1.0 Python for DevOps Automation

Python for DevOps Automation

☁️ Cloud Automation  ·  🔄 CI/CD  ·  🏗️ Infrastructure as Code  ·  🐳 Containers

Level: DevOps Engineer Focus  |  Goal: Cloud Automation, CI/CD, Infrastructure as Code

📚 Concepts Covered

• 🎯 What is Python?
• ⚙️ Why Python for DevOps?
• 📦 Key DevOps Libraries
• 🔧 Quick Setup
• 💻 DevOps Code Examples
• 🧠 Simple Way to Remember
• 📝 Quick Knowledge Review

What is Python?

Python is a simple, readable programming language created in 1991. It reads almost like English, making it the fastest language to learn and the #1 choice for DevOps automation.

📖

Readable

Code reads like plain English — easy to write and maintain

☁️

Cloud-Ready

Best SDKs for AWS, Azure, GCP built in Python

⚡

Fast to Script

Write automation scripts in minutes, not hours

🔑 Remember It Simply:

• Python = English-like code — No complex { } or ; like Java/C++
• Python = Glue language — Connects AWS, Docker, Kubernetes, Terraform together
• Python = #1 DevOps language — Ansible, Boto3, Fabric — all Python

Why Python for DevOps? ⚙️

DevOps Task	Python Tool	What It Does
Cloud (AWS)	boto3	Manage EC2, S3, Lambda, RDS with Python
Config Management	ansible	Automate server setup and configuration
Containers	docker SDK	Build, run, and manage Docker containers
Kubernetes	kubernetes	Deploy and scale pods via Python
Terraform	subprocess	Run terraform commands from Python scripts
CI/CD	requests / subprocess	Trigger pipelines, call GitHub/Jenkins APIs
Jenkins CI/CD	requests / jenkinsapi	Trigger builds, check job status, parse results
Ansible Automation	ansible-runner	Run playbooks, manage inventory from Python
Monitoring	prometheus_client	Expose metrics, parse logs, send alerts

Key DevOps Libraries 📦

☁️ Cloud

• boto3 — AWS SDK (EC2, S3, Lambda)
• azure-sdk — Azure resources
• google-cloud — GCP resources

🐳 Containers & Orchestration

• docker — Docker SDK for Python
• kubernetes — K8s Python client

🔧 Infrastructure & Automation

• subprocess — Run shell/terraform commands
• paramiko — SSH into servers
• fabric — Remote command execution
• ansible-runner — Run Ansible playbooks from Python

🏗️ CI/CD — Jenkins

• requests — Call Jenkins REST API directly
• jenkinsapi — High-level Jenkins Python client
• python-jenkins — Manage jobs, builds, nodes

📊 Monitoring & APIs

• requests — Call REST APIs (Slack, PagerDuty)
• prometheus_client — Expose metrics
• logging — Built-in structured logging

💡 Install all at once:

pip install boto3 docker kubernetes requests paramiko fabric ansible-runner python-jenkins prometheus-client

Quick Setup 🔧

1. Install Python

# Ubuntu / Debian (most DevOps servers)
sudo apt update && sudo apt install python3 python3-pip -y
python3 --version   # should show 3.10+

# macOS
brew install python@3.11

# Verify
python3 -c "print('Python ready!')"

2. Install DevOps Packages

# Install essential DevOps packages
pip3 install boto3 docker kubernetes requests paramiko

# Save dependencies for your project
pip3 freeze > requirements.txt

# On another machine, restore them
pip3 install -r requirements.txt

3. Common pip Commands

Command	What it does
pip install boto3	Install a package
pip list	See all installed packages
pip install -r requirements.txt	Install from file
pip uninstall boto3	Remove a package

DevOps Code Examples 💻

1. AWS EC2 — List Running Instances

import boto3

ec2 = boto3.client('ec2', region_name='us-east-1')
response = ec2.describe_instances(
    Filters=[{'Name': 'instance-state-name', 'Values': ['running']}]
)

for reservation in response['Reservations']:
    for instance in reservation['Instances']:
        print(f"ID: {instance['InstanceId']}  Type: {instance['InstanceType']}")

2. Docker — List Running Containers

import docker

client = docker.from_env()

for container in client.containers.list():
    print(f"Name: {container.name}  Status: {container.status}")

3. Terraform — Run Apply from Python

import subprocess

result = subprocess.run(
    ['terraform', 'apply', '-auto-approve'],
    capture_output=True, text=True
)

if result.returncode == 0:
    print("✅ Terraform applied successfully")
else:
    print(f"❌ Error: {result.stderr}")

4. Kubernetes — Scale a Deployment

from kubernetes import client, config

config.load_kube_config()   # reads ~/.kube/config
apps_v1 = client.AppsV1Api()

apps_v1.patch_namespaced_deployment_scale(
    name='my-app',
    namespace='production',
    body={'spec': {'replicas': 5}}
)
print("✅ Scaled to 5 replicas")

5. Slack Alert — Send a Notification

import requests

webhook_url = "https://hooks.slack.com/services/YOUR/WEBHOOK/URL"

requests.post(webhook_url, json={
    "text": "✅ Deployment to production succeeded!"
})

6. SSH — Run Command on Remote Server

import paramiko

ssh = paramiko.SSHClient()
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect('192.168.1.100', username='ubuntu', key_filename='~/.ssh/id_rsa')

stdin, stdout, stderr = ssh.exec_command('df -h')
print(stdout.read().decode())
ssh.close()

