As you start moving workloads to the AWS cloud and opening access to developers you will see you AWS cost increase every month without controls in place.
The best way to control and have a charge back model in place is to use AWS tags. You can have tags assigned to different departments like Marketing, Research, Finance, etc. Now, if instances are created without proper tags you can have a program stop the instances.
You accomplish two objectives with this approach. First, you find out who is creating instances outside the processes you have put in place. Second, you get allocate charges to the correct departments.
To run the following code you need
- AWS cli tools installed
- Configure AWS keys via cli
- Python3 installed
- Import the boto3 library
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| #! /usr/bin/env python3 | |
| """ | |
| This program terminate instances if proper tag is not used | |
| """ | |
| import time | |
| import boto3 | |
| start_time = time.time() | |
| ec2 = boto3.resource('ec2') | |
| ec2_client = boto3.client('ec2') | |
| tag_deparment = ['Finance', 'Marketing', 'HumanResources', 'Research'] # Your departments | |
| shutdown_instance = False | |
| for instance in ec2.instances.all(): | |
| instance_state = instance.state['Name'] | |
| if instance_state == ('running' or 'pending'): | |
| for tags in instance.tags: | |
| for department in tag_deparment: | |
| if tags['Value'] == department: | |
| shutdown_instance = False | |
| break | |
| else: | |
| shutdown_instance = True | |
| print('The following instance will be shutdown', instance.id, 'Shutdown = ', shutdown_instance) | |
| if shutdown_instance is True: | |
| ec2_client.stop_instances( | |
| InstanceIds = [instance.id], | |
| Force = True | |
| ) |
Gabe's Blog 