In my test environment, I have amazon VPC, which I am accessing using Linux server.

For performing all the activities on amazon vpc, I have used python script.For automation in amazon VPC, aws provides module boto3, which need to be installed using python pip. Using this module we list all the running instances.In below script I am creating a config file and then reading that config file.Following script perform all these steps:

• Create a config file, which is required to connect aws vpc.
• Read the config file, and list all the instance following details:
  • ‘Name’:name,
  • ‘Type’: instance.instance_type,
  • ‘State’:instance.state[‘Name’],
  • ‘Private IP’:instance.private_ip_address,
  • ‘Public IP’: instance.public_ip_address,
  • ‘Launch Time’: instance.launch_time

</script>

import ConfigParser,boto3,os,sys,paramiko
from collections import defaultdict
config = ConfigParser.RawConfigParser()
#When adding sections or items, add them in reverse order
config.add_section('EC2')
config.add_section('USER')
config.set('EC2','SSHKey','<keyname>')
config.set('EC2','VPC_IP','<vpcname>')
config.set('EC2','Security_Group','<securitygroupname>')
config.set('EC2','DisableAPI_Termination','False')
config.set('USER','Username','<ec2user>')
config.set('USER','AWS_Profile','<aws user to login>')
config.set('EC2','Region','<aws region>')
config.set('USER','Private_Key','<path_to_privatekey>')

#Writing configruation to config file
name = raw_input("Enter the config file name::: ")
with open(name, 'wb') as configfile:
config.write(configfile)
#Reading the config file
config1 = ConfigParser.ConfigParser()
config1.read(name)
ses = boto3.Session(profile_name = config1.get("USER", "AWS_Profile"))
ec2 = ses.resource('ec2')
key = paramiko.rsakey.RSAKey.from_private_key_file(filename=config1.get("USER","Private_Key")) 
running_instances = ec2.instances.filter(Filters=[{
'Name': 'instance-state-name',
'Values': ['running']}])
ec2info = defaultdict()
for instance in running_instances:
for tag in instance.tags:
if 'Name' in tag['Key']:
name = tag['Value']
ec2info[instance.id] = {
'Name':name,
'Type': instance.instance_type,
'State':instance.state['Name'],
'Private IP':instance.private_ip_address,
'Public IP': instance.public_ip_address,
'Launch Time': instance.launch_time
}
attributes = ['Name','Type','State','Private IP','Public IP','Launch Time']
for instance_id, instance in ec2info.items():
for key in attributes:
print("{0}:{1}".format(key,instance[key]))
print("------")

output of the script :

——
Name:testinstance
Type:m4.xlarge
State:running
Private IP:10.140.30.209
Public IP:None
Launch Time:2016-08-26 23:09:17+00:00
——

This blog is for those, who are very new to aws and python. They want to start both of them together. Assuming they have setup boto3 environment in their test lab.

In lab setup type python: python

It will give python prompt, we can explore boto3.

>>> import boto3
>>> dir(boto3)
[‘DEFAULT_SESSION’, ‘NullHandler’, ‘Session’, ‘__author__’, ‘__builtins__’, ‘__doc__’, ‘__file__’, ‘__name__’, ‘__package__’, ‘__path__’, ‘__version__’, ‘_get_default_session’, ‘client’, ‘docs’, ‘exceptions’, ‘logging’, ‘resource’, ‘resources’, ‘session’, ‘set_stream_logger’, ‘setup_default_session’, ‘utils’]

Perform help (boto3) ,It will show the package content with this package..

PACKAGE CONTENTS
compat
docs (package)
dynamodb (package)
ec2 (package)
exceptions
resources (package)
s3 (package)
session
utils

Lets import the resources : from boto3 import resources

>>> dir (boto3.resources)
[‘__builtins__’, ‘__doc__’, ‘__file__’, ‘__name__’, ‘__package__’, ‘__path__’, ‘action’, ‘base’, ‘collection’, ‘factory’, ‘model’, ‘params’, ‘response’]
>>>

PACKAGE CONTENTS
action
base
collection
factory
model
params
response

/*perform following on your python console or write a .py script
import boto3
ec2=boto3.resource(ec2)
#help(ec2) /*it will list all the available option with ec2*/
#help(ec2.instances) /*search for filter*/
#help(ec2.instances.filter /*list the filter option and list syntax
/* instance_iterator = ec2.instances.filter(
 | DryRun=True|False,
 | InstanceIds=[
 | 'string',
 | ],
 | Filters=[
 | {
 | 'Name': 'string',
 | 'Values': [
 | 'string',
 | ]
 | },
 | ]
*/

import boto3
ec2=boto3.resource('ec2')
instances = ec2.instances.filter(
    Filters=[{'Name': 'instance-state-name', 'Values': ['running']}])
for instance in instances:
    print(instance.id, instance.instance_type)

Boto is python sdk in amazon, which can be used for automation purpose for ec2,s3 etc.

Installation: Boto can be installed using using pip or offline. for pip the command:    pip install boto3

Offline installation we need to download the offline bundle and install, it has the dependency , download and install it.

Configuration : Before we use boto we need to set the configuration, which can be done using : 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

Alternatively, you can pass a region_name when creating clients and resources.

Lets see some the sample code:

import boto3

ec=boto3.resource(‘ec2’)

if we print ec, it shows “ec2.ServiceResource()”

Just give help(ec),it will show up the complete description what we can do ,what methods are available. Below example we want to check all the instance status

# Boto 3
#!/usr/bin/python
import boto3
ec=boto3.resource('ec2')
#help(ec)
#check the status of all the ec2 instances
for status in ec.meta.client.describe_instance_status()['InstanceStatuses']:
    print(status)