iPlant Atmosphere: A Gateway to Cloud Infrastructure for
the Plant Sciences
Edwin Skidmore
Seung-jin Kim
Sangeeta Kuchimanchi
iPlant Collaborative
[email protected]
iPlant Collaborative
[email protected]
iPlant Collaborative
[email protected]
Sriramu Singaram
Nirav Merchant
Dan Stanzione
iPlant Collaborative
[email protected]
University of Arizona
[email protected]
Texas Advanced Computing Center
[email protected]
ABSTRACT
Keywords
The cloud platform complements traditional compute and storage
infrastructures by introducing capabilities for efficiently
provisioning resources in a self-service, on-demand manner. The
new provisioning model promises to accelerate scientific
discovery by improving access to customizable and task-specific
computing resources. This paradigm is well-suited, especially for
those applications tailored to leverage cloud-style of infrastructure
capabilities.
cloud, cloud computing, cloud storage, virtualization, plant
sciences, cyberinfrastructure
Adoption of the cloud model has been challenging for many
domain scientists and scientific software developers due to the
technical expertise required to effectively utilize this
infrastructure. Some of the key limitations of cloud infrastructure
are: limited integration with institutional authentication and
authorization frameworks, lack of frameworks to enable domainspecific configurations for instances, and integration with
scientific data repositories alongside existing computational
clusters and grid deployments. Specifically designed to address
some of these operational barriers towards adoptions by the plant
sciences community, the iPlant Collaborative cloud platform,
aptly named Atmosphere, is an open-source, robust, configurable
gateway that extends established cloud infrastructure to meet the
diverse computing needs for the plant science.
Atmosphere manages the Virtual Machine (VM) lifecycle while
maximizing the utilization of cloud resources for scientific
workflows. Thus, Atmosphere allows researchers developing
novel analytical tools to deploy them with ease while abstracting
the underlying computing infrastructure, at the same time making
it relatively easy for the users to access these tools via web
browser. Atmosphere also provides a rich extensible Application
Programming Interface (APIs) for integration and automation
with other services. Since its launch, Atmosphere has seen a wide
adoption by the plant sciences community for a broad array of
applications that range from image processing to next generation
sequence (NGS) analysis and can serve as a template for
providing similar capabilities to other domains.
Categories and Subject Descriptors
C.2.4 [Distributed Systems]: Distributed Applications – cloud
computing and storage.
General Terms
Management, Experimentation, Performance
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1. INTRODUCTION
The iPlant Collaborative was established with a very broad
mandate from the National Science Foundation (NSF) to support
the cyberinfrastructure (CI) needs of researchers addressing the
“grand challenges” of plant biology [1]. Plant biology itself is a
very diverse field. The rapid expansion of the –omics era
(genomics, proteomics, metabolomics, transcriptomics, etc.) is
transforming what has traditionally been a bench- and field-based
research discipline into a computationally intense, data-driven
area of science.
The research problems of plant biology range from those
requiring intense computation (genome assembly, genome wide
association studies) to those requiring little computation but
intensive data integration (genome and functional annotations).
The data sets range in scale and type from molecular phenotype to
satellite maps of species’ range, with most scales falling
somewhere in between. In most areas of inquiry around plants, the
algorithms and workflows are still rapidly evolving, as are the
types of questions being explored. The entire cyberinfrastructure
foundation, therefore, must support the needs of a diverse group
of plant science researchers, ranging from biologists to computer
scientists. The iPlant Collaborative cyberinfrastructure comprises
of high performance computing (HPC) cluster and data storage
resources to the support large-scale data and computational needs
of plant science research. While the HPC cluster and storage
resources are suitable for many applications, not all scientific
computations require the use of supercomputer-scale resources
[2]. Some computational workflows require a dedicated server to
provide their own interfaces, some of which are web based or
native operating system based graphical user interfaces (GUI)
with associated local databases, or compute environments.
Furthermore, the nature of algorithm development and data
analyses as applied to plant biology domain requires customized
software development environments with significant software
version dependencies, while requiring simultaneous access to
large-scale compute and storage infrastructures.
Many existing plant science-related computational tools are a
natural fit for the cloud based infrastructure, many of which are
highly serial or data parallel. Traditionally, such tools have been
designed for single-threaded, small-scale computations, easily
executed on a single workstation.
Large-scale compute
environments typically discourage the execution of these types of
tools, as they do not make efficient use of cluster resources.
