List ec2 instances running in your account.
$ python3 list_ec2_instances.py --help
usage: list_ec2_instances.py [-h] [-price]
List EC2 instances
optional arguments:
-h, --help show this help message and exit
-price, -p Pass this if you want the prices to be included
$ python3 list_ec2_instances.py
| Type | Launch Time | Private IP Address | Key Name | Tag | State |
|------------+---------------+----------------------+------------+--------------------+---------|
| m1.small | 2014-01-02 | xx.xxx.x.xxx | key1 | webserver1 | running |
| m1.small | 2014-01-02 | xx.xxx.x.xxx | key1 | webserver2 | running |
| m1.large | 2014-10-14 | xx.xxx.x.xxx | key1 | webserver3 | running |
| m3.large | 2015-06-11 | xx.xxx.x.xxx | key3 | database1 | running |
| c3.2xlarge | 2016-02-09 | xx.xxx.x.xxx | key2 | database2 | running |
| c3.2xlarge | 2016-02-11 | xx.xxx.x.xx | key2 | database3 | running |
| c3.2xlarge | 2016-02-11 | xx.xxx.x.xx | key3 | loadbalancer1 | running |
| m3.medium | 2016-06-08 | xx.xxx.x.xx | key3 | loadbalancer2 | running |
| m2.4xlarge | 2016-07-18 | xx.xxx.x.xxx | key4 | backup-database | running |
| m3.xlarge | 2016-08-09 | xx.xxx.x.xxx | key3 | backup-webserver | running |
Time taken: 0:00:00.745601
$ python3 list_ec2_instances.py -p
----------------------------------------
Please wait, getting ec2-instances
----------------------------------------
| Type | Launch Time | Private IP Address | Key Name | Tag | State | Price per hour | Price per month |
|------------+---------------+----------------------+------------+--------------------+---------+------------------+-------------------|
| m1.small | 2014-01-02 | xx.xxx.x.xxx | key1 | webserver1 | running | 0.044 | 32.12 |
| m1.small | 2014-01-02 | xx.xxx.x.xxx | key1 | webserver2 | running | 0.044 | 32.12 |
| m1.large | 2014-10-14 | xx.xxx.x.xxx | key1 | webserver3 | running | 0.175 | 127.75 |
| m3.large | 2015-06-11 | xx.xxx.x.xxx | key3 | database1 | running | 0.133 | 97.09 |
| c3.2xlarge | 2016-02-09 | xx.xxx.x.xxx | key2 | database2 | running | 0.42 | 306.6 |
| c3.2xlarge | 2016-02-11 | xx.xxx.x.xx | key2 | database3 | running | 0.42 | 306.6 |
| c3.2xlarge | 2016-02-11 | xx.xxx.x.xx | key3 | loadbalancer1 | running | 0.42 | 306.6 |
| m3.medium | 2016-06-08 | xx.xxx.x.xx | key3 | loadbalancer2 | running | 0.067 | 48.91 |
| m2.4xlarge | 2016-07-18 | xx.xxx.x.xxx | key4 | backup-database | running | 0.98 | 715.4 |
| m3.xlarge | 2016-08-09 | xx.xxx.x.xxx | key3 | backup-webserver | running | 0.266 | 194.18 |
Total amount per month: $2,167.37
Time taken: 0:00:09.387928
- python3
- boto3 (pip install boto3)
- tabulate (pip install tabulate)
Before you can begin using Boto 3, you should set up authentication credentials. Credentials for your AWS account can be found in the IAM Console. You can create or use an existing user. Go to manage access keys and generate a new set of keys.
If you have the AWS CLI installed, then you can use it to configure your credentials file:
aws configure
Alternatively, you can create the credential file yourself. By default, its location is at ~/.aws/credentials:
[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY
You may also want to set a default region. This can be done in the configuration file. By default, its location is at ~/.aws/config:
[default]
region=us-east-1
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