# Managing data in containers So far we've been introduced to some [basic Docker concepts](/userguide/usingdocker/), seen how to work with [Docker images](/userguide/dockerimages/) as well as learned about [networking and links between containers](/userguide/dockerlinks/). In this section we're going to discuss how you can manage data inside and between your Docker containers. We're going to look at the two primary ways you can manage data in Docker. * Data volumes, and * Data volume containers. ## Data volumes A *data volume* is a specially-designated directory within one or more containers that bypasses the [*Union File System*](/reference/glossary#union-file-system). Data volumes provide several useful features for persistent or shared data: - Volumes are initialized when a container is created. If the container's base image contains data at the specified mount point, that existing data is copied into the new volume upon volume initialization. - Data volumes can be shared and reused among containers. - Changes to a data volume are made directly. - Changes to a data volume will not be included when you update an image. - Data volumes persist even if the container itself is deleted. Data volumes are designed to persist data, independent of the container's life cycle. Docker therefore *never* automatically delete volumes when you remove a container, nor will it "garbage collect" volumes that are no longer referenced by a container. ### Adding a data volume You can add a data volume to a container using the `-v` flag with the `docker create` and `docker run` command. You can use the `-v` multiple times to mount multiple data volumes. Let's mount a single volume now in our web application container. $ docker run -d -P --name web -v /webapp training/webapp python app.py This will create a new volume inside a container at `/webapp`. > **Note:** > You can also use the `VOLUME` instruction in a `Dockerfile` to add one or > more new volumes to any container created from that image. Docker volumes default to mount in read-write mode, but you can also set it to be mounted read-only. $ docker run -d -P --name web -v /opt/webapp:ro training/webapp python app.py ### Locating a volume You can locate the volume on the host by utilizing the 'docker inspect' command. $ docker inspect web The output will provide details on the container configurations including the volumes. The output should look something similar to the following: ... Mounts": [ { "Name": "fac362...80535", "Source": "/var/lib/docker/volumes/fac362...80535/_data", "Destination": "/webapp", "Driver": "local", "Mode": "", "RW": true } ] ... You will notice in the above 'Source' is specifying the location on the host and 'Destination' is specifying the volume location inside the container. `RW` shows if the volume is read/write. ### Mount a host directory as a data volume In addition to creating a volume using the `-v` flag you can also mount a directory from your Docker daemon's host into a container. ``` $ docker run -d -P --name web -v /src/webapp:/opt/webapp training/webapp python app.py ``` This command mounts the host directory, `/src/webapp`, into the container at `/opt/webapp`. If the path `/opt/webapp` already exists inside the container's image, the `/src/webapp` mount overlays but does not remove the pre-existing content. Once the mount is removed, the content is accessible again. This is consistent with the expected behavior of the `mount` command. If you are using Docker Machine on Mac or Windows, your Docker daemon has only limited access to your OS X or Windows filesystem. Docker Machine tries to auto-share your `/Users` (OS X) or `C:\Users` (Windows) directory. So, you can mount files or directories on OS X using. ``` docker run -v /Users/:/ ... ``` On Windows, mount directories using: ``` docker run -v /c/Users/:/ ...` ``` All other paths come from your virtual machine's filesystem. For example, if you are using VirtualBox some other folder available for sharing, you need to do additional work. In the case of VirtualBox you need to make the host folder available as a shared folder in VirtualBox. Then, you can mount it using the Docker `-v` flag. Mounting a host directory can be useful for testing. For example, you can mount source code inside a container. Then, change the source code and see its effect on the application in real time. The directory on the host must be specified as an absolute path and if the directory doesn't exist Docker will automatically create it for you. Docker volumes default to mount in read-write mode, but you can also set it to be mounted read-only. ``` $ docker run -d -P --name web -v /src/webapp:/opt/webapp:ro training/webapp python app.py ``` Here we've mounted the same `/src/webapp` directory but we've added the `ro` option to