DeletePolicy

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Event Information

• The DeletePolicy event in AWS Auto Scaling refers to the deletion of an Auto Scaling policy.
• When this event occurs, it means that a specific policy associated with an Auto Scaling group has been deleted.
• This event is typically triggered when an administrator or user manually deletes a policy or when a scaling policy is no longer needed for the Auto Scaling group.

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Examples

• Unauthorized deletion of Auto Scaling groups: If the DeletePolicy for Auto Scaling is not properly configured, it may allow unauthorized users or malicious actors to delete Auto Scaling groups, leading to disruption of services and potential data loss.
• Accidental deletion of critical resources: Misconfiguration of the DeletePolicy can result in accidental deletion of critical resources associated with Auto Scaling, such as EC2 instances, load balancers, or databases, impacting the availability and functionality of the application.
• Lack of audit trail: Inadequate logging and monitoring of Auto Scaling deletion events can make it difficult to track and investigate any unauthorized or accidental deletions, hindering incident response and forensic analysis.

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Remediation

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Using Console

1. Identify the issue: Use the AWS console to monitor the Auto Scaling group and identify any scaling issues or anomalies. Look for instances that are consistently failing health checks or instances that are not being replaced when they become unhealthy.

2. Adjust Auto Scaling group settings: Access the AWS console and navigate to the Auto Scaling group that is experiencing the issue. Modify the desired capacity, minimum size, or maximum size of the group to ensure that it can scale up or down as needed. This can be done by selecting the Auto Scaling group, clicking on the “Edit” button, and adjusting the appropriate settings.

3. Configure health checks: Configure health checks for the Auto Scaling group to ensure that instances are replaced when they become unhealthy. In the AWS console, go to the Auto Scaling group, select the “Health check type” option, and choose the appropriate health check type (e.g., EC2 or ELB). Configure the health check grace period and threshold as per your requirements.

4. Monitor and test: After making the necessary adjustments, monitor the Auto Scaling group to ensure that instances are scaling up or down as expected. Test the health check configuration by intentionally causing an instance to become unhealthy and verifying that it is replaced by a new instance.

5. Review and optimize: Regularly review the Auto Scaling group settings and health check configurations to ensure they are still appropriate for your application’s needs. Optimize the scaling policies and thresholds based on the observed behavior and performance of your application.

Note: The steps provided are general guidelines and may vary depending on the specific requirements and configurations of your AWS Auto Scaling group. It is recommended to refer to the AWS documentation for detailed instructions and best practices.

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Using CLI

1. To remediate an issue with AWS AutoScaling using AWS CLI, you can use the following CLI commands:

• To update the desired capacity of an Auto Scaling group:

aws autoscaling update-auto-scaling-group --auto-scaling-group-name <auto-scaling-group-name> --desired-capacity <desired-capacity>

Replace <auto-scaling-group-name> with the name of your Auto Scaling group and <desired-capacity> with the desired number of instances.

• To update the minimum and maximum size of an Auto Scaling group:

aws autoscaling update-auto-scaling-group --auto-scaling-group-name <auto-scaling-group-name> --min-size <min-size> --max-size <max-size>

Replace <auto-scaling-group-name> with the name of your Auto Scaling group, <min-size> with the minimum number of instances, and <max-size> with the maximum number of instances.

• To update the launch configuration of an Auto Scaling group:

aws autoscaling update-auto-scaling-group --auto-scaling-group-name <auto-scaling-group-name> --launch-configuration-name <launch-configuration-name>

Replace <auto-scaling-group-name> with the name of your Auto Scaling group and <launch-configuration-name> with the name of the updated launch configuration.

2. To remediate an issue with AWS AutoScaling using AWS CLI, you can use the following CLI commands:

• To suspend scaling processes for an Auto Scaling group:

aws autoscaling suspend-processes --auto-scaling-group-name <auto-scaling-group-name> --scaling-processes <scaling-processes>

Replace <auto-scaling-group-name> with the name of your Auto Scaling group and <scaling-processes> with a comma-separated list of scaling processes to suspend.

