How to Utilize Python Scripts for Automation on Kamatera

Whether you’re spinning up new servers, managing existing instances, or orchestrating deployment workflows. automation is a critical component of efficient cloud infrastructure management, enabling teams to save time, reduce human error, and ensure repeatable deployments. 

This guide explores how to leverage Python scripts to automate tasks on Kamatera’s cloud platform, including running scripts, managing files, and scheduling jobs.

Let’s start by creating an account on Kamatera.

Go to console.kamatera.com and sign up for an account by providing the following information:

1. Verify Your Email: Click the verification link sent to your email by Kamatera.
2. Password: Enter your password.
3. Repeat Password: Re-enter your password and click Create Account. 
4. Enter your username and password and click Login to access Kamatera Management Console.

1. Navigate to My Cloud on the left pane, select Servers and click on Create New Server or click on Create New Server on the right pane. 

Choose the zone that works best for you:

• Asia
• North America
• Europe 
• Middle East

Note: For this setup, we used the Asia server domain to set up an Ubuntu server.

Now, choose an image.

Kamatera offers a variety of app and server images to help users set up preconfigured resources. Users can explore options such as:

• Server OS images
• Desktop OS images
• App images
• Service images 
• My private images 

For this case, we will select Server OS Images and select Ubuntu.

Under Choose Version, from the drop-down menu, select the latest version of Ubuntu.

Note: Always select the latest version.

Once the version is selected you can see message as: “Ubuntu Server version 24.04 LTS (Noble Numbat 64-bit)”

Toggle the Detailed view button to enable you to view the detailed description, including the price.  For this use case, we’ve used the server specifications below. Select whichever server specs you need.

Choose server specs

Choose networking

Users can select the network they wish to use, whether it is a public Internet network or a private local network.

Advanced configuration 

 Hide – If the user wants to hide the advanced configuration. 

 Show – If you want to see the advanced configuration.

Finalize settings

Finalize settings by setting the password, re-validating it, selecting the number of servers, specifying the server’s name, and enabling the Power On Servers option.

Note: Once the user enters the details in Finalize Settings, they can select either the monthly or hourly billing.

Billing cycle and pricing

The user can choose between the Monthly Billing Cycle and Hourly Billing Cycle.

Note: The Server Summary displays the location, operating system (including server specifications), add-on services, servers, and pricing.

Click Create Server. In Tasks Queue, you can see the Ubuntu Server is downloading.

Once the installation is successful, you will see the message as Success beside the server’s name and Ubuntu Server is reflected in the Server Management dashboard.  

Click Open, beside the Ubuntu Server.

A new screen appears. The Overview tab in the center is selected by default and it displays information like Power state, Guest OS, Zone, Public Internet (WAN), Server ID of the server and Configuration-Number of CPU. Memory Size, Disk 1.

Click on Connect to connect to the server.

Now, click on Open Remote Console to open a new terminal.

In the terminal, enter the Username and Password that you mentioned while creating a server (step-7).

Connect to your Kamatera server

To begin automating tasks, you’ll first need to connect to your Kamatera server.

Use the following command on your local machine (Linux, macOS, or Windows with PowerShell or WSL):

Command: ssh root@your-server-ip

Replace your-server-ip with the public IP address of your Kamatera server (e.g., 198.51.100.25).
Or use Kamatera’s web console.

Install Python and dependencies

To run Python scripts, you first need to ensure that Python and its package manager, pip, are installed. These tools allow you to execute Python code and install additional libraries or dependencies your scripts may need. 

For Ubuntu:

Command: sudo apt update

This command updates the list of available packages and their versions from the Ubuntu repositories. 

Command: sudo apt install python3 python3-pip –y

• python3 is the actual Python interpreter.
• python3-pip is the package manager for Python—it lets you install Python libraries like requests, flask, or psutil.
• The -y flag automatically says “yes” to any prompts during installation, so you don’t have to manually confirm.

Check Python version

After installing Python, it’s important to verify that the installation was successful and to confirm which version of Python is available on your server.

Command: python3 –version

Create your Python script

If you prefer to write or edit the script directly on the server (or just want a quick test script), you can use the nano text editor. It is already installed on most Linux systems. 

Create it directly on the server:

Command: nano my_script.py

• nano opens a text editor in the terminal.
• my_script.py is the name of your Python file. You can name it anything you like, just make sure it ends with .py.

