The CICA GRID

A Cloud Computing Infrastructure on Demand with Open Source Technologies

M. A. Alvarez

, A. Fernandez-Montes

, J. A. Ortega

and L. Gonzalez-Abril

Computer Languages and Systems Department, University of Seville, Seville, Spain

Applied Economics I Department, University of Seville, Seville, Spain

Keywords:

Cloud Computing, Cluster, Cobbler, IaaS, OpenNebula, Proﬁle, Puppet, ReCarta, Virtual Machine.

Abstract:

A new approach technology to enable the expansion and replication of resources on demand is presented in

this paper. This approach is called CICA GRID and it provides service to research community in the Scientiﬁc

Computer Centre of Andalusia (CICA). This approach is an alternative solution to the initial cost involved in

building an own data center by public organizations for researches. This solution quickly provides resources

with a minimal technical staff effort. Also, an architecture and user interface example called ReCarta was

presented. This system supplies a private Cloud Computing system for non-technical end-users.

1 INTRODUCTION

In the last years, Cloud Computing has been launched

as a concept that it has potential to transform the way

in which computers are used and managed. This tech-

nology promises to realize the objective of transform-

ing the computing resources into a single process.

This process can use any quantity of resources dur-

ing the needed time.

These features are especially interesting for the

HPC/Grid Computing/Scientiﬁc area since they en-

able resources to be managed in a controlled envi-

ronment. In this sense, researchers estimate their

computing needs when a new project is considered.

Therefore, researchers must spend their time to con-

ﬁgure the available resources to satisfy their needs.

Furthermore, the problem is bigger if researchers do

not have technical computer knowledges.

In response to the needs of researchers and to

improve the Andalusian Supercomputing Network

(RASCI)

, the Scientiﬁc Computer Center of Andalu-

sia (CICA)

has implemented a technology solution

called CICA GRID. It enables the expansion or repli-

cation of resources depending on research demands.

CICA, in collaboration with the Spanish National

Grid Initiative

, features a high scalability cloud with

a quick resources conﬁguration: a GRID environment

http://rasci.cica.es

http://www.cica.es

http://www.es-ngi.es

solution.

The developed approach incorporates three tools

to carry out its function: Cobbler

, Puppet

and Open-

Nebula

. It was called ReCarta

and it hides these

tools to user by a web interface.

The paper is organized as follows: Cloud Com-

puting technology is brieﬂy presented in the next sec-

tion. In Section 3, the project motivation and system

architecture are analyzed and users’ tools and exam-

ples are given in Section 4. Benchmarks and features

are shown in Section 5. Section 6 provides a ﬁnal dis-

cussion and concludes this paper.

2 CLOUD COMPUTING

Cloud Computing refers to hardware and software in-

frastructure which allows applications to be served

across the web for end-users. Furthermore, it provides

computational resources and virtual hosting to build

their own applications for them and the hardware and

software datacenter is called the Cloud.

There are two kinds of Cloud: Public Cloud (Arm-

brust et al., 2009) and Private Cloud. The ﬁrst one

is available for commercial purposes and pay-per-use

(Stuer et al., 2007). The second one is found in an in-

http://cobbler.github.com

http://reductivelabs.com/trac/puppet

http://www.opennebula.org/doku.php

http://trac.cica.es/recarta/

301

A. Alvarez M., Fernandez-Montes A., A. Ortega J. and Gonzalez-Abril L..

The CICA GRID - A Cloud Computing Infrastructure on Demand with Open Source Technologies.

DOI: 10.5220/0003992603010304

In Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS-2012), pages 301-304

ISBN: 978-989-8565-11-2

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

dividual organization and the access is only allowed

to authorized members. Also, Cloud Computing sys-

tems can be classiﬁed as IaaS (Infrastructure as a Ser-

vice), PaaS (Platform as a Service) and SaaS (Soft-

ware as a Service).

3 PROJECT MOTIVATION AND

SYSTEM ARCHITECTURE

A cluster for HPC is supported by CICA and the ap-

plied model is basically IaaS inside a private cloud

which is accessed only by users from RASCI. It uses

SGE as the Local Resource Manager (LRM) with Sun

Grid Engine. Furthermore, this cluster has about 30

machines ant it is part of the Spanish National Grid

Initiative.

The main motivation is to increase the require-

ments for access to excess computational resources

of a working scheme in a cluster with an LRM. Thus,

a project where authenticated and authorized users

could design their own computational infrastructure

and then use and manage it across a comfortable and

simple interface was initiated. It was called “Recursos

a la carta” (À-la-carte resources).

To achieve these goals some technical issues must

be solved: i) machine supply; and ii) how to distribute

the available physical resources among these virtual

machines which they need them. The presented pro-

posal, called CICA GRID, is developed as follows.

3.1 Provisioning and Management of

Large-scale Virtual Systems

The CICA GRID is a private cloud with 35 virtual

machines. It is composed by gLite’s working nodes

and services (Andreetto et al., 2008). It is essential

to have a tool that enables easy and ﬂexible admin-

istration of these machines. The management of this

cloud will be easier and more automated with it. Also,

it must support the production control of the features

and services of each machine. Hence, the problem of

building the machines demanded by users has been

resolved using Cobbler/Koan.

This tool facilitates the provisioning of virtual ma-

chines according to options given by users when they

select how they want to build their machines and es-

tablishes an object hierarchy which deﬁnes the con-

ﬁguration characteristics at the highest levels. From

the highest to the lowest level, they are Distro, Pro-

ﬁle, Subproﬁle and System.