Additionally, large shared clusters are not always amenable to
customized execution environments for the domain-specific tasks,
such as configuring a wide range of system library versions to
support legacy versions of applications, or the latest “bleeding
edge” versions of bioinformatics software [3]. The deployment of
algorithms and tools thus becomes a challenge in shared
computing environments.
Atmosphere addresses these issues by providing preconfigured,
domain-specific virtual instances of common bioinformatic tools
that are integrated within other parts of iPlant's
cyberinfrastructure. In this manner, Atmosphere users are able to
quickly develop algorithms and deploy workflows, thereby
reducing the extensive time, resources, and overhead needed to set
up analyses. Users can access the subset of data required by a
specific analysis from iPlant’s large-scale storage by staging the
data into their virtual machine (VM). In addition, users are able to
preserve the state of their VM instances, saving not only a specific
workflow and analysis but an entire system state, introducing new
opportunities for algorithm development and experimental
reproducibility.
A fundamental practice within biosciences research, particularly
in the plant sciences community, is the sharing of data sets,
analysis tools, and computational workflows. Tool developers
have their own community of collaborators and often seek
convenient access to computational resources in order to provide
early and reliable access to the analytical tools for their
community. This iterative step is often a tedious limitation for
biologists, as the data and resource provisioning to validate the
tools is a time consuming process. While many cloud solutions
focus on the Infrastructure-as-a-Service (IAAS) or Platform-as-aService (PAAS) model, Atmosphere reinforces the Software-as-aService (SAAS) approach by allowing users to collaborate, share
their images, and conveniently launch applications using one-click
buttons. SAAS allows the tool developers to provide web-based,
secure single click access to their collaborators to precisely
configured versions of the application and their dependencies,
allowing them to provide quick assessment and feedback before
publishing the tool for public consumption. This capability also
allows the biologists to adjust the underlying computational
infrastructure and modify items such as the number of cores and
RAM depending on the size of the data set being analyzed,
without having to encumber the developer for additional
resources.
Virtualization software typically exists at a low level of most
infrastructures and requires proficient systems administrators to
provision resources for end-users. The nature of virtualization
and the provisioning of virtual resources often demand an intimate
knowledge of underlying physical resources and the low level
access controls. Additionally, the user interfaces for virtualization
software are typically command-line tools or, at best, desktop
applications requiring direct access to the systems and hardware.
Many academic and open-source cloud projects began in an
attempt to fulfill an unmet need to provide the dynamic, usercentric provisioning of virtual resources. Some projects began as
research projects and have continued as open-source projects,
such as OpenNebula [7]. Other projects have attempted to model
themselves after successful private industry services. One such
project is Eucalyptus Cloud [8], which provides API-compatible
web services to Amazon Elastic Compute Cloud (EC2) [9] and a
very basic web interface to managing VMs and storage resources.
Other projects aim to be more of a toolkit or API to service, such
as Nimbus [10] and OpenStack [11]. Most of these projects cater
more toward service providers who wish to build a cloud rather
than delivering the cloud more directly to the end-users
themselves. A major distinction between Atmosphere and these
other projects is that Atmosphere attempts to close the usability
gap between a cloud provider and that of cloud users, particularly
for biologists and plant science researchers.
3. ARCHITECTURE
Conceptually, Atmosphere can be separated into three logical
layers accompanied by a set of toolkits which reside within the
virtual machine (VMs) (see Figure 1). The three layers of
Atmosphere are the cloud engine, the middleware, and the web
frontend. The toolkits facilitate the configuration of the virtual
machines, communication with the middleware tier, and the
interfacing with other parts of iPlant’s cyberinfrastructure.
In addition to the various cloud service models that Atmosphere
supports, the iPlant cloud services platform exposes its
functionality by providing HTTP-based application programming
interfaces (APIs) through its middleware. The APIs enable
functionality available through the web front end as well as
mechanisms to customize notifications, resource management,
and metadata management. The purpose of the Atmosphere APIs
is to encourage deeper integration with other applications and
services while making Atmosphere a first-class citizen of the
institutional infrastructure through the integration capabilities.
2. RELATED WORK
Before the inception of Atmosphere in 2010, there were few
mature open-source cloud-centric middleware or portal projects
focused toward a biological sciences community. Below are some
of the projects that iPlant evaluated before developing a targeted
cloud infrastructure for the plant science community.
