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AWS Auto Scaling using Python Boto3

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Auto Scaling Group in AWS configure using Python Boto3 

What is Auto Scaling means? 

This is key capability or power of Cloud Computing Engineers believe in their skills on scaling abilities. 

Amazon EC2 Auto Scaling helps to maintain application availability and lets automatically add or remove EC2 instances using scaling policies that we define.  There are 2 types of scaling policies : Dynamic or predictive. These scaling policies let us add or remove EC2 instances capacity to service established or real-time demand patterns.

It contains various steps involved in Auto Scaling process using Python Boto3 we will explore every step that accumulate to form a complete automation solution for a DevOps project.

ASG Groups associated with ELB and EC2 instances


 

Understanding AWS Auto scaling configuration steps

Check any running instances Create launch configuration Configure ASG for Auto scaling Verify the configuration Disable Auto Scaling
In order to setup Auto Scaling, we need Launch configuration to be created first followed by Auto Scaling group

1. Check any running instances

Get the running EC2 instance list 
import boto3
ec2_resource=boto3.resource('ec2')

instances = ec2_resource.instances.filter(
	Filters=[{'Name':'insance-state-name','Values':['running']}
	])
for i in instances:
    print(instance.id, instance.state)
Check the output
 

2. Create launch configuration 

 object client referring to 'autoscaling' method: create_launch_configuration() method is used to create launch configuration 
as_client = boto3.client('autoscaling')	

ami_id = input("Please enter AMI id to use in Auto Scaling:")
keyname = input("Please enter Key Name to use for instances:")

response = as_client.create_launch_configuration(
	LaunchConfigurationName = 'vybhava_lc',
	ImageId = ami_id,
	KeyName = kayname,
	SecurityGroup = ['vybhava_sg']
	InstanceType = 't2.micro'
)
print(response)
When you observe the printed output have 'HTTPStatusCode as 200 then it is successful. 3. Creating Auto Scaling Group The create_auto_scaling_group() method is used to create Auto Scaling group. 
asg_resp = as_client.create_auto_scaling_group(
	AutoScalingGroupName='vybhava_asg',
	LaunchConfigurationName='vybhava_lc',
	MinSize=1, MaxSize=2, DesiredCapacity=1,
	LoadBalancerNames=['vybhava_lb']
	AvailabilityZones=['ap-south-1b','ap-south-1c']
)
print (asg_resp)
print (asg_resp['ResponseMetadata']['HTTPStatusCode']) #Try this
Check the output and compare it withe AWS console
 

4. Updating ASG 

You can try scale up by increase MinSize, MaxSize, DesiredCapacity values up similarly down. When you do update remember that is should not pass LoadBalancerNames. 
update_resp = as_client.update_auto_scaling_group(
	AutoScalingGroupName='vybhava_asg',
	LaunchConfigurationName='vybhava_lc',
	MinSize=1, MaxSize=2, DesiredCapacity=1,

	AvailabilityZones=['ap-south-1b','ap-south-1c']
)

print(update_resp)
When you run down to 0 value then terminated ASG instances.

In Auto Scaling group configuration, Number of instances always remain up and running is the meaning of parameter 'DesiredCapacity'. Auto Scaling Group defining we need to define the Load Balancer in Auto Scaling setup.

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