Amazon EC2 container instances for Amazon ECS
An Amazon ECS container instance is an Amazon EC2 instance that run the Amazon ECS container agent and is registered to a cluster. When you run tasks with Amazon ECS using the EC2 launch type, External launch type or an Auto Scaling group capacity provider, your tasks are placed on your active container instances. You are responsible for the container instance management and maintenance.
Although you can create your own Amazon EC2 instance AMI that meets the basic specifications needed to run your containerized workloads on Amazon ECS, the Amazon ECS-optimized AMIs are preconfigured and tested on Amazon ECS by AWS engineers. It is the simplest way for you to get started and to get your containers running on AWS quickly.
When you create a cluster using the console, Amazon ECS creates a launch template for your instances with the latest AMI associated with the selected operating system.
When you use AWS CloudFormation to create a cluster, the SSM parameter is part of the Amazon EC2 launch template for the Auto Scaling group instances. You can configure the template to use a dynamic Systems Manager parameter to determine what Amazon ECS Optimized AMI to deploy. This parameter ensures that each time you deploy the stack it will check to see if there is available update that needs to be applied to the EC2 instances. For an example of how to use the Systems Manager parameter, see Create an Amazon ECS cluster with the Amazon ECS-optimized Amazon Linux 2023 AMI in the AWS CloudFormation User Guide.
You can choose from the instance types that are compatible with your application. With larger instances, you can launch more tasks at the same time. With smaller instances, you can scale out in a more fine-grained way to save costs. You don't need to choose a single Amazon EC2 instance type that to fit all the applications in your cluster. Instead, you can create multiple Auto Scaling groups where each group has a different instance type. Then, you can create an Amazon EC2 capacity provider for each one of these groups.
Use the following guidelines to determine the instance family types and instance type to use:
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Eliminate the instance types or instance families that don't meet the specific requirements of your application. For example, if your application requires a GPU, you can exclude any instance types that don't have a GPU.
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Consider requirements including network throughput and storage.
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Consider the CPU and memory. As a general rule, the CPU and memory must be large enough to hold at least one replica of the task that you want to run.
Spot Instances
Spot capacity can provide significant cost savings over on-demand instances. Spot capacity is excess capacity that's priced significantly lower than on-demand or reserved capacity. Spot capacity is suitable for batch processing and machine-learning workloads, and development and staging environments. More generally, it's suitable for any workload that tolerates temporary downtime.
Understand that the following consequences because Spot capacity might not be available all the time.
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During periods of extremely high demand, Spot capacity might be unavailable. This can cause Amazon EC2 Spot instance launches to be delayed. In these events, Amazon ECS services retry launching tasks, and Amazon EC2 Auto Scaling groups also retry launching instances, until the required capacity becomes available. Amazon EC2 doesn't replace Spot capacity with on-demand capacity.
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When the overall demand for capacity increases, Spot Instances and tasks might be terminated with only a two-minute warning. After the warning is sent, tasks should begin an orderly shutdown if necessary before the instance is fully terminated. This helps minimize the possibility of errors. For more information about a graceful shutdown, see Graceful shutdowns with ECS
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To help minimize Spot capacity shortages, consider the following recommendations:
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Use multiple Regions and Availability Zones - Spot capacity varies by Region and Availability Zone. You can improve Spot availability by running your workloads in multiple Regions and Availability Zones. If possible, specify subnets in all the Availability Zones in the Regions where you run your tasks and instances.
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Use multiple Amazon EC2 instance types - When you use Mixed Instance Policies with Amazon EC2 Auto Scaling, multiple instance types are launched into your Auto Scaling Group. This ensures that a request for Spot capacity can be fulfilled when needed. To maximize reliability and minimize complexity, use instance types with roughly the same amount of CPU and memory in your Mixed Instances Policy. These instances can be from a different generation, or variants of the same base instance type. Note that they might come with additional features that you might not require. An example of such a list could include m4.large, m5.large, m5a.large, m5d.large, m5n.large, m5dn.large, and m5ad.large. For more information, see Auto Scaling groups with multiple instance types and purchase options in the Amazon EC2 Auto Scaling User Guide.
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Use the capacity-optimized Spot allocation strategy - With Amazon EC2 Spot, you can choose between the capacity- and cost-optimized allocation strategies. If you choose the capacity-optimized strategy when launching a new instance, Amazon EC2 Spot selects the instance type with the greatest availability in the selected Availability Zone. This helps reduce the possibility that the instance is terminated soon after it launches.
For information about how to configure spot termination notices on your container instances, see:
