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# Galaxy Interactive Tools
Updated: Apr 6, 2021
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Useful when presenting. --- ### <i class="fas fa-bullseye" aria-hidden="true"></i><span class="visually-hidden">objectives</span> Objectives - Learn the differences between Galaxy Interactive Environments and Galaxy Interactive Tools - Have an understanding of what Galaxy Interactive Tools are and how they work --- # History ## 2015 @hexylena, @bgruening, and @jmchilton create Galaxy Interactive Environments (GIEs) GIEs use Galaxy's *visualization framework* to run certain types of *interactive* visualizations (e.g. Jupyter Notebook) GIEs run in a docker container on the Galaxy server or a single remote Docker server ??? - Galaxy Interactive Environments were added to Galaxy in 2015. - They are a type of visualization in Galaxy. - Accessible through the “Visualize” menu or under the visualization button on a dataset with a specific datatype. - Back then, the docker container serving an interactive environment could not be run on a cluster. - More details within Galaxy Interactive Environment slides. --- # History ## 2016 Support for Docker Swarm is added, allowing running a cluster for GIEs ??? - As of 2016, Docker includes swarm mode for natively managing a cluster of Docker Engines called a swarm. - This allowed to run Galaxy Interactive Environment on a cluster. --- # History ## 2019 @blankenberg creates Galaxy Interactive Tools (GxITs) Building on the GIE concept, but run as *tools* Tools run just as any other Galaxy job (e.g. via Slurm, HTCondor) You will sometimes see Interactive Tools referred to as Interactive Environments version 2 ??? - In 2019, were created the Galaxy Interactive Tools. - Like interactive environment, Galaxy Interactive Tools are built on docker containers and are accessible through the Galaxy interface. - But they are considered as tools. - They are launchable from the toolbox menu, on a predefined destination and prioritized as any other job. --- # Tool config syntax ```xml <tool id="interactive_tool_jupyter_notebook" tool_type="interactive" name="Interactive Jupyter Notebook" version="0.1"> <requirements> <container type="docker">quay.io/bgruening/docker-jupyter-notebook:ie2</container> </requirements> <entry_points> <entry_point name="Jupyter Interactive Tool" requires_domain="True"> <port>8888</port> <url>ipython/lab</url> </entry_point> </entry_points> </tool> ``` ??? - Some settings are needed to configure an interactive tool wrapper. - The tool type must be set to interactive. - As a requirement, set the path to the repository where the container is to be pulled from. - The tool entry point on the container must be defined. - For instance, for a Jupyter Notebook, you'll give the port the application is served on and the domain name suffix. --- # Mapping clients to containers - GIEs: Unique path, e.g. `https://galaxy.example.org/gie-proxy/jupyter/...` - Pros: Works with existing SSL certificate - Cons: Requires Galaxy session cookie (no sharing), can only run one at a time, closing your browser loses your session - GxITs: Unique hostname, e.g. `https://<unique-id>.interactivetoolentrypoint.interactivetool.galaxy.example.org/` - Pros: Needs no special credentials (can be shared) - Cons: Requires *wildcard* DNS entry and *wildcard* SSL certificate (not possible at many sites) ??? - Diverse infrastructures behind Galaxy Interactive Environments and Galaxy Interactive Tools induces various constraints and benefits. - Particularly in building the path between the browser and the container. --- # Anatomy of a running Interactive Tool ![Galaxy Interactive Tools Proxy Diagram](../../images/interactive-tools/gxit-proxy-diagram.png "Galaxy Interactive Tools Proxy Diagram") .reduce70[.footnote[The source for this figure can be found at: https://docs.google.com/presentation/d/1_4PtfM6A4mOxOlgGh6OGWvzFcxD1bdw4CydEWtm5n8k/]] ??? - This slide illustrates the steps allowing a client to interact with a Galaxy Interactive Tool. - We consider a Galaxy server running behind a reverse proxy (NGINX). - The client only ever speaks to NGINX on the Galaxy server, running on the standard HTTPS 443 port. - Based on the elements provided by the URL, NGINX redirects the requests to Galaxy over a unix domain socket as usual. - On the other hand, HTTP requests targetting interactive tools are redirected by NGINX to a proxy, called GIE Proxy, running on port 8000. - At this point, remember, when an docker container starts, it will be assigned a host (server or node) and a random port on that host (in our example, port 32768). - This information is stored by Galaxy in a sqlite database. - So the GIE proxy checks in this sqlite database to know which node and port the IT container is to be found. - The GIE proxy forwards the HTTP request to Docker on that node and port. - Docker, in turn, forwards it to the application (e.g. Jupyter) on the container's port, defined in the wrapper. --- # Galaxy configuration Enable docker on a destination in `job_conf.xml` and assign your GxITs to that destination .left[Set in `galaxy.yml`:] ```yaml interactivetools_enable: true interactivetools_map: /srv/galaxy/var/gie-proxy-sessions.sqlite ``` ??? - A few settings are needed to get interactive tools running within your Galaxy instance. - In your galaxy configuration file, enable the use of interactive tools then set the path to the sqlite database storing the proxying data. - In the job configuration file, give to the tool a destination allowing the use of Docker (more details in the tutorial). --- # Proxy configuration Use the uWSGI proxy configuration that ships with Galaxy Or the [Node.js-based proxy][usegalaxy_eu-gie_proxy] [usegalaxy_eu-gie_proxy]: https://galaxy.ansible.com/usegalaxy_eu/gie_proxy ??? - In production, you are likely to use the Node.js based proxy, set up by the Galaxy admin team. - During developement, you can use the uWSGI proxy configuration used by default by Galaxy. --- # Security The default docker-enabled container exposes all datasets to the tool Normally this isn't bad (normal tools can't be controlled by the user) Interactive tools are fully user controllable Solution: [Embedded Pulsar][job-conf-pulsar-embedded] [job-conf-pulsar-embedded]: https://github.com/galaxyproject/galaxy/blob/6622ad1acb91866febb3d2f229de7cfb8af3a9f6/lib/galaxy/config/sample/job_conf.xml.sample_advanced#L106 ??? - As we have seen, interactive tools are launched in docker containers. - By default in galaxy, each container has full access to all user's data. - This is a security issue since a user could take control of an interactive tool and read, write or delete those data. --- # Embedded Pulsar Runs a [Pulsar][pulsar] server within the Galaxy application to "stage" (i.e. copy) inputs. - Pros: Inputs in isolated dir so only that dir is mounted in the container: secure - Cons: Has to copy inputs on each Interactive Tool execution: slow [pulsar]: https://github.com/galaxyproject/pulsar ??? - A solution to this security issue is to use embedded pulsar. - This way, pulsar makes available only the job input data to the container. - Moreover, these data are read only. - You will have more details in the tutorial. --- ## Thank You! This material is the result of a collaborative work. Thanks to the [Galaxy Training Network](https://training.galaxyproject.org) and all the contributors!
This material is licensed under the Creative Commons Attribution 4.0 International License