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http://bit.ly/bosc2013
github.com:chapmanb/cloudbiolinux.git
config/
puppet/
modules/
lwr
biocloudcentral
apache
.....
...
github.com:bioconfig/puppet-lwr.git
github.com:bioconfig/puppet-biocloudcentral.git
John Chilton1, Pratik Jagtap1, Benjamin Lynch1, Brad Chapman2, Timothy Griffin3
github.com:puppetlabs/puppetlabs-apache.git
They can be easily integrated the same way by institutions or teams with their own Chef or Puppet repositories or by tools such as Globus Provision.
1 University of Minnesota Supercomputing Institute
2 Harvard School of Public Health
3 University of Minnesota
biopython, bioperl, biojava...
Initial Applications
http://github.com/bioconfig/XXXXX
https://lwr.readthedocs.org/
https://github.com/bioconfig/puppet-lwr
Clearing house for high quality
interoperable modules for use with
CloudBioLinux, Globus Provision, or institutional repositories.
The Globus Toolkit provides utilities for federated data transfer, identity management, etc...
https://github.com/bioconfig/chef-globus
http://bit.ly/cbl-gridftp
Django application allowing users to easily launch CloudBioLinux and CloudMan instances
https://github.com/bioconfig/puppet-biocloudcentral
Fabric is a low-level procedural library. Chef & Puppet are DSLs with higher level constructs for services, dependencies, packages, etc...
Built-in easy templating (great for config files).
Puppet/Chef remotely installed as needed, packages are bundled up, shipped to remote server, and applied to server,
Applications broken down into packages
that can be easily shared.
Huge wealth of existing best practice configurations exist.
Can set Puppet and Chef properties via Fabric
Can define what modules/cookbooks configured via new YAML package types.
Great unit testing frameworks available.
Fabric is library used by CBL to remotely
run install commands.
Fabric is great at recreating identical
deployments on multiple machines.
The Problem: Different institutions/teams want to build different environments with applications configured differently.
Configuring complex applications is hard!
Building on open source frameworks can
simplify this task.
CloudBioLinux (& CloudMan) is an example.
bio_nextgen:
- bio-linux-fastqc
- fastx-toolkit
- maq
- plink
bio_proteomics:
- xsltproc
- libxml-sax-expat-perl
- libgd2-xpm-dev
- libbz2-dev
Can be OS packages,
language libraries, or
custom installs
@_if_not_installed("bfast")
def install_bfast(env):
"""BFAST: Blat-like Fast Accurate Search Tool.
http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page
"""
default_version = "0.7.0a"
version = env.get("tool_version", default_version)
major_version_regex = "\d+\.\d+\.\d+"
major_version = re.search(major_version_regex, version).group(0)
url = "http://downloads.sourceforge.net/project/bfast/bfast/%s/bfast-%s.tar.gz"\
% (major_version, version)
_get_install(url, env, _configure_make)