ECS service auto scaling in AWS - Commands & Configuration

Introduction

When your app runs on AWS ECS, traffic can change a lot. ECS service auto scaling helps your app add or remove running copies automatically to handle more or less users smoothly.

When your website gets more visitors during the day and fewer at night, and you want to save money by running fewer servers at night.

When your app suddenly gets a lot of users and you want it to stay fast without crashing.

When you want to keep your app healthy by automatically replacing unhealthy copies.

When you want to avoid manual work of changing server numbers based on guesswork.

When you want to meet user demand without paying for too many servers all the time.

Config File - ecs-service-autoscaling.json

ecs-service-autoscaling.json

{
  "Resources": {
    "MyECSCluster": {
      "Type": "AWS::ECS::Cluster",
      "Properties": {
        "ClusterName": "example-ecs-cluster"
      }
    },
    "MyTaskDefinition": {
      "Type": "AWS::ECS::TaskDefinition",
      "Properties": {
        "Family": "example-task",
        "Cpu": "256",
        "Memory": "512",
        "NetworkMode": "awsvpc",
        "RequiresCompatibilities": ["FARGATE"],
        "ContainerDefinitions": [
          {
            "Name": "example-container",
            "Image": "nginx:1.23",
            "PortMappings": [
              {
                "ContainerPort": 80,
                "Protocol": "tcp"
              }
            ]
          }
        ]
      }
    },
    "MyECSService": {
      "Type": "AWS::ECS::Service",
      "Properties": {
        "Cluster": { "Ref": "MyECSCluster" },
        "TaskDefinition": { "Ref": "MyTaskDefinition" },
        "DesiredCount": 1,
        "LaunchType": "FARGATE",
        "NetworkConfiguration": {
          "AwsvpcConfiguration": {
            "AssignPublicIp": "ENABLED",
            "Subnets": ["subnet-0123456789abcdef0"],
            "SecurityGroups": ["sg-0123456789abcdef0"]
          }
        }
      }
    },
    "MyScalableTarget": {
      "Type": "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties": {
        "MaxCapacity": 4,
        "MinCapacity": 1,
        "ResourceId": { "Fn::Join": ["", ["service/", { "Ref": "MyECSCluster" }, "/", { "Fn::GetAtt": ["MyECSService", "Name"] }]] },
        "RoleARN": "arn:aws:iam::123456789012:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService",
        "ScalableDimension": "ecs:service:DesiredCount",
        "ServiceNamespace": "ecs"
      }
    },
    "MyScalingPolicy": {
      "Type": "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties": {
        "PolicyName": "CpuScalingPolicy",
        "PolicyType": "TargetTrackingScaling",
        "ScalingTargetId": { "Ref": "MyScalableTarget" },
        "TargetTrackingScalingPolicyConfiguration": {
          "TargetValue": 50.0,
          "PredefinedMetricSpecification": {
            "PredefinedMetricType": "ECSServiceAverageCPUUtilization"
          },
          "ScaleInCooldown": 60,
          "ScaleOutCooldown": 60
        }
      }
    }
  }
}

This JSON is a CloudFormation template that sets up ECS service auto scaling.

• MyECSCluster: Creates an ECS cluster to run your app.
• MyTaskDefinition: Defines the app container with CPU, memory, and image.
• MyECSService: Runs the app on Fargate with network settings.
• MyScalableTarget: Tells AWS which ECS service to scale and the min/max copies.
• MyScalingPolicy: Sets a rule to keep CPU usage around 50% by adding or removing copies.

Commands

This command creates the ECS cluster, service, and auto scaling setup using the CloudFormation template.

Terminal

aws cloudformation deploy --template-file ecs-service-autoscaling.json --stack-name example-ecs-autoscaling --capabilities CAPABILITY_NAMED_IAM

Expected Output

Waiting for stack create/update to complete...

Successfully created/updated stack - example-ecs-autoscaling

→

--template-file - Specifies the CloudFormation template file to use.

→

--stack-name - Names the CloudFormation stack.

→

--capabilities - Allows creation of IAM roles needed for auto scaling.

Checks the status of the ECS service to confirm it is running and ready for auto scaling.

Terminal

aws ecs describe-services --cluster example-ecs-cluster --services example-ecs-autoscaling-MyECSService-XYZ123

Expected Output

{

    "services": [

        {

            "serviceName": "example-ecs-autoscaling-MyECSService-XYZ123",

            "status": "ACTIVE",

            "desiredCount": 1,

            "runningCount": 1

        }

    ]

}

→

--cluster - Specifies the ECS cluster name.

