Galaxy on Academic Research Clouds
You should do this.
By Dave Clements, Marco Antonio Tangaro, Federico Zambelli, Nikolay Aleksandrov Vazov
One of the reasons we launched the Galaxy Platforms Directory last year was to better highlight the many ways in which researchers can use Galaxy, and not only public servers, which we have emphasized for years, but also containers, virtual machines, commercial clouds, and academic clouds.
This post covers why you might want to consider running Galaxy on an academic clouds.
Academic Research Clouds are compute clouds that are available to researchers in particular geographies or who belong to particular consortia. Compute clouds are dynamically scalable, on-demand compute infrastructures on which you can launch servers like Galaxy when you need them, scale them up and down to meet your fluctuating needs, and then shut them down when you are done. Someone else manages the actual hardwarecluster management. Commercial Clouds also have these properties, except for one key factor ...
Academic Clouds are Often Free to Researchers.
That's right, free. You will need to apply for an allocation but these organizations exist to help researchers like you and are eager to help you use their resources.
After all, the usegalaxy.* servers, and the 100+ other public servers are all free too, and I don't have to do any work to set them up.
All those public servers are shared resources. While some of them are big, you are sharing them with the entire world. There is no way to predict on any given day (or week) if the server(s) you want to use will be zippy or really busy. If you set up your own server, then only people you give access to it will be using it. And since it's a cloud, you may also be able to make it dynamically scalable so it expands and shrinks depending on loads.
Some of the public servers have large quotas - usegalaxy.org has a 250GB quota with an account. However, if you are doing a large scale experiment you'll find that you can easily burn through even a generous quota in no time. With cloud servers you decide how much resource you'll want to set up and then you can use all of it.
All of the academic cloud providers described here have preconfigured Galaxy images that you can bring up on their cloud with varying capacities. You don't need to figure out what disk to buy or how to set up cluster management software. All that is taken care of by the cloud provider.
Many cloud providers enable admin access to your Galaxy instance. This means you can customize the tools and genomes that are available on it.
If you need something, you can add it.
Where can I get Galaxy on an academic cloud? Here are the academic cloud providers we know about (as of 2019) and who they support.
Laniakea@ReCaS is the pilot deployment of Laniakea. Laniakea is a software suite designed to allow academic clouds to add a Galaxy on-demand service to their portfolio easily. It is based on the modular and flexible INDIGO-DataCloud middleware solution for e-science. This first instance of Laniakea, based at ReCaS-Bari, is undergoing beta testing right now and is foreseen to switch to production phase by June 2019. Laniakea@ReCaS has already received more beta-test account requests then the ones available for this initial phase. However, the number of available beta-test user slots will be gradually increased during the first half of 2019; anyone is for now welcome to apply and enroll to become a new beta tester. The standard resource package granted to beta accounts includes 14 CPUs, 28 GBs of RAM and 500 GBs of storage.
Laniakea features include: full admin access (so Galaxy instances are fully customizable), dynamic scalability, a set of pre-configured Galaxy flavors with an extensive set of tools and workflows for RNA-Seq, variants calling, somatic variants calling and ChIP-Seq data analysis, and an encryption layer for users that need to process sensitive human data (or very jealous of their datasets!). Once in the production phase, Laniakea@ReCaS will be an ELIXIR-IT service available to Italian and European researchers through a program similar to the HPC@CINECA one, that already provides HPC resources to Italian life science researchers since 2016. The details of the program will be available soon.
You can have a better look at Laniakea watching this video demo.
For info and beta-tester account applications: email@example.com
Swedish researchers have two local choices for running Galaxy on academic clouds.
The Lifeportal is a Galaxy instance to satisfy the computational needs of the Norwegian research community in life sciences but also of any other user willing to use the service. We would definitely prefer a collaboration between local and external users/groups as collaborating groups get allocated more resources than unique independent users.
Norwegian academic users log in via a national academic provider FEIDE. All other users may select Facebook, Twitter or Linkedin to log in. A real email address is compulsory for feedback and job-reports management. All login methods use Xauth (OpenIDC). All users receive 200 hrs CPU time at first login. FEIDE users can then apply for a project within Lifeportal, up to 20 000 hrs. The applications are considered immediately and resources are allocated within minutes by a routine which is implemented within Lifeportal (Galaxy). All other users may write to firstname.lastname@example.org and their applications will be considered by our committee. If approved, they will be given access to common projects with larger resource allocations. Every user with their own project in Lifeportal can manage it through the menus built in the Galaxy GUI.
Here are the slides with a detailed description of the login procedure.
Our instance, called Lifeportal, implements about 400 applications. It runs Galaxy version 18.09 and jobs are executed on the Abel cluster (~650 nodes) using the slurm-drmaa library.
We have tailored our application set to run either locally, or on the cluster with regard to the requested resources for the job. Resources (memory, walltime, number of tasks, number of cpus) are allocated on a per job basis which gives an exceptional flexibility to use and save requested resources. The instance is among the few in the world implementing a resource allocation management system plugged into Galaxy (and Galaxy GUI) which reserves, charges and refunds the user accounts after each executed job.
Really, if you want your own Galaxy, and you want someone else to deal with the implementation then academic research clouds are your friend.
See you in the cloud,