7. Jenkins — Trigger a Build via Python

What is Jenkins? Jenkins is a CI/CD server. Python can talk to it using its REST API to trigger builds, check status, and get logs — without clicking the UI.

import requests
from requests.auth import HTTPBasicAuth

JENKINS_URL = "http://jenkins.mycompany.com"
JOB_NAME    = "deploy-production"
USER        = "admin"
API_TOKEN   = "your-api-token"   # from Jenkins → User → Configure

# Trigger a build
response = requests.post(
    f"{JENKINS_URL}/job/{JOB_NAME}/build",
    auth=HTTPBasicAuth(USER, API_TOKEN)
)

if response.status_code == 201:
    print("✅ Jenkins build triggered!")
else:
    print(f"❌ Failed: {response.status_code}")

8. Jenkins — Check Build Status

import requests
from requests.auth import HTTPBasicAuth

JENKINS_URL = "http://jenkins.mycompany.com"
JOB_NAME    = "deploy-production"
BUILD_NUM   = "lastBuild"

response = requests.get(
    f"{JENKINS_URL}/job/{JOB_NAME}/{BUILD_NUM}/api/json",
    auth=HTTPBasicAuth("admin", "your-api-token")
).json()

print(f"Job:    {response['fullDisplayName']}")
print(f"Result: {response['result']}")
print(f"URL:    {response['url']}")

9. Ansible — Run a Playbook from Python

What is Ansible? Ansible automates server configuration using YAML playbooks. Python's ansible-runner library lets you trigger and control those playbooks from your Python scripts.

import ansible_runner

# Run a playbook
result = ansible_runner.run(
    playbook='deploy.yml',
    inventory='hosts.ini',
    private_data_dir='/opt/ansible'
)

if result.rc == 0:
    print("✅ Ansible playbook succeeded")
else:
    print(f"❌ Playbook failed — status: {result.status}")

10. Ansible — Dynamic Inventory with Python

import boto3
import json

# Build Ansible inventory from AWS EC2 automatically
ec2 = boto3.client('ec2', region_name='us-east-1')
response = ec2.describe_instances(
    Filters=[{'Name': 'instance-state-name', 'Values': ['running']}]
)

inventory = {'all': {'hosts': []}}

for r in response['Reservations']:
    for i in r['Instances']:
        inventory['all']['hosts'].append(i['PublicIpAddress'])

# Print as JSON — Ansible reads this as a dynamic inventory
print(json.dumps(inventory, indent=2))

# Run: ansible-playbook -i script.py deploy.yml

Simple Way to Remember 🧠

📝 Syntax Rules (3 to remember)

• Indentation = code blocks — use 4 spaces, no { }
• No semicolons — just press Enter
• import first — always import library before using it

import boto3          # 1. import
ec2 = boto3.client()  # 2. use it
if status == 'ok':    # 3. indent block
    print('ok')       # 4 spaces indent

🔑 DevOps Data Types (4 to remember)

• List — servers = ['web1', 'web2']
• Dict — config = {'env': 'prod'}
• String — region = 'us-east-1'
• Boolean — healthy = True

🔄 Control Flow (3 patterns)

# Loop over servers
for server in servers:
    deploy(server)

# Check condition
if status == 'running':
    restart(server)

# Function
def deploy(server):
    print(f"Deploying {server}")

🧠 Memory Shortcut — "PILAF"

P	Packages — always import first
I	Indentation — 4 spaces = 1 block level
L	Loops — for x in list to repeat tasks
A	Actions — functions def deploy():
F	Flow — if/else to handle success/failure

Quick Knowledge Review 📝

Q1: What Python library do you use to manage AWS resources?

💡 boto3 — the official AWS SDK for Python. import boto3 then call boto3.client('ec2'), boto3.client('s3') etc.

Q2: How do you run a shell command (like terraform apply) from Python?

💡 Use the built-in subprocess module:
subprocess.run(['terraform', 'apply', '-auto-approve'], capture_output=True)

Q3: What does indentation mean in Python?

💡 In Python, 4 spaces = 1 code block. There are no { } braces. Every line inside a loop, if-statement, or function must be indented by 4 spaces.

Q4: Which library do you use to control Docker containers from Python?

💡 The docker SDK: import docker → client = docker.from_env() → client.containers.list()

Q5: How do you SSH into a server and run a command using Python?

💡 Use paramiko: ssh.connect('server-ip', username='ubuntu', key_filename='~/.ssh/id_rsa') then ssh.exec_command('your-command')

Q6: What does PILAF stand for in Python DevOps?

💡 Packages (import) · Indentation (4 spaces) · Loops (for) · Actions (def) · Flow (if/else)

Q7: How does Python talk to Jenkins to trigger a build?

💡 Use the requests library to call Jenkins REST API with HTTP Basic Auth (username + API token).

requests.post(f"{JENKINS_URL}/job/{JOB_NAME}/build", auth=HTTPBasicAuth(user, token))

A 201 response = build triggered. You can also check status at /job/<name>/lastBuild/api/json.

Q8: What is Ansible and how do you run a playbook from Python?

💡 Ansible automates server setup/config using YAML playbooks. From Python, use ansible-runner:

ansible_runner.run(playbook='deploy.yml', inventory='hosts.ini', private_data_dir='/opt/ansible')

Check result.rc == 0 for success. You can also build a dynamic inventory using boto3 (pull live EC2 IPs) and pass it to Ansible automatically.

↑ Top