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https://issues.apache.org/jira/browse/TAVERNA-901?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hewa Vidana Gamage Nadeesh Dilanga updated TAVERNA-901:
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Attachment: Docker Activity Plugin UnitTest User Guide.pdf
Here I am attaching the use guide PDF with screen captures on understanding
docker activity plugin unit test case(which expose the end to end docker
functionality)
> Run Docker from Taverna
> -----------------------
>
> Key: TAVERNA-901
> URL: https://issues.apache.org/jira/browse/TAVERNA-901
> Project: Apache Taverna
> Issue Type: Story
> Components: Taverna Common Activities
> Reporter: Stian Soiland-Reyes
> Labels: docker, gsoc2016, tool, unix, workflow
> Attachments: Docker Activity Plugin UnitTest User Guide.pdf
>
>
> h2. GSOC: Add Docker support to Taverna
> The proposed GSOC project is to add support for invoking Docker containers
> within Taverna by adding a Docker Activity plugin.
> Tasks include:
> * Propose JSON model for describing a {{docker run}} command
> * (Optional) Validate Docker activity config, e.g. can the docker image be
> pulled?
> * Investigate: New Docker activity, or modify existing External Tool activity?
> * Make/modify a Taverna Activity plugin for executing Docker (may or may not
> be based on the External Tool activity)
> * (Optional) Capture docker metadata and add to workflow run provenance (e.g.
> which docker image ID was pulled)
> * (Optional) Add Bioboxes support
> * (Optional) Integrate with CWL support (TAVERNA-900)
> Other Taverna/Docker--related tasks can of course also be proposed by the
> students.
> h2. Docker
> [Docker|https://www.docker.com/] is a Linux container virtualization
> platform. A Linux _container_ is a special kernel feature, which similar to
> _chroot jails_ behave as a separate machine, but unlike Virtual Machines do
> not have the overhead of virtualization of hardware.
> Docker is popular in the _devops_ movement as it provides an easy way to
> install dependencies for software development and deployment, e.g. to run
> servers for mySQL, Apache Solr or node.js.
> In brief a _Docker Image_ contains a virtual Linux file system (e.g. a
> miniature Debian installation). A _Docker Container_ is a particular
> execution of a Docker Image, which typically runs a single process as
> installed within the container, and may have network ports exposed to the
> world, or have parts of the host computer's file system mounted within the
> inner container.
> One great advantage of Docker is that it simplifies tool *installation*, as
> each Docker image is a _self-contained Linux distribution_ which don't have
> to be compatible with the host computer (beyond the kernel).
> For Windows and OS X users Docker automatically manage a virtual machine
> running the Linux containers, but Docker containers can also be deployed on
> the cloud or a local cluster, e,g. using _Docker Machine_.
> Docker images can be created from a {{Dockerfile}}, which basically lists the
> commands to run to prepare the image. Docker images can be chained together
> using _base images_ - for instance to build on an image with mySQL, the
> Dockerfile says {{FROM mysql}}.
> Thus Docker is also an important tool for *reproducibility*, as these images
> can be automatically kept up to date and are distributed through the [Docker
> hub|https://hub.docker.com/]. In bioinformatics, this has led to
> [Bioboxes|http://bioboxes.org/], a standard for creating interchangable
> bioinformatics software containers.
> h2. Taverna
> [Apache Taverna|http://taverna.incubator.apache.org/] (incubating) is a
> Java-based workflow system with a graphical design interface. Taverna
> workflows can combine many different service types, including REST and WSDL
> services, command line tools, scripts (e.g. BeanShell, R) and custom plugins
> (e.g. BioMart).
> Taverna workflows can be executed on the desktop, on the command line, or on
> a Taverna server installation, which can be controlled from a web portal, a
> mobile app, or integrated into third-party applications.
> Taverna is used in a [wide range of
> sciences|http://taverna.incubator.apache.org/introduction/taverna-in-use/]
> for data analysis and processing, including bioinformatics, cheminformatics,
> biodiversity and musicology. Workflow engine features include provenance
> tracking, implicit parallelism/iterations, retry/failover and looping.
> Taverna workflows are commonly shared on
> [myExperiment|http://www.myexperiment.org], and can either be created
> graphically in the [Taverna
> workbench|http://taverna.incubator.apache.org/download/workbench/],
> programmatically using the [Taverna Language
> API|http://taverna.incubator.apache.org/download/language/] or by generating
> workflow definitions in the
> [SCUFL2|http://taverna.incubator.apache.org/documentation/scufl2/] format.
> h2. Community engagement
> Interested GSOC students are requested to engage early with the
> [dev@taverna|http://taverna.incubator.apache.org/community/lists#devtaverna]
> mailing list to describe their ideas for approaching this project, to clarify
> the tasks and for any questions and issues.
> As a first step, the prospective applicant should leave a comment on this
> Jira issue to indicate their interest, and the GSOC mentors would be happy to
> assist on any questions.
> As the project starts we are expecting the student to become part of the
> dev@taverna community to regularly discuss their progress.
> h2. Mentors
> An important part of GSOC is the personal mentoring from existing members of
> the open source community. Our job is not just to teach you how to
> successfully get through the GSOC programme, but also to motivate you and
> make sure you progress. We will show you how to contribute to open source,
> debug, improve, document, test and release your code as part of Apache
> Taverna.
> The GSOC mentors for Apache Taverna have experience from guiding multiple
> earlier GSOC students and local students, and can be contacted privately for
> day-to-day interaction and trouble-shooting.
> Mentors for this GSOC project:
> * Stian Soiland-Reyes
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