aws-autoscaling

Automatically scale EC2 instance groups based on demand

TLDR

Create an Auto Scaling group with a launch template

$ aws autoscaling create-auto-scaling-group --auto-scaling-group-name [my-asg] --launch-template LaunchTemplateId=[lt-12345] --min-size [1] --max-size [5] --vpc-zone-identifier "[subnet-abc,subnet-def]"

List Auto Scaling groups

$ aws autoscaling describe-auto-scaling-groups

Update group capacity

$ aws autoscaling update-auto-scaling-group --auto-scaling-group-name [my-asg] --desired-capacity [3]

Set scaling policy (target tracking)

$ aws autoscaling put-scaling-policy --auto-scaling-group-name [my-asg] --policy-name [cpu-policy] --policy-type TargetTrackingScaling --target-tracking-configuration file://[config.json]

Describe instances in a group

$ aws autoscaling describe-auto-scaling-instances

Roll out a new launch template version with an instance refresh

$ aws autoscaling start-instance-refresh --auto-scaling-group-name [my-asg]

Attach a load balancer target group

$ aws autoscaling attach-load-balancer-target-groups --auto-scaling-group-name [my-asg] --target-group-arns [arn:aws:elasticloadbalancing:...]

Delete an Auto Scaling group

$ aws autoscaling delete-auto-scaling-group --auto-scaling-group-name [my-asg] --force-delete

SYNOPSIS

aws autoscaling command [options]

DESCRIPTION

aws autoscaling manages Amazon EC2 Auto Scaling groups that automatically adjust the number of EC2 instances based on demand or schedules. Groups maintain application availability and allow automatic scaling up during demand spikes and scaling down to reduce costs.Launch templates or launch configurations define instance settings (AMI, instance type, security groups). Scaling policies determine when and how to scale based on metrics like CPU utilization or request count.Target tracking scaling maintains a specific metric value (e.g., 50% CPU). Step scaling adjusts capacity in steps based on alarm thresholds. Scheduled scaling changes capacity at specified times.Health checks (EC2 or ELB) detect unhealthy instances for automatic replacement. The health-check-grace-period prevents premature termination of instances still initializing.

PARAMETERS

create-auto-scaling-group

Create a new Auto Scaling group

describe-auto-scaling-groups

List Auto Scaling groups and their configuration

update-auto-scaling-group

Modify group settings (capacity, health checks, etc.)

delete-auto-scaling-group

Delete an Auto Scaling group

put-scaling-policy

Create or update a scaling policy

describe-scaling-activities

View scaling activity history

start-instance-refresh

Replace instances to roll out a new launch template version

put-scheduled-update-group-action

Create a scheduled scaling action

set-desired-capacity

Set the desired number of instances

attach-load-balancer-target-groups

Attach target groups to the group

create-launch-configuration

Create a launch configuration (legacy)

--auto-scaling-group-name name

Name of the Auto Scaling group

--launch-template spec

Launch template ID or name and version

--min-size n

Minimum number of instances

--max-size n

Maximum number of instances

--desired-capacity n

Desired number of instances

--vpc-zone-identifier subnets

Comma-separated subnet IDs

--health-check-type type

EC2 or ELB health check type

--health-check-grace-period seconds

Seconds before health checks start

--force-delete

Delete even with running instances

INSTALL

sudo dnf install aws

sudo pacman -S aws-cli

sudo apk add aws-cli

sudo zypper install aws-cli

CAVEATS

Launch templates are recommended over legacy launch configurations. Deleting a group with running instances requires --force-delete. Scaling activities have rate limits. Instances may take time to become healthy, affecting scaling responsiveness.

HISTORY

Amazon EC2 Auto Scaling launched in May 2009 as one of AWS's earliest services for elastic compute capacity. Originally using launch configurations, AWS introduced launch templates in 2017 for more flexibility. The service has expanded to support mixed instance types, predictive scaling, and warm pools for faster scaling.

RESOURCES

Source code · Documentation