ECS CapacityProviderReservation Triggers Unnecessary EC2 Instance Launch in ASG Despite Low Task Load

Question

I'm currently experiencing an issue where my Auto Scaling Group (ASG) is launching a second EC2 instance automatically, even though only one task is running, and CPU
 consumption is low. I need help understanding why this happens and how I can address it.

### Infrastructure Overview:

- **EC2 Instances**: T3.medium instances.
- **Auto Scaling Group (ASG)**:
  - Minimum: 0
  - Maximum: 3
  - Desired capacity varies depending on scaling policies.
- **ASG Scaling Policies**:
  - Step scaling policy for high and low CPU utilization with alarms set at thresholds.
  - Target tracking policy based on the `CapacityProviderReservation` metric with an 80% threshold.

### ECS Task and Service Configuration:

- **ECS Task Definition**:
  - CPU capacity allocated per task: 1024 CPU units (equivalent to 1 vCPU).
  - The task is configured to scale based on service CPU utilization, with policies set to add more tasks if usage surpasses 80% and scale down if it drops below 20%.
- **ECS Service**:
  - Runs a single task initially and scales based on traffic and CPU utilization.
  - The `CapacityProviderReservation` scaling policy is configured to trigger a scale-up if the reservation surpasses 80%.

### Observations:

1. The ASG launches a second EC2 instance even when the existing instance has only one running task with no significant CPU usage. When I tested my container on an EC2 instance without any scaling, it only consumed 4 CPU units at idle.
2. The ECS service shows CPU utilization spikes reaching 102%, which surpasses the set scale-up threshold (80%). However, this does not align with the actual container workload, which should be low given there is no traffic.

### Key Policies:

- **ASG Step Scaling Policies**:
  - High CPU utilization policy triggers when CPU utilization exceeds 1600 units for a period.
  - Low CPU utilization policy removes instances when CPU falls below 400 units.
- **Target Tracking Policy**:
  - Monitors the `CapacityProviderReservation` metric at an 80% threshold to maintain cluster capacity.

### Question:

Why is the `CapacityProviderReservation` policy consistently triggering the launch of a second EC2 instance even though:
- The task has sufficient CPU capacity (1024 units).
- The actual task CPU usage should be minimal at startup (around 4 units observed).
- Only one task is running, and it doesn't seem to require scaling up the cluster?

I'm looking for guidance on how to interpret the `CapacityProviderReservation` metric behavior correctly and what changes I might need to make to avoid unnecessary scaling actions. Any insights on aligning the scaling behavior with my actual task load would be greatly appreciated.

**What I Tried:**
- Increasing Task CPU Capacity: I configured the task to have a higher CPU capacity (1024 units, equivalent to 1 vCPU) to ensure it would not reach the CPU utilization threshold (80%) too quickly. My aim was to provide the task with ample CPU headroom to handle initial loads without scaling up unnecessarily.

- Monitoring Task Behavior: I observed the task running on a single EC2 instance without load, noting that it only used around 4 CPU units at idle, which is far below the scale-up threshold.

**What I Was Expecting:**
Initially, I expected that only one task would run on a single EC2 instance without triggering additional instance launches unless traffic or CPU utilization significantly increased.

Here are my ASG and ECS scaling policies respectively:
![Enter image description here](/media/postImages/original/IMl_pKreD2TWqhj4Xhq_5nOw)
![Enter image description here](/media/postImages/original/IMdCNuty_PTiG8Kv4Xe8g0uw)

Gary Mclean · Answer

Try setting target capacity to 100

re:Post Agent · Answer

The issue you're experiencing with your Auto Scaling Group (ASG) launching unnecessary EC2 instances despite low task load is likely related to how the CapacityProviderReservation metric works in conjunction with your current configuration. Let's break down the problem and potential solutions:

1. CapacityProviderReservation Metric:
This metric represents the ratio of how much capacity remains in the Auto Scaling group. When the CapacityProviderReservation value is greater than the target capacity (in your case, 80%), it indicates that more tasks are using a higher percentage of the capacity than desired. This triggers the associated CloudWatch alarm to update the DesiredCapacity value for the Auto Scaling group, causing it to launch new EC2 instances.

2. Target Capacity Setting:
Your target capacity is set to 80%, which means ECS aims to keep 20% of the capacity free. With only one task running on a single instance, the system might interpret this as using more than 80% of the available capacity, triggering a scale-out event.

3. Task CPU Allocation vs. Instance Capacity:
You've allocated 1024 CPU units (1 vCPU) to your task, which is a significant portion of a t3.medium instance's capacity (2 vCPUs). Even though the actual usage is low, the reservation is high relative to the instance's total capacity.

4. Minimum Capacity of 0:
Having a minimum capacity of 0 in your ASG can lead to unexpected scaling behavior, as the system might be more aggressive in scaling out to ensure capacity is available.

To address these issues, consider the following adjustments:

1. Adjust Target Capacity: Lower the target capacity in your CapacityProviderReservation policy. For example, try setting it to 100% instead of 80%. This will allow full utilization of an instance before scaling out.

2. Increase Minimum Capacity: Set the minimum capacity of your ASG to 1. This ensures you always have one instance running and may reduce unnecessary scaling actions.

3. Task Right-sizing: Consider reducing the CPU allocation for your task if 1024 units are not necessary. This will allow more efficient use of instance resources.

4. Review Scaling Thresholds: Adjust your CPU utilization thresholds for scaling. The current settings might be too sensitive, causing premature scale-out actions.

5. Use Managed Scaling: If not already enabled, turn on managed scaling for your capacity provider. This allows ECS to manage scale-in and scale-out actions more effectively.

6. Monitor and Adjust: Closely monitor the CapacityProviderReservation metric and your actual resource utilization. Adjust your settings based on observed patterns to find the right balance between responsiveness and efficiency.

By fine-tuning these settings, you should be able to achieve a more stable and efficient scaling behavior that aligns better with your actual task load. Remember that finding the optimal configuration may require some trial and error, so continue monitoring and adjusting as needed.  
**Sources**  
[Automatically manage Amazon ECS capacity with cluster auto scaling - Amazon Elastic Container Service](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/cluster-auto-scaling.html)  
[EC2 Autoscaling group launching more instances than required | AWS re:Post](https://repost.aws/questions/QUwMGMbC7mT4K5gMxr4t-3Ug/ec2-autoscaling-group-launching-more-instances-than-required)  
[Amazon ECS enables easier EC2 capacity management, with managed instance draining | Containers](https://aws.amazon.com/blogs/containers/amazon-ecs-enables-easier-ec2-capacity-management-with-managed-instance-draining/)

ECS CapacityProviderReservation Triggers Unnecessary EC2 Instance Launch in ASG Despite Low Task Load

Infrastructure Overview:

ECS Task and Service Configuration:

Observations:

Key Policies:

Question:

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