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Welcome to DEEP-Hybrid-DataCloud releases page

You'll find here useful information regarding the DEEP-HybridDataCloud services and components releases, their schedules, documentation and support.

DEEP-Hybrid-DataCloud releases

.. toctree::
   :maxdepth: 2

   releases/genesis/index.rst


Release repositories

Source Code repositories

Source code repositories are available on GitHub under the indigo-dc and deephdc organizations - http://bit.ly/deep-hdc

Artefacts repositories

DEEP-HDC production (stable) repositories:

YUM & APT configuration files are available here or use the deephdc-release package to install DEEP-HDC repositories

Release schedule

  • Time-based releases
    • projects’ Major releases - the DEEP-HybridDataCloud project foresees two major releases, distributions, during its lifetime, at around 10 months since the start of the project.
  • As-soon-as-available
    • components’ Minor/Revision releases - in a project Major release, Development teams (aka Product Teams) can release updated versions of their components as soon as the DEEP-HDC software quality criteria are met. Thought the project Continuous Integration and Delivery System tests are continuously run giving feedback on the status of the components.

Support Model

  • in a Major Release for each component or service only the latest revision released is supported.
  • for each component or service a (major) release is supported at least for the lifetime of the projects’ major release in which this version was released the first time.

Supported platforms

  • DEEP-HybridDataCloud releases are supported for the following platforms:
    • CentOS7 & Ubuntu 16.04
      • for the products distributed through rpms and deb packages
    • all platforms supporting Docker containers
      • for the products distributed as docker images

Supported artifacts & packaging formats

  • Packages:
    • Binaries: executable packages
    • Sources: when available, package files that contain all of the necessary files to compile/build the respective piece of software
    • Tarballs: clients are distributed as tarballs for all the platforms
  • Containers: Docker images are available for almost all project software