→

--services - Specifies the ECS service name to describe.

Verifies the scalable target is registered and ready for scaling actions.

Terminal

aws application-autoscaling describe-scalable-targets --service-namespace ecs --resource-id service/example-ecs-cluster/example-ecs-autoscaling-MyECSService-XYZ123 --scalable-dimension ecs:service:DesiredCount

Expected Output

{

    "ScalableTargets": [

        {

            "ServiceNamespace": "ecs",

            "ResourceId": "service/example-ecs-cluster/example-ecs-autoscaling-MyECSService-XYZ123",

            "ScalableDimension": "ecs:service:DesiredCount",

            "MinCapacity": 1,

            "MaxCapacity": 4,

            "RoleARN": "arn:aws:iam::123456789012:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService",

            "CreationTime": "2024-06-01T12:00:00Z"

        }

    ]

}

→

--service-namespace - Specifies the AWS service namespace, here ECS.

→

--resource-id - Identifies the ECS service to scale.

→

--scalable-dimension - Defines what property to scale, here the desired count of tasks.

Key Concept

If you remember nothing else from this pattern, remember: ECS service auto scaling adjusts the number of running app copies automatically based on CPU usage to keep your app fast and cost-efficient.

Common Mistakes

Not specifying the correct IAM role ARN for auto scaling in the scalable target.

Without the right IAM role, AWS cannot perform scaling actions, so auto scaling won't work.

Use the AWS managed service role ARN for ECS auto scaling or create a proper IAM role with required permissions.

Setting MinCapacity and MaxCapacity to the same value.

This disables scaling because the service cannot scale beyond that fixed number.

Set MinCapacity lower than MaxCapacity to allow scaling up and down.

Not enabling the right metric in the scaling policy (e.g., using CPU when your app is memory-bound).

Scaling triggers won't match actual load, causing poor performance or wasted resources.

Choose the metric that best reflects your app's load, like CPU or memory utilization.

Summary

Use a CloudFormation template to define ECS cluster, service, scalable target, and scaling policy.

Deploy the template with AWS CLI to create the infrastructure and auto scaling setup.

Verify the ECS service and scalable target status with AWS CLI commands to ensure auto scaling is active.

Practice

1. What is the main purpose of ECS service auto scaling?

easy

A. Store container logs for analysis

B. Manually start and stop containers

C. Automatically adjust the number of running containers based on demand

D. Create new ECS clusters automatically

Solution

1. Step 1: Understand ECS service auto scaling function

   ECS service auto scaling changes the number of containers automatically to match workload.

2. Step 2: Compare options to this function

   Only Automatically adjust the number of running containers based on demand describes automatic adjustment of container count based on demand.

3. Final Answer:

   Automatically adjust the number of running containers based on demand -> Option C

4. Quick Check:

   Auto scaling adjusts container count = Automatically adjust containers [OK]

Hint: Auto scaling means automatic container count changes [OK]

Common Mistakes:

• Confusing auto scaling with manual container management
• Thinking auto scaling creates clusters
• Believing auto scaling stores logs

2. Which of the following is the correct way to specify a target tracking scaling policy for CPU utilization in ECS service auto scaling?

easy

A. "TargetValue": 50, "PredefinedMetricSpecification": {"PredefinedMetricType": "ECSServiceAverageCPUUtilization"}

B. "TargetValue": "high", "PredefinedMetricSpecification": {"PredefinedMetricType": "CPUUsage"}

C. "TargetValue": 100, "MetricName": "MemoryUtilization"

D. "TargetValue": 30, "PredefinedMetricSpecification": {"PredefinedMetricType": "NetworkIn"}

Solution

1. Step 1: Identify correct metric type for CPU utilization

   The predefined metric for ECS CPU is "ECSServiceAverageCPUUtilization" with a numeric target value.

2. Step 2: Check option syntax and metric correctness

   "TargetValue": 50, "PredefinedMetricSpecification": {"PredefinedMetricType": "ECSServiceAverageCPUUtilization"} uses correct metric type and numeric target value 50, which is valid.

