Create a pool
This article describes how to create a pool using the UI. To learn how to use the Databricks CLI to create a pool, see Instance Pools CLI. To learn how to use the REST API to create a pool, see the Instance Pools API.
You must have permission to create a pool; see Pool access control.
Create a pool using the UI
To create a pool using the UI:
Click Compute in the sidebar.
Click the Pools tab.
Click the Create Pool button.
Specify the pool configuration.
Click the Create button.
Attach a cluster to a pool
To attach a cluster to a pool using the cluster creation UI, select the pool from the Driver Type or Worker Type dropdown when you configure the cluster. Available pools are listed at the top of each dropdown list. You can use the same pool or different pools for the driver node and worker nodes.
If you use the Clusters API, you must specify
driver_instance_pool_id for the driver node and
instance_pool_id for the worker nodes.
Pool size and auto termination
When you create a pool, in order to control its size, you can set three parameters: minimum idle instances, maximum capacity, and idle instance auto termination.
Minimum Idle Instances
The minimum number of instances the pool keeps idle. These instances do not terminate, regardless of the auto termination settings. If a cluster consumes idle instances from the pool, Databricks provisions additional instances to maintain the minimum.
The maximum number of instances the pool can provision. If set, this value constrains all instances (idle + used). If a cluster using the pool requests more instances than this number during autoscaling, the request fails with an
This configuration is optional. Databricks recommend setting a value only in the following circumstances:
You have an instance quota you must stay under.
You want to protect one set of work from impacting another set of work. For example, suppose your instance quota is 100 and you have teams A and B that need to run jobs. You can create pool A with a max 50 and pool B with max 50 so that the two teams share the 100 quota fairly.
You need to cap cost.
A pool consists of both idle instances kept ready for new clusters and instances in use by running clusters. All of these instances are of the same instance provider type, selected when creating a pool.
A pool’s instance type cannot be edited. Clusters attached to a pool use the same instance type for the driver and worker nodes. Different families of instance types fit different use cases, such as memory-intensive or compute-intensive workloads.
Databricks always provides one year’s deprecation notice before ceasing support for an instance type.
Preloaded Databricks Runtime version
You can speed up cluster launches by selecting a Databricks Runtime version to be loaded on idle instances in the pool. If a user selects that runtime when they create a cluster backed by the pool, that cluster will launch even more quickly than a pool-backed cluster that doesn’t use a preloaded Databricks Runtime version.
Setting this option to None slows down cluster launches, as it causes the Databricks Runtime version to download on demand to idle instances in the pool. When the cluster releases the instances in the pool, the Databricks Runtime version remains cached on those instances. The next cluster creation operation that uses the same Databricks Runtime version might benefit from this caching behavior, but it is not guaranteed.
Delete a pool
Deleting a pool terminates the pool’s idle instances and removes its configuration. To delete a pool, click the icon in the actions on the Pools page. If you delete a pool:
Running clusters attached to the pool continue to run, but cannot allocate instances during resize or up-scaling.
Terminated clusters attached to the pool will fail to start.
You cannot undo this action.