Decrease latency for applications with long boot times using warm pools - Amazon EC2 Auto Scaling
Core conceptsPrerequisitesUpdate the instances in a warm poolRelated resourcesLimitations

Decrease latency for applications with long boot times using warm pools

A warm pool gives you the ability to decrease latency for your applications that have exceptionally long boot times, for example, because instances need to write massive amounts of data to disk. With warm pools, you no longer have to over-provision your Auto Scaling groups to manage latency in order to improve application performance. For more information, see the following blog post Scaling your applications faster with EC2 Auto Scaling Warm Pools.

Important

Creating a warm pool when it's not required can lead to unnecessary costs. If your first boot time does not cause noticeable latency issues for your application, there probably isn't a need for you to use a warm pool.

Topics

Core concepts

Before you get started, familiarize yourself with the following core concepts:

Warm pool

A warm pool is a pool of pre-initialized EC2 instances that sits alongside an Auto Scaling group. Whenever your application needs to scale out, the Auto Scaling group can draw on the warm pool to meet its new desired capacity. This helps you to ensure that instances are ready to quickly start serving application traffic, accelerating the response to a scale-out event. As instances leave the warm pool, they count toward the desired capacity of the group. This is known as a warm start.

While instances are in the warm pool, your scaling policies only scale out if the metric value from instances that are in the InService state is greater than the scaling policy's alarm high threshold (which is the same as the target utilization of a target tracking scaling policy).

Warm pool size

By default, the size of the warm pool is calculated as the difference between the Auto Scaling group's maximum capacity and its desired capacity. For example, if the desired capacity of your Auto Scaling group is 6 and the maximum capacity is 10, the size of your warm pool will be 4 when you first set up the warm pool and the pool is initializing.

To specify the warm pool's maximum capacity separately, use the custom specification (MaxGroupPreparedCapacity) option and set a custom value for it that is greater than the current capacity of the group. If you provide a custom value, the size of the warm pool is calculated as the difference between the custom value and the current desired capacity of the group. For example, if the desired capacity of your Auto Scaling group is 6, if the maximum capacity is 20, and if the custom value is 8, the size of your warm pool will be 2 when you first set up the warm pool and the pool is initializing.

You might only need to use the custom specification (MaxGroupPreparedCapacity) option when working with large Auto Scaling groups to manage the cost benefits of having a warm pool. For example, an Auto Scaling group with 1,000 instances, a maximum capacity of 1,500 (to provide extra capacity for emergency traffic spikes), and a warm pool of 100 instances might help you achieve your goals better than keeping 500 instances reserved for future use inside the warm pool.

Minimum warm pool size

Consider using the minimum size setting (MinSize) to statically set the minimum number of instances to maintain in the warm pool. There is no minimum size set by default. The MinSize setting is useful when you specify MaxGroupPreparedCapacity to ensure that a minimum number of instances are maintained in the warm pool even when the desired capacity of the Auto Scaling group is higher than the MaxGroupPreparedCapacity.

Warm pool instance state

You can keep instances in the warm pool in one of three states: Stopped, Running, or Hibernated. Keeping instances in a Stopped state is an effective way to minimize costs. With stopped instances, you pay only for the volumes that you use and the Elastic IP addresses attached to the instances.

Alternatively, you can keep instances in a Hibernated state to stop instances without deleting their memory contents (RAM). When an instance is hibernated, this signals the operating system to save the contents of your RAM to your Amazon EBS root volume. When the instance is started again, the root volume is restored to its previous state and the RAM contents are reloaded. While the instances are in hibernation, you pay only for the EBS volumes, including storage for the RAM contents, and the Elastic IP addresses attached to the instances.

Keeping instances in a Running state inside the warm pool is also possible, but is highly discouraged to avoid incurring unnecessary charges. When instances are stopped or hibernated, you are saving the cost of the instances themselves. You pay for the instances only when they are running.

Lifecycle hooks

You use lifecycle hooks to put instances into a wait state so that you can perform custom actions on the instances. Custom actions are performed as the instances launch or before they terminate.

In a warm pool configuration, lifecycle hooks delay instances from being stopped or hibernated and from being put in service during a scale-out event until they have finished initializing. If you add a warm pool to your Auto Scaling group without a lifecycle hook, instances that take a long time to finish initializing could be stopped or hibernated and then put in service during a scale-out event before they are ready.

Instance reuse policy

By default, Amazon EC2 Auto Scaling terminates your instances when your Auto Scaling group scales in. Then, it launches new instances into the warm pool to replace the instances that were terminated.