Many IAAS clouds utilize virtualization software, such asXen [4],
VMWare [5], or Kernel Virtual Machine (KVM) [6].
Figure 1. High-level illustration of Atmosphere’s components.
3.1 Cloud Engine
Atmosphere’s design planned for the interchange of multiple
cloud types and cloud engines. Currently, Atmosphere supports
Eucalyptus Cloud, an open-source project with API compatibility
with Amazon Elastic Compute Cloud and other Amazon web
services. At the time of Atmosphere’s inception, Eucalyptus
Cloud was determined to be the most stable, feature rich, and
extensibles. Integration with OpenStack is planned by early 2012.
3.2 Middleware
Atmosphere’s middleware is built on top of Django [12], a highlevel extensible python web framework designed for rapid
development. While having originated as a content management
system, the Django provides an excellent foundation for web
applications. Other python web frameworks were considered, but
Django was considered the most mature and offered the most
features when Atmosphere development began. Django’s core
components include an object relational mapper and user interface
facilities. Atmosphere’s middleware adds additional services for
auditing and monitoring, resource and job scheduling,
authentication, and metadata management.
Atmosphere’s authentication middleware service, named
CloudAuth, is designed to accept different authentication
schemes. Currently, it supports LDAP and an internal database.
Once a user authenticates, tokens are used for subsequent API
calls within the middleware. Authentication is discussed in more
detail in the security section of the paper.
Figure 2. Screenshot of Atmosphere home screen. VMs organized as "Applications".
The primary motivation for the user interface design is usability
for both inexperienced and expert cloud users. The home screen
for Atmosphere allows users to review and launch virtual
machines in an application store model, resembling modern
mobile and touch devices (see Figure 2). Convenient access to
VM and resource metadata is also provided using sidebars in the
interface. For expert cloud users, detailed information and finegrain access to the underlying cloud resources are available
through the “Dashboard” (see Figure 3).
Auditing and monitoring is provided through extensive logging of
most activities in Atmosphere and stored within Atmosphere’s
internal database. Detailed activities include VM launches, VM
terminations, storage requests, user logins, and user logouts. In
addition, Atmosphere performs periodic polling of the cloud
resources to perform resource consistency checks or to monitor
for known failure states of the underlying cloud. For instance, a
known failure state of Eucalyptus occurs when new VM cannot
obtain an IP address.
For failure states that cannot be
automatically remedied, notifications are sent to cloud
administrators.
Atmosphere requires internal scheduler to perform periodic tasks,
such as monitoring and polling. This internal schedule was built
using python celery [13]. Another important function of the
scheduler is to throttle simultaneous requests to the cloud engine
at times of high utilization, without which the cloud engine could
be paralyzed with too many requests. Future plans for the
scheduler include providing a means to launch VMs to backfill
resources during periods of low utilization, maximizing the
overall cluster efficiency.
Metadata management is facilitated through tags, descriptions,
and derived elements provided by users or cloud administrators.
Future versions of Atmosphere will include more intuitive means
to manage and search metadata, and to link metadata information
generated by other components of iPlant’s infrastructure.
3.3 Web Frontend
Atmosphere’s web frontend is a rich web 2.0 application, which
extensively uses AJAX [14] and JavaScript [15]. Ext JS [16]
provides much of the look and feel. Bidirectional communication
between middleware and the client browser, such as event
notifications, uses Faye [17], which implements the Bayeux
protocol [18].
Figure 3. Dashboard view to customize a virtual machine. The dashboard view provides
fine-grained configuration options for expert users.
3.4 Virtual Machine Toolkits
Atmosphere bundles several tools, in the form of scripts and
applications, through the virtual machine toolkits. Some tools are
essential to the operation of Atmosphere, assisting with the
communication between the Atmosphere middleware and the VM.
Other tools enhance the usability of a VM within iPlant’s
infrastructure or provide integration with iPlant’s compute and
storage resources. The following are descriptions of the tools in
the iPlant VM toolkits:
atmoCL – This program provides convenient access to select
Atmosphere web service functions, such as querying Atmosphere
metadata and managing cloud-specific storage. A typical use for
atmoCL is mounting EBS volumes onto a VM without using the
web frontend.
atmo_init – atmo_init executes as part of the boot-time process
and facilitates the configuration of a VM before it is available to a
user. Users will never need to access this tool directly.
condor tools – iPlant provides access to a small compute grid
based on Condor [19]. The condor tools are essentially the condor
executables necessary to submit jobs to iPlant’s grid for some
types of computations.
configuration management – Traditional configuration
management enables systems administrators to control and
automate the configuration of system software and services.
