- iPython for GIEs has been deprecated as of 16.04. Jupyter replaces it and will be fully incorporated into the upcoming 16.07 release. Reference
- Please see the updated documentation at RTD: https://docs.galaxyproject.org/en/master/admin/interactive_environments.html
These are revolutionary components of Galaxy allowing users to do interactive data processing from within Galaxy. IEs are built as standard Galaxy visualization plugins, however they launch Docker containers and use some additional routing information to connect end users through the Galaxy server, to the Docker images.
There is currently one IE built into Galaxy:
And more on the way
To enable IE's in your Galaxy instance you need to do the following:
- Set interactive_environment_plugins_directory to
- Adjust the config file if needed, for example to set the docker command if Galaxy cannot run sudo-less docker with
- Install the Galaxy IE proxy (you might need set this sym-link first: ln -s /usr/bin/nodejs /usr/bin/node )
$ cd lib/galaxy/web/proxy/js $ npm install $ cd -
If your IE shows up, but you get an error like: "Could not connect to a galaxy instance. Please contact your sysadmin for help with this error", try the following:
- set 'host' to the IP address of your galaxy server in config/galaxy.ini (instead of 127.0.0.1)
- set 'galaxy_url' to
:8080 in the config file (i.e. ipython.ini)
There are some extra considerations with "enterprise" deployments like running docker on a dedicated machine, and having everything under a single /galaxy URL that users will be accessing your services at.
See the Nginx configuration page for more details about how to configure it for the GIEs
Most larger deployments have an apache or nginx proxy sitting in front of Galaxy. To support this, first adjust your galaxy.ini file:
dynamic_proxy_manage=True dynamic_proxy_session_map=database/session_map.sqlite dynamic_proxy_bind_port=8800 dynamic_proxy_bind_ip=0.0.0.0 dynamic_proxy_external_proxy=True dynamic_proxy_prefix=gie_proxy
Make sure to uncomment and take note of the dynamic_proxy_prefix. Then, our apache configuration looks like:
#RewriteEngine on ProxyPass /galaxy/gie_proxy/ipython/api/kernels ws://localhost:8800/galaxy/gie_proxy/ipython/api/kernels ProxyPass /galaxy/gie_proxy http://localhost:8800/galaxy/gie_proxy ProxyPassReverse /galaxy/gie_proxy http://localhost:8800/galaxy/gie_proxy <Location /galaxy> XSendFile on XSendFilePath / </Location> ProxyPass /galaxy http://localhost:8000/galaxy ProxyPassReverse /galaxy http://localhost:8000/galaxy
you'll note that the
dynamic_proxy_prefix is reused here.
There are many reasons to run Interactive Environments on a separated host and not on your webserver, serving Galaxy. This is possible and is used in production at least at the University of Freiburg.
At first you need to configure a second host to be Docker enabled. This can also be a VM. In the following we call this host
glxdk1. You need to start the Docker daemon and bind it to a TCP port, not to a socket which is the default. For example you can start the daemon with:
docker -H 0.0.0.0:4243 -d
On your client, the Galaxy webserver, you can now install a Docker client. This can also be done on older Systems like Sientific-Linux, CentOS 6, which does not have Docker support by default. The client just talks to the Docker daemon on host
glxdk1. You can test your configuration for example by starting busybox from your client on the Docker host with:
docker -H tcp://glxdk1:4243 run -it busybox sh
So far so good :). Now we need to configure Galaxy to use our new Docker host to start the Interactive Environments. For that we need to edit the
ipython.ini to use our custom docker command. An example
ipython.ini file can be found here: https://gist.github.com/bgruening/a8d53b500642b72db358
[main] # Following options are ignored if using the Galaxy dynamic proxy but # are useful if mapping a range of ports for environment consumption. #apache_urls = False #password_auth = False #ssl = False [docker] # Command to execute docker. For example `sudo docker` or `docker-lxc`. command = docker -H tcp://glxdk1:4243 # The docker image name that should be started. image = bgruening/docker-ipython-notebook:dev # Additional arguments that are passed to the `docker run` command. command_inject = --sig-proxy=true # URL to access the Galaxy API with from the spawn Docker containter, if empty # this falls back to galaxy.ini's galaxy_infrastructure_url and finally to the # Docker host of the spawned container if that is also not set. #galaxy_url = # The Docker hostname. It can be useful to run the Docker daemon on a different # host than Galaxy. docker_hostname = glxdk1 docker_galaxy_temp_dir = /var/tmp/glxdk1
Please adopt your
command and the
image as needed.
As next step we need to configure a share mount point between the Docker host and Galaxy. Unfortunately, this can not be a NFS mount. Docker does not like NFS yet. You could for example use a sshfs mount with the following script: https://gist.github.com/bgruening/9601f51ecff3aa209e04
#!/usr/bin/env sh if mount | grep ^glxdk1:/var/tmp/glxdk1; then echo "/var/tmp/glxdk1 already mounted." else sshfs glxdk1:/var/tmp/glxdk1 /var/tmp/glxdk1 echo 'Mounting ...' fi