If you want to return instances to the warm pool instead, you can specify an instance reuse policy. This lets you reuse instances that are already configured to serve application traffic. To make sure that your warm pool is not over-provisioned, Amazon EC2 Auto Scaling can terminate instances in the warm pool to reduce its size when it is larger than necessary based on its settings. When terminating instances in the warm pool, it uses the default termination policy to choose which instances to terminate first.

Important

If you want to hibernate instances on scale in and there are existing instances in the Auto Scaling group, they must meet the requirements for instance hibernation. If they don't, when instances return to the warm pool, they will fallback to being stopped instead of being hibernated.

Note

Currently, you can only specify an instance reuse policy by using the AWS CLI or an SDK. This feature is not available from the console.

Prerequisites

Before you create a warm pool for your Auto Scaling group, decide how you will use lifecycle hooks to initialize new instances with an appropriate initial state.

To perform custom actions on instances while they are in a wait state due to a lifecycle hook, you have two options:

  • For simple scenarios where you want to run commands on your instances at launch, you can include a user data script when you create a launch template or launch configuration for your Auto Scaling group. User data scripts are just normal shell scripts or cloud-init directives that are run by cloud-init when your instances start. The script can also control when your instances transition to the next state by using the ID of the instance on which it runs. If you are not doing so already, update your script to retrieve the instance ID of the instance from the instance metadata. For more information, see Retrieve instance metadata in the Amazon EC2 User Guide.

    Tip

    To run user data scripts when an instance restarts, the user data must be in the MIME multi-part format and specify the following in the #cloud-config section of the user data:

    #cloud-config
cloud_final_modules:
 - [scripts-user, always]

  • For advanced scenarios where you need a service such as AWS Lambda to do something as instances are entering or leaving the warm pool, you can create a lifecycle hook for your Auto Scaling group and configure the target service to perform custom actions based on lifecycle notifications. For more information, see Supported notification targets.

Prepare instances for hibernation

To prepare Auto Scaling instances to use the Hibernated pool state, create a new launch template or launch configuration that is set up correctly to support instance hibernation, as described in the Hibernation prerequisites topic in the Amazon EC2 User Guide. Then, associate the new launch template or launch configuration with the Auto Scaling group and start an instance refresh to replace the instances associated with a previous launch template or launch configuration. For more information, see Use an instance refresh to update instances in an Auto Scaling group.

Update the instances in a warm pool

To update the instances in a warm pool, you create a new launch template or launch configuration and associate it with the Auto Scaling group. Any new instances are launched using the new AMI and other updates that are specified in the launch template or launch configuration, but existing instances are not affected.

To force replacement warm pool instances to launch that use the new launch template or launch configuration, you can start an instance refresh to do a rolling update of your group. An instance refresh first replaces InService instances. Then it replaces instances in the warm pool. For more information, see Use an instance refresh to update instances in an Auto Scaling group.

You can visit our GitHub repository for examples of lifecycle hooks for warm pools.

Limitations

  • You can't add a warm pool to an Auto Scaling group that has a mixed instances policy. You also can't add a warm pool to an Auto Scaling group that has launch template or launch configuration that requests Spot Instances.

  • Amazon EC2 Auto Scaling can put an instance in a Stopped or Hibernated state only if it has an Amazon EBS volume as its root device. Instances that use instance stores for the root device cannot be stopped or hibernated.

  • Amazon EC2 Auto Scaling can put an instance in a Hibernated state only if meets all of the requirements listed in the Hibernation prerequisites topic in the Amazon EC2 User Guide.

  • If your warm pool is depleted when there is a scale-out event, instances will launch directly into the Auto Scaling group (a cold start). You could also experience cold starts if an Availability Zone is out of capacity.

  • If an instance within the warm pool encounters an issue during the launch process, preventing it from reaching the InService state, the instance will be considered a failed launch and terminated. This applies regardless of the underlying cause, such as an insufficient capacity error or any other factor.

  • If you try using a warm pool with an Amazon Elastic Kubernetes Service (Amazon EKS) managed node group, instances that are still initializing might register with your Amazon EKS cluster. As a result, the cluster might schedule jobs on an instance as it is preparing to be stopped or hibernated.

  • Likewise, if you try using a warm pool with an Amazon ECS cluster, instances might register with the cluster before they finish initializing. To solve this problem, you must configure a launch template or launch configuration that includes a special agent configuration variable in the user data. For more information, see Using a warm pool for your Auto Scaling group in the Amazon Elastic Container Service Developer Guide.

  • Hibernation support for warm pools is available in all commercial AWS Regions where Amazon EC2 Auto Scaling and hibernation are available, except the following:

    • Asia Pacific (Hyderabad)

    • Asia Pacific (Melbourne)

    • Canada West (Calgary)

    • China (Beijing) Region

    • China (Ningxia) Region

    • Europe (Spain)

    • Israel (Tel Aviv)