Python DevOps Automation

Automation patterns for infrastructure, cloud, and operational tasks.

Core Principles

•Idempotent operations - Safe to run multiple times
•Error handling first - Anticipate failures
•Logging over print - Structured, searchable logs
•Configuration external - Environment variables, config files

CLI Development with Click

Use click for command-line tools

python

import click

@click.command()
@click.option('--count', default=1, help='Number of times to run')
@click.option('--verbose', is_flag=True, help='Verbose output')
@click.argument('name')
def greet(count, verbose, name):
    """Simple CLI tool."""
    for _ in range(count):
        if verbose:
            click.echo(f'Greeting: Hello {name}!')
        else:
            click.echo(f'Hello {name}!')

if __name__ == '__main__':
    greet()

See cli-patterns.md for:

•Command groups
•Progress bars
•File handling
•Click vs Typer

AWS Automation with Boto3

Use boto3 for AWS operations

python

import boto3

# S3 operations
s3 = boto3.client('s3')
s3.upload_file('local.txt', 'bucket-name', 'remote.txt')

# EC2 operations
ec2 = boto3.resource('ec2')
instances = ec2.instances.filter(
    Filters=[{'Name': 'tag:Environment', 'Values': ['production']}]
)

See boto3-patterns.md for:

•Resource vs client
•Pagination
•Error handling
•Credential management

Subprocess Management

Use subprocess for external commands

python

import subprocess

# Run command, capture output
result = subprocess.run(
    ['ls', '-la'],
    capture_output=True,
    text=True,
    check=True
)
print(result.stdout)

# Stream output in real-time
process = subprocess.Popen(
    ['long-running-command'],
    stdout=subprocess.PIPE,
    stderr=subprocess.PIPE,
    text=True
)

for line in process.stdout:
    print(line, end='')

returncode = process.wait()

See subprocess-patterns.md for:

•Error handling
•Timeouts
•Shell=True dangers
•Environment variables

Docker Automation

Use docker-py for container management

python

import docker

client = docker.from_env()

# Run container
container = client.containers.run(
    "ubuntu:latest",
    "echo hello world",
    detach=True
)

# Wait for completion
container.wait()
print(container.logs().decode())

See docker-patterns.md.

Configuration Management

python

import os
from pathlib import Path
from dataclasses import dataclass
import tomli

@dataclass
class Config:
    api_key: str
    region: str
    debug: bool = False
    
    @classmethod
    def from_env(cls):
        """Load from environment variables."""
        return cls(
            api_key=os.environ['API_KEY'],
            region=os.getenv('AWS_REGION', 'us-east-1'),
            debug=os.getenv('DEBUG', 'false').lower() == 'true'
        )
    
    @classmethod
    def from_file(cls, path: Path):
        """Load from TOML config file."""
        with open(path, 'rb') as f:
            data = tomli.load(f)
        return cls(**data)

See config-patterns.md.

Logging Best Practices

python

import logging
from pathlib import Path

# Setup logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('app.log'),
        logging.StreamHandler()
    ]
)

logger = logging.getLogger(__name__)

def deploy_app():
    logger.info("Starting deployment")
    try:
        # Deployment logic
        logger.debug("Uploading files...")
        logger.info("Deployment successful")
    except Exception as e:
        logger.error(f"Deployment failed: {e}", exc_info=True)
        raise

See logging-patterns.md.

source: DevOps with Python