# Service-managed fleets
A service-managed fleet (SMF) is a fleet of workers that have default settings provided by Deadline Cloud. These default settings are designed to be efficient and cost-effective.
Some of the default settings limit the amount of time that workers and tasks can run. A worker can only run for seven days and a task can only run for five days. When the limit is reached, the task or worker stops. If this happens, you might lose work that worker or task was running. To avoid this, monitor your workers and tasks to ensure they don't exceed the maximum duration limits. To learn more about monitoring your workers, see [Using the Deadline Cloud monitor](working-with-deadline-monitor.md).
## Create a service-managed fleet
There are 3 types of instance options you can choose for your service-managed fleet; spot, on-demand, and wait-and-save. Spot instances are unreserved capacity that you can use at a discounted price, but might be interrupted by on-demand requests. On-demand instances are priced by the second, have no long-term commitment, and will not be interrupted. Wait-and-save provides delayed job scheduling for reduced cost and can be interrupted by on-demand and spot requests.
1. From the [Deadline Cloud console](https://console.aws.amazon.com/deadlinecloud/home), navigate to the farm you want to create the fleet in.
1. Select the **Fleets** tab, and then choose **Create fleet**.
1. Enter a **Name** for your fleet.
1. (Optional) Enter a **Description**. A clear description can help you quickly identify your fleet's purpose.
1. Select **Service-managed** fleet type.
1. Choose the **Spot**, **On-demand**, or **Wait and Save** instance market option for your fleet. By default, fleets use the Spot option.
1. For service access for your fleet, select an existing role or create a new role. A service role provides credentials to instances in the fleet, granting them permission to process jobs, and to users in the monitor so that they can read log information.
1. Choose **Next**.
1. Choose between CPU only instances or GPU accelerated instances. GPU accelerated instances may be able to process your jobs faster, but can be more expensive.
1. Select the operating system for your workers. You can leave the default, **Linux** or choose **Windows**.
1. (Optional) If you selected GPU accelerated instances, set the maximum and minimum number of GPUs in each instance. For testing purposes you are limited to one GPU. To request more for your production workloads, see [Requesting a quota increase](https://docs.aws.amazon.com/servicequotas/latest/userguide/request-quota-increase.html) in the *Service Quotas User Guide*.
1. Enter the minimum and maximum **vCPUs** that you require for you fleet.
1. Enter the minimum and maximum **memory** that you require for you fleet.
1. (Optional) You can choose to allow or exclude specific instance types from your fleet to ensure only those instance types are used for this fleet.
1. (Optional) Set the maximum number of instances to scale the fleet so that capacity is available for the jobs in the queue. We recommend that you leave the minimum number of instances at **0** to ensure the fleet releases all instances when no jobs are queued.
1. (Optional) You can specify the size of the Amazon Elastic Block Store (Amazon EBS) gp3 volume that will be attached to the workers in this fleet. For more information, see the [ EBS user guide](https://docs.aws.amazon.com/ebs/latest/userguide/general-purpose.html#gp3-ebs-volume-type).
1. Choose **Next**.
1. (Optional) Define custom worker capabilities that define features of this fleet that can be combined with custom host capabilities specified on job submissions. One example is a particular license type if you plan to connect your fleet to your own license server.
1. Choose **Next**.
1. (Optional) To associate your fleet with a queue, select a **queue** from the dropdown. If the queue is set up with the default conda queue environment, your fleet is automatically provided with packages that support partner DCC applications and renderers. For a list of provided packages, see [Default conda queue environment](create-queue-environment.md#conda-queue-environment).
1. Choose **Next**.
1. (Optional) To add a tag to your fleet, choose **Add new tag**, and then enter the **key** and **value** for that tag.
1. Choose **Next**.
1. Review your fleet settings, and then choose **Create fleet**.