This document summarizes a desktop as a service solution called EOSCloud that provides scalable bioinformatics tools on the cloud. EOSCloud is a NERC Big Data project that gives researchers virtual machines with preinstalled bioinformatics software like Biolinux. Researchers are given two VMs - one with Biolinux and one Ubuntu Docker host. The VMs can be boosted to higher capabilities for more intensive tasks, consuming credits only for the boosted time. EOSCloud aims to make infrastructure more efficient and lower barriers to entry for researchers compared to traditional HPC or grid computing. A pilot launch is scheduled for March 31st, 2015 to test with early user communities.

1. Desktop as a Service supporting
Environmental ‘omics
Dr David Wallom
University of Oxford
On behalf of the EOSCloud team

2. Biolinux: A scalable solution
• Comprehensive, free bioinformatics workstation based on
Ubuntu Linux
• 10 years & 8 major releases
• 200+ bioinf packages including big integrative tools :-
QIIME, Galaxy Server, PredictProtein, EMBOSS,
...Incorporates all software
Dual BootLinux Live Local Servers Cloud

3. Why Cloud?
Big e-Infrastructure
Biologist

4. Why Cloud?
• Tools such as Biolinux are community enablers
• Data sets can be too big or restricted to easily move
– move the compute to the data
– Researcher work patterns are maintained
• More efficient use of shared resources
• Central maintenance of infrastructure
• Lower barrier to entry (Compared to traditional HPC
and Grid)

5. JASMIN Infrastructure at RAL
• 10/12/14
Thanks to Philip Kershaw
• <number>

6. JASMIN Infrastructure at RAL
• 10/12/14 • <number>
Thanks to Philip Kershaw

7. EOSCloud
• A NERC Big Data capital project
• Organisationally a tenancy in the Unmanaged Cloud
• Interfaces based on JASMIN IaaS software platform
• ‘Users’ or VMAdmin are registered JASMIN users
– Each receives two VMs
• Biolinux
• Ubuntu Docker hosting environment
– Total responsibility for instantiated system
– Accessible though standard remote desktop tools
• Utilising single scale of resources would be a waste
– Can we scale the users virtual services to take into account demand?

8. Boosting Resource Capabilities
• Users VMs operate in native state ‘Standard’
– Enough capability to access stored data
– Configure applications and workflows
– Free
• User may boost his running VM to increased capability
– Enough to run installed BioLInux analysis applications on useful timescale
– Credit consumption only for Boosted instances
• Reference datasets available to users through shared storage
Name # Core Memory (GB) Cost(Credit/hou
r)
Standard 1 16 0
Standard+ 2 40 1
Big 8 140 4
Max 16 500 8

12. Desktop as a Service for research
• Giving researchers an environment they are confident in by
changing the infrastructure around them
• Creating a new user facility for NERC research communities
• Utilise generic cloud capabilities
– Package would operate on any IaaS Cloud
– Currently using native VMWare interfaces
– Not using platform specific capabilities - no impediment to standards
adoption
• Launch for pilot user communities 31st Mar 2015
– Testing and documentation in final days
– Engaging pilot user communities (e.g. OSD)
• Investigating other key usage models such as teaching or online
learning

13. THANK YOU & QUESTIONS