Atmosphere uses Puppet [20], a configuration management tool,
to dynamically configure systems on virtual machines. Future
versions of Atmosphere will enable users to dynamically
configure their own VMs.
image_request – This command-line tool collects the necessary
metadata from a VM, which will ultimately be displayed within
Atmosphere’s graphical catalogue.
The second type of storage is the iPlant Data Store. Users can
pull, push, or synchronize data in parallel using iRODS
command-line utilities or graphical clients. Another method of
managing data is using a Filesystem in Userspace (FUSE) [28]
client, which translates the iRODS API calls into filesystem calls.
One important distinction to using the iPlant Data Store is that
users can readily access the data across the entirety of iPlant’s
cyberinfrastructure, including the HPC resources and the
Discovery Environment.
6. CLOUD UTILIZATION
When Atmosphere was launched as a “preview” to the public in
January 2011, access was limited. Shortly after its initial launch,
iPlant Atmosphere opened access to researchers. The diversity of
current users represents 16 countries and 87 institutions. Within
the United States, where 89.6% of the total users reside, 30 states
are represented (see Chart 1).
iPlant Data Store utilities – iPlant utilitizes iRODS Data Grid
[21] for large scale storage. Users have access to both commandline and GUI-based clients to manage data within iPlant’s Data
Store.
4. SECURITY AND AUTHENTICATION
A function of the Atmosphere middleware is to mediate both the
cloud engine’s authentication and iPlant’s central authentication
services. An authentication service, called CloudAuth, provides a
pluggable framework to integrate with different authentication
mechanisms via modules. Currently, CloudAuth supports an
internal database or LDAP [22]. Planned authentication modules
include CAS [23] and Shibboleth [24].
In a typical authentication use case, users authenticate to the web
frontend. Secure sockets are used for every layer of network
communication. When a user authenticates using the web
frontend, a user’s iPlant credentials are mapped to the
corresponding credential provided by the cloud engine. The cloud
credentials allow the user to provision resources within their
namespace, allowing Atmosphere to leverage the cloud engine’s
mechanism for resource isolation.
Atmosphere web services APIs employ a simplified version of a
token-based authentication system. After authentication, external
services use a token to call methods on behalf of a user. Tokens
have a finite lifetime, configurable by the cloud administrator.
Users authenticate to their VMs primarily using their iPlant
credentials. SSH access is automatically configured to allow ssh
access to the specific user and by cloud administrators. Secure
VNC [25] access is enabled using a RealVNC [26] Enterprise
Server embedded on the VM.
5. DATA
Plant science is a data intensive science [27]. To address their
extensive data needs within the cloud, Atmosphere users have
access to two types of storage. The first type is provisioned
through the underlying cloud engine and is exclusive to a user’s
virtual machines. The cloud engine’s storage is recognized by the
VM as a native block device and uses typical system utilities for
managing devices, such as fdisk, parted and mount.
Chart 1. This chart illustrates the cumulative growth in the number of users since
Atmosphere’s public launch in January 2011.
Atmosphere has been utilized in three workshops and one
graduate-level bioinformatics course. Atmosphere is in active use
by five research laboratories to share image data using the iPlant
data store and analyze it using custom command line and GUI
based applications developed in MATLAB, these tools and
dependencies were deployed as compiled binaries as a bundled
VM; this custom VM is made available to the community to use
with their own data sets through Atmosphere (See Figure 4).
7. USE CASES
iPlant’s cyberinfrastructure provides multiple entry points to its
storage and compute resources, where Atmosphere fills specific
needs unmet by the other infrastructure services. The iPlant
Discovery Environment provides a structured way for users to
integrate tools and perform analysis via a web portal. Web
service APIs, through the Foundational and Semantic APIs,
programmatically expose this functionality to developers to
integrate with their existing science portals and tools. Direct
access to complex, large scale compute and storage is generally
available to plant scientists through XSEDE providers, such as
Texas Advanced Computing Center (TACC). Given these modes
•
Education, workshops, and training: Another large category
of users utilize Atmosphere for workshops and training
events.
Oftentimes, workshop organizers need preconfigured VMs, loading with sample data, for their
participants. The iPlant staff works closely with workshop
organizers to structure their environments and sample data.