specify that the mount should be read-only. >**Note**: The host directory is, by its nature, host-dependent. For this >reason, you can't mount a host directory from `Dockerfile` because built images >should be portable. A host directory wouldn't be available on all potential >hosts. ### Mount a host file as a data volume The `-v` flag can also be used to mount a single file - instead of *just* directories - from the host machine. $ docker run --rm -it -v ~/.bash_history:/.bash_history ubuntu /bin/bash This will drop you into a bash shell in a new container, you will have your bash history from the host and when you exit the container, the host will have the history of the commands typed while in the container. > **Note:** > Many tools used to edit files including `vi` and `sed --in-place` may result > in an inode change. Since Docker v1.1.0, this will produce an error such as > "*sed: cannot rename ./sedKdJ9Dy: Device or resource busy*". In the case where > you want to edit the mounted file, it is often easiest to instead mount the > parent directory. ## Creating and mounting a data volume container If you have some persistent data that you want to share between containers, or want to use from non-persistent containers, it's best to create a named Data Volume Container, and then to mount the data from it. Let's create a new named container with a volume to share. While this container doesn't run an application, it reuses the `training/postgres` image so that all containers are using layers in common, saving disk space. $ docker create -v /dbdata --name dbdata training/postgres /bin/true You can then use the `--volumes-from` flag to mount the `/dbdata` volume in another container. $ docker run -d --volumes-from dbdata --name db1 training/postgres And another: $ docker run -d --volumes-from dbdata --name db2 training/postgres In this case, if the `postgres` image contained a directory called `/dbdata` then mounting the volumes from the `dbdata` container hides the `/dbdata` files from the `postgres` image. The result is only the files from the `dbdata` container are visible. You can use multiple `--volumes-from` parameters to bring together multiple data volumes from multiple containers. You can also extend the chain by mounting the volume that came from the `dbdata` container in yet another container via the `db1` or `db2` containers. $ docker run -d --name db3 --volumes-from db1 training/postgres If you remove containers that mount volumes, including the initial `dbdata` container, or the subsequent containers `db1` and `db2`, the volumes will not be deleted. To delete the volume from disk, you must explicitly call `docker rm -v` against the last container with a reference to the volume. This allows you to upgrade, or effectively migrate data volumes between containers. > **Note:** Docker will not warn you when removing a container *without* > providing the `-v` option to delete its volumes. If you remove containers > without using the `-v` option, you may end up with "dangling" volumes; > volumes that are no longer referenced by a container. > Dangling volumes are difficult to get rid of and can take up a large amount > of disk space. We're working on improving volume management and you can check > progress on this in [pull request #14214](https://github.com/docker/docker/pull/14214) ## Backup, restore, or migrate data volumes Another useful function we can perform with volumes is use them for backups, restores or migrations. We do this by using the `--volumes-from` flag to create a new container that mounts that volume, like so: $ docker run --volumes-from dbdata -v $(pwd):/backup ubuntu tar cvf /backup/backup.tar /dbdata Here we've launched a new container and mounted the volume from the `dbdata` container. We've then mounted a local host directory as `/backup`. Finally, we've passed a command that uses `tar` to backup the contents of the `dbdata` volume to a `backup.tar` file inside our `/backup` directory. When the command completes and the container stops we'll be left with a backup of our `dbdata` volume. You could then restore it to the same container, or another that you've made elsewhere. Create a new container. $ docker run -v /dbdata --name dbdata2 ubuntu /bin/bash Then un-tar the backup file in the new container's data volume. $ docker run --volumes-from dbdata2 -v $(pwd):/backup ubuntu cd /dbdata && tar xvf /backup/backup.tar You can use the techniques above to automate backup, migration and restore testing using your preferred tools. # Next steps Now we've learned a bit more about how to use Docker we're going to see how to combine Docker with the services available on [Docker Hub](https://hub.docker.com) including Automated Builds and private repositories. Go to [Working with Docker Hub](/userguide/dockerrepos).