After running the command, the nano editor opens, for testing purposes write a simple script 

print (“HI”)

After you’ve edited in the Nano editor, you need to save and exit. 

• To save your changes: Press CTRL + O (this stands for “Write Out”).

When prompted to confirm the file name, press Enter to save the file with the default name.

• To exit Nano: Press CTRL + X (this stands for “Exit”).

Your changes will be saved, and you’ll return to the terminal.

 Command: python3 my_script.py

When you run this command, Python will read and execute the code inside the file line by line.

Run scripts manually or with cron jobs

You can run your Python script either manually on demand or automatically on a schedule using cron, a built-in Linux tool for task automation.

• Manual: This command runs the script immediately and shows the output in your terminal. Use this method if you’re testing or running the script infrequently.

Command: python3 my_script.py

• Automated via cron: To run your script automatically at scheduled intervals, you can use a cron job.
  Edit the crontab by running the below command:

Command: crontab –e

When you run the above command for the first time, you may be prompted to select a text editor to edit your cron jobs. Since we’re using the Nano editor (which is user-friendly), choose option 1.

So, type 1 in this line, Choose 1-4 [1]: 1, as shown in the screen below. Press Enter to proceed.

Now the Nano editor will open and you can add your cron schedule at the bottom of the file. 

Add a line like : 0 * * * * /usr/bin/python3 /root/my_script.py >> /root/script.log 2>&1
This runs the script hourly and logs output.

After you’ve edited the crontab file in Nano, you need to save and exit. 

• To save your changes: Press CTRL + O (this stands for “Write Out”).

When prompted to confirm the file name, press Enter to save the file with the default name.

• To exit Nano: Press CTRL + X (this stands for “Exit”).

Your changes will be saved, and you’ll return to the terminal.

In the terminal, you will see, crontab: installing new crontab. This means that your new or updated cron job has been successfully saved and installed.

Automate tasks with Python

Python is a powerful scripting language you can use to automate routine server tasks. Once your script is written and tested, you can run it manually or schedule it with cron. 

Common Automation Use Cases: 

• Server Maintenance – Delete old log files, clear temp directories, or apply updates.
• Monitoring – Check CPU, memory, or disk usage and alert when thresholds are crossed.
• Data Collection – Pull data from APIs or remote servers on a schedule.
• Integration – Sync systems, trigger other workflows, or clean/format data.

Example: 

Monitor disk usage and send an alert- This Python script checks your server’s disk space and prints a warning if it’s getting low. 

Command:

import shutil
total, used, free = shutil.disk_usage(“/”)
if free / total < 0.1:
    print(“Warning: Low disk space!”)

    Command: python3 my_script.py

When you run this command, Python will read and execute the code inside the file line by line.

Use virtual environments

When working on Python projects, it’s a best practice to use a virtual environment to manage your project’s dependencies. This ensures that packages installed for one project don’t interfere with packages from another. 

Command: python3 -m venv myenv

• python3: Runs the Python 3 interpreter.
• -m venv: Uses Python’s built-in venv module to create a virtual environment.
• myenv: The name of the virtual environment folder that will be created in your current directory.

After running this command, a new folder named myenv/ is created. It contains a self-contained Python installation with its own pip, Python binaries, and installed packages. 

In the below screen, if you see after running the command: python3 –m venv myenv, we will see a message, the virtual environment was not created successfully, because ensurepip is not available. So, first install python3-venv package by running the below command. 

Command: sudo apt install python3.12-venv

When asked “Do you want to continue? [y/n]”. Enter “y”.

Set up and use a Python virtual environment 

Using a virtual environment allows you to manage dependencies in isolation for each project. 

• Command: Python3 -m venv myenv

This command creates a virtual environment.

• Command: source myenv/bin/activate

This command activates the virtual enviraonment

• Command: pip install requests 

This command installs python packages.

The ls command is used in Linux (and other Unix-like systems) to list the contents of a directory. 

Command: ls

This will display the names of files and folders in your current directory.

Going forward, we recommend the following steps to secure and monitor your server.

• Use firewalls and only expose necessary ports.
• Install monitoring tools (like Netdata or Prometheus exporters).
• Regularly update packages:

Command: sudo apt update && sudo apt upgrade -y