8. CONCLUSION AND FUTURE WORK
Figure 4. A remote VNC connection to a Atmosphere instance showing the image analysis
toolkit and iPlant data store windows.
of access, there was a need for highly configurable environments
for algorithm exploration, tool development, small- to mediumsized analyses, or analyses that might not be traditionally suited
for HPC environments.
The following provides a glimpse of the typical use cases that
Atmosphere has used over the past several months since
Atmosphere has been released to the public:
•
•
•
Algorithm and Tool Development: Many of Atmosphere’s
users do not have convenient access to a UNIX environment
to design their own tools, whether via shell access or a
graphic desktop. The cloud, with its self-service, on-demand
model, is an obvious fit for these users. Typically, the period
of algorithm and tool development is finite between releases,
after which the environment may be saved or terminated
until the next stage of development begins. In some cases,
algorithm and tool developers publish their virtual machine
images for other community users. One example is the
Phytomorph VM, developed by Nathan Miller from the
University of Wisconsin, which provides machine vision
tools to correlate seed morphology to seed development.
On-Demand, Standalone Analysis:
As mentioned
previously, some users utilize virtual machines, configured
by tool developers, as part of their data analysis pipeline. In
other cases, users have developed their own analysis pipeline
want to deploy it virtually. A common problem mentioned
by some users is that their analysis pipeline exists on a
desktop or laptop, lacking the reliability or performance they
need to scale their analysis. In many cases, users choose
Atmosphere as a facility to share their analysis pipeline with
other lab members or collaborators. In these cases, providing
wholly contained, reproducible computational environments
is the most attractive features of Atmosphere.
On-Demand, Integrated Analysis: Integrated analysis refers
to analysis that may be partially performed using other parts
of iPlant’s infrastructure. For example, some users may have
part of their analysis performed using the Discovery
Environment and wish to further process the data using preinstalled tools on a virtual machine in Atmosphere. In other
cases, Atmosphere VMs have been used to prepare an
analysis to be later targeted for HPC resources. For
integrated analyses, the iPlant DataStore is used for sharing
data across iPlant’s various services.
The goal for Atmosphere is to provide ease of access to highly
customizable computational infrastructure, functioning as a
gateway that integrates and augments cloud resources with
capabilities such as HPC and data grids. Atmosphere also serves
as a platform to allow computational tool designers and
developers the ability to collaborate, and rapidly deploy their
analysis pipelines for broad use by the community. Atmosphere
plays a key role in providing customized computational resources
for pre and post analysis; e.g. Atmosphere has custom VM of
eight popular genome visualizers which are used to visualize a
large genome assembly, the compute intensive tasks were
performed on a HPC system where these resources intensive GUI
applications are not typically installed. Atmosphere’s ability to
provide easy web interface to preserve data, tools, and workflows
with minimal effort and skill overcomes the limitations and
technological barriers that prevent adoption of the cloud.
Deploying a cloud for the plant sciences hasn’t always been
smooth. One of the most salient challenges initially faced when
the project began was selecting the best cloud technology to use at
a time when cloud technologies were emergent. Selecting a
dominant cloud technology was more comparable to hedging a bet
than making a thorough competitive analysis. To move forward
with the project, we selected the best technologies at the time with
a design philosophy accounting for the fact that that the
underlying technologies would rapidly change and most likely be
replaced in the future.
Current and ongoing development module / features include:
•
OpenStack and public cloud integration; replacing the use of
euca2ools python library with a more generic, flexible
library, such as Apache’s Libcloud [29].
•
Utilization-based scheduling of resources, including
backfilling instances during low utilization periods
•
Multi-cloud support; the scheduling and provisioning of
resources across multiple, geographically dispersed clouds
•
Tighter integration with iPlant Discovery Environment, Grid,
and HPC resources
•
Automated, user-initiated VM image bundling
•
Expansion of support for mobile devices. Currently, an
Android application is available to view, launch, and
terminate instances.
•
Authentication with common academic institutional
authentication standards, such as Jasig Central
Authentication Service (CAS) or Shibboleth; Integration with
InCommon [30].
•
More intelligent metadata management and search
capabilities; integration with semantic approaches to
metadata search.
9. ACKNOWLEDGMENTS
The iPlant Collaborative is funded by a grant from the National
Science Foundation Plant Cyberinfrastructure Program (#DBI0735191).
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