• To resume scaling processes for an Auto Scaling group:

aws autoscaling resume-processes --auto-scaling-group-name <auto-scaling-group-name> --scaling-processes <scaling-processes>

Replace <auto-scaling-group-name> with the name of your Auto Scaling group and <scaling-processes> with a comma-separated list of scaling processes to resume.

• To set a specific instance protection state for instances in an Auto Scaling group:

aws autoscaling set-instance-protection --instance-ids <instance-ids> --auto-scaling-group-name <auto-scaling-group-name> --protected-from-scale-in <true|false>

Replace <instance-ids> with a comma-separated list of instance IDs, <auto-scaling-group-name> with the name of your Auto Scaling group, and <true|false> with either true or false to enable or disable instance protection.

3. To remediate an issue with AWS AutoScaling using AWS CLI, you can use the following CLI commands:

• To create a new launch configuration:

aws autoscaling create-launch-configuration --launch-configuration-name <launch-configuration-name> --image-id <image-id> --instance-type <instance-type> --security-groups <security-groups> --key-name <key-name>

Replace <launch-configuration-name> with the name of the new launch configuration, <image-id> with the ID of the desired Amazon Machine Image (AMI), <instance-type> with the desired instance type, <security-groups> with a comma-separated list of security group IDs, and <key-name> with the name of the key pair.

• To delete an existing launch configuration:

aws autoscaling delete-launch-configuration --launch-configuration-name <launch-configuration-name>

Replace <launch-configuration-name> with the name of the launch configuration to delete.

• To update the instance protection settings for instances in an Auto Scaling group:

aws autoscaling set-instance-protection --instance-ids <instance-ids> --auto-scaling-group-name <auto-scaling-group-name> --protected-from-scale-in <true|false>

Replace <instance-ids> with a comma-separated list of instance IDs, <auto-scaling-group-name> with the name of your Auto Scaling group, and <true|false> with either true or false to enable or disable instance protection.

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Using Python

To remediate AWS AutoScaling issues using Python, you can use the following approaches:

1. Adjusting Auto Scaling Group (ASG) Parameters:

   • Use the AWS SDK for Python (Boto3) to modify the desired capacity, minimum and maximum size of the ASG based on the specific requirements.
   • Example script:

     import boto3
     
     def adjust_asg_capacity(asg_name, min_size, max_size, desired_capacity):
         autoscaling_client = boto3.client('autoscaling')
         response = autoscaling_client.update_auto_scaling_group(
             AutoScalingGroupName=asg_name,
             MinSize=min_size,
             MaxSize=max_size,
             DesiredCapacity=desired_capacity
         )
         print(response)
     
     adjust_asg_capacity('my-asg', 2, 10, 5)
     

2. Modifying Launch Configuration:

   • Use Boto3 to update the launch configuration associated with the ASG to change instance types, security groups, or any other required configurations.
   • Example script:

     import boto3
     
     def modify_launch_configuration(lc_name, instance_type, security_groups):
         autoscaling_client = boto3.client('autoscaling')
         response = autoscaling_client.update_launch_configuration(
             LaunchConfigurationName=lc_name,
             InstanceType=instance_type,
             SecurityGroups=security_groups
         )
         print(response)
     
     modify_launch_configuration('my-lc', 't2.micro', ['sg-12345678'])
     

3. Implementing Custom Scaling Policies:

   • Use Boto3 to create custom scaling policies that define specific scaling actions based on CloudWatch alarms or other metrics.
   • Example script:

     import boto3
     
     def create_scaling_policy(asg_name, policy_name, adjustment_type, scaling_adjustment, cooldown):
         autoscaling_client = boto3.client('autoscaling')
         response = autoscaling_client.put_scaling_policy(
             AutoScalingGroupName=asg_name,
             PolicyName=policy_name,
             AdjustmentType=adjustment_type,
             ScalingAdjustment=scaling_adjustment,
             Cooldown=cooldown
         )
         print(response)
     
     create_scaling_policy('my-asg', 'my-policy', 'ChangeInCapacity', 2, 300)
     

Please note that the provided scripts are just examples and may need to be customized based on your specific requirements and environment.