3. Final Answer:

   "TargetValue": 50, "PredefinedMetricSpecification": {"PredefinedMetricType": "ECSServiceAverageCPUUtilization"} -> Option A

4. Quick Check:

   Correct metric and numeric target = "TargetValue": 50, "PredefinedMetricSpecification": {"PredefinedMetricType": "ECSServiceAverageCPUUtilization"} [OK]

Hint: Use numeric target and correct predefined metric name [OK]

Common Mistakes:

• Using string instead of number for TargetValue
• Using wrong metric names like CPUUsage
• Mixing memory or network metrics for CPU scaling

3. Given this ECS service auto scaling configuration snippet:

{"MinCapacity": 2, "MaxCapacity": 5, "TargetValue": 60}

What happens when CPU utilization stays at 70% for a long time?

medium

A. The service scales up to 5 containers to reduce CPU load

B. The service scales down to 2 containers to save cost

C. The service keeps running 2 containers without change

D. The service crashes due to high CPU

Solution

1. Step 1: Understand scaling triggers from CPU target

   TargetValue 60 means ECS tries to keep CPU near 60%. If CPU is 70%, it needs more containers.

2. Step 2: Apply min and max capacity limits

   Min is 2, max is 5. Scaling up is allowed up to 5 containers to reduce CPU load.

3. Final Answer:

   The service scales up to 5 containers to reduce CPU load -> Option A

4. Quick Check:

   CPU above target scales up containers = The service scales up to 5 containers to reduce CPU load [OK]

Hint: CPU above target scales up, below scales down [OK]

Common Mistakes:

• Thinking service scales down when CPU is high
• Ignoring max capacity limit
• Assuming service crashes on high CPU

4. You configured ECS service auto scaling but the service never scales out even when CPU is high. What is a likely cause?

medium

A. The service has no load balancer attached

B. The target CPU utilization is set to 100%

C. The ECS cluster has no running tasks

D. The maximum capacity is set equal to the minimum capacity

Solution

1. Step 1: Analyze scaling limits

   If max capacity equals min capacity, no room to scale out exists.

2. Step 2: Check other options

   Target 100% means scaling triggers only at max CPU, but scaling can still happen. No running tasks or load balancer affect service but not scaling limits directly.

3. Final Answer:

   The maximum capacity is set equal to the minimum capacity -> Option D

4. Quick Check:

   Max equals min blocks scaling out = The maximum capacity is set equal to the minimum capacity [OK]

Hint: Max capacity must be greater than min capacity to scale out [OK]

Common Mistakes:

• Ignoring max and min capacity settings
• Assuming load balancer affects scaling triggers
• Confusing target CPU with scaling limits

5. You want to configure ECS service auto scaling to keep container count between 3 and 10, scaling based on memory usage targeting 70%. Which configuration is correct?

hard

A. MinCapacity: 10, MaxCapacity: 3, TargetValue: 70, PredefinedMetricType: ECSServiceAverageMemoryUtilization

B. MinCapacity: 3, MaxCapacity: 10, TargetValue: 70, PredefinedMetricType: ECSServiceAverageMemoryUtilization

C. MinCapacity: 3, MaxCapacity: 10, TargetValue: 70, PredefinedMetricType: ECSServiceAverageCPUUtilization

D. MinCapacity: 3, MaxCapacity: 10, TargetValue: 30, PredefinedMetricType: ECSServiceAverageMemoryUtilization

Solution

1. Step 1: Set correct min and max container counts

   MinCapacity must be less than MaxCapacity, so 3 and 10 is valid, 10 and 3 is invalid.

2. Step 2: Use correct metric and target value for memory

   Memory scaling uses ECSServiceAverageMemoryUtilization with target 70% to trigger scaling.

3. Step 3: Verify options

   MinCapacity: 3, MaxCapacity: 10, TargetValue: 70, PredefinedMetricType: ECSServiceAverageMemoryUtilization matches all requirements: correct min/max, target 70, memory metric.

4. Final Answer:

   MinCapacity: 3, MaxCapacity: 10, TargetValue: 70, PredefinedMetricType: ECSServiceAverageMemoryUtilization -> Option B

5. Quick Check:

   Correct min/max and memory target = MinCapacity: 3, MaxCapacity: 10, TargetValue: 70, PredefinedMetricType: ECSServiceAverageMemoryUtilization [OK]

Hint: Min < Max and match metric to resource (memory or CPU) [OK]

Common Mistakes:

• Setting max less than min capacity
• Using CPU metric for memory scaling
• Setting wrong target value for scaling