Amazon Elastic Container Service
Developer Guide (API Version 2014-11-13)

Using Data Volumes in Tasks

There are several use cases for using data volumes in Amazon ECS task definitions. We give the following guidance, broken down by launch type.

Fargate tasks only support nonpersistent storage volumes. For more information, see Fargate Task Storage.

For EC2 tasks, use data volumes in the following common examples:

  • To provide persistent data volumes for use with a container

  • To define an empty, nonpersistent data volume and mount it on multiple containers

  • To share defined data volumes at different locations on different containers on the same container instance

  • To provide a data volume to your task that is managed by a third-party volume driver

The lifecycle of the volume can be tied to either a specific task or to the lifecycle of a specific container instance.

The following are the types of data volumes that can be used:

  • Docker volumes — A Docker-managed volume that is created under /var/lib/docker/volumes on the container instance. Docker volume drivers (also referred to as plugins) are used to integrate the volumes with external storage systems, such as Amazon EBS. The built-in local volume driver or a third-party volume driver can be used. Docker volumes are only supported when using the EC2 launch type. Windows containers only support the use of the local driver. To use Docker volumes, specify a dockerVolumeConfiguration in your task definition. For more information, see Using volumes.

  • Bind mounts — A file or directory on the host machine is mounted into a container. Bind mount host volumes are supported when using either the EC2 or Fargate launch types. To use bind mount host volumes, specify a host and optional sourcePath value in your task definition. For more information, see Using bind mounts.


Before the release of the Amazon ECS-optimized AMI version 2017.03.a, only file systems that were available when the Docker daemon was started are available to Docker containers. You can use the latest Amazon ECS-optimized AMI to avoid this limitation, or you can upgrade the docker package to the latest version and restart Docker.