware.memoryMB']
vm_view = content.viewManager.CreateContainerView(content.rootFolder, [vim.VirtualMachine], True)
vms = vm_view.view
vm_view.Destroy()

Next, we calculate the total amount of CPU and RAM assigned to the running virtual machines and display it in the output:

# Display the total amount of CPU and RAM assigned to the virtual machines
print(f"Total amount of CPU assigned to the virtual machines: {num_vcpu_assigned}")
print(f"Total amount of memory assigned to the virtual machines: {total_memory_assigned:.2f} GB")
print(f"Total memory of the host: {total_memory:.2f} GB")

Finally, we close the connection to the ESX hypervisor:

# Disconnect from the ESX hypervisor
Disconnect(si)

With this script, we can obtain valuable information about our ESX resources and ensure that everything is running properly. Additionally, by using a Python script to monitor our ESX resources, we can automate this process and save time and effort.

In summary, monitoring your ESX CPU and RAM resources is essential to ensuring that your infrastructure is running efficiently and avoiding performance and downtime issues. By automating this process with a Python script, you can save time and effort by not having to do it manually. I hope this article has been helpful to you and I encourage you to try this script in your own environment!

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