The relationship between objects that can be de-

ﬁned with Cobbler and the actual supplied machines

are shown in Figure 1.

Figure 1: Cobbler object hierarchy.

At the time of computer installation, PXE boots

the system while Cobbler shows a drop-down menu

where the installation type can be chosen. If a virtual

machine is going to be supplied, then it is possible to

use the Koan command over the physical machine to

specify what kind of machine is needed.

In the CICA GRID, users initiate a guided instal-

lation through a Cobbler proﬁle. In answer to this

request, the designated virtual machines are kept in

a shared space (machine repository [see Figure 2])

where they are left available to OpenNebula for de-

ployment.

Since provision and deployment of virtual ma-

chines does not resolve all infrastructure maintenance

problems, a system for automating administration

tasks is required and Puppet has been chosen. It pro-

vides a framework to simplify the work of system ad-

ministrators, reusing the code as much as possible and

allowing a modular system. Also, it is based on a

client-server scheme and a declarative language that

speciﬁes administration tasks.

Puppet is used in the CICA GRID to conﬁgure

and ensure that the NTP service of machines works

correctly. Also, it must ensure that users are authen-

ticated by LDAP and a basic backup conﬁguration,

security updates and certain ﬁle systems are set up.

Through Cobbler proﬁles, each newly supplied vir-

tual machine has a Puppet installed client.

Both Cobbler/Koan and Puppet have been proved

to be capable of providing support for hundreds of

machines.

3.2 Virtualized Systems

Open Nebula has been chosen to solve the problem

of ﬁnding a system for an efﬁcient deployment on

virtual machine. It is an open-source virtual infras-

tructure engine and it enables dynamic deployment

and re-placement of virtual machines using a pool of

physical resources. It has achieved to decouple the

ICEIS2012-14thInternationalConferenceonEnterpriseInformationSystems

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server not only from the physical infrastructure, but

also from the physical location.

Therefore, once Cobbler has provided machines

requested by users and they have been saved in repos-

itory, the system will build needed ﬁles to enable

OpenNebula to launch the deployment of machines

as shown in Figure 2.

Figure 2: Architecture: connection scheme.

4 USER TOOL

The CICA GRID has a modular design. It facilitates

its development and has been implemented in Python

(Lutz and Van, 2001) language. Each module presents

a well-deﬁned interface so it can be easily used by

other parts. They are Cobbler, DHCP and DNS man-

agement, Puppet, Open Nebula and User Interface

modules.

4.1 ReCarta

A minimalist approach which attempts to show users

the possible options is required. Therefore, the main

focus is not on writing less code, but providing users

with a useful system. This system is called ReCarta.

The created machine is composed for 2 steps. At

ﬁrst, users must deﬁne hardware and software fea-

tures when they create a new group of machines.

Later, users must indicate how many machines and

the names of each have to be deﬁned with these fea-

tures.

At the end of this process, created system user data

is shown along with the information needed for con-

nection and start-up. Therefore, users have a project

control panel at their disposal and they can see sys-

tems that they have been deﬁned.

4.2 Code Example

A code example is given in order to illustrate the set of

calls to deﬁned API by different modules. They carry

out tasks that a user has requested via web interface.

A new Cobbler proﬁle (a new project in the user

terminology) is created. It deﬁnes machines with 1

CPU, 512 MB of RAM, 4 GB of hard drive and Java

language support.

import mod_cobbler

import mod_dhcpDns

import mod_puppet

import mod_nebula

miCobbler = mod_cobbler.Cobbler( ’john’ )

miCobbler.setProfile( {

’nombrePerfil’:’project’,

’kickstart’:’vm-kickstart.template’,

’diskSize’:’4’,

’ram’:’512’,

’cpus’:’1’,

’comment’:’project profile’,

’software’:[ ’X-WINDOW’, ’JAVA-SUPPORT’ ]

} )

macs = miCobbler.setSystems( [

{ ’nombre’:’project-vm’,

’comentario’:’project VM’,

’perfil’:’project’ }

] )

mapIpNames = mod_dhcpDns.addSystemsDHCP(macs)

mod_dhcpDns.addEntryDns( mapIpNames )

miCobbler.provisionSystems( [ ’project-vm’ ] )

It is important to note two ReCarta design fea-

tures

. One is the high abstraction level offered by

different methods. The kickstart template is modiﬁed

to adapt it to different user requirements and it do not

appear nowhere. Also, DHCP/DNS server conﬁgura-

tions are modiﬁed to assign a place to new systems in

network.

The other feature of ReCarta is the absence of

system database to save information about deﬁned

projects and users, etc. ReCarta put the usernames

as a preﬁx to data proﬁles and the project name to de-

ﬁned system names by users. This design decision

has been taken to keep ReCarta as simple as possible.

5 BENCHMARKS AND

FEATURES

The CICA GRID is a private cloud with 35 virtual

machines with the following virtualized features: 1

core and 1 GB RAM. 6 physical servers are used to

virtualize them with the following features: 2 cores

and 4 GB RAM.

http://trac.cica.es/recarta/wiki/RecartaDevel

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Table 1: HPCC benchmarks.

Intel 6400 Intel 6400

Physical Virtualized

PTRANS(GB/s) 0.65 0.54

HPL(Gﬂops) 14.26 13.01

MPI Latency(ms) 0.00043 0.00053

MPI Bandwidth (ms) 1471.17 1477.64

Table 2: Bonnie++ write test - 2Gb blocks.

Server Sequential Sequential Random

type output (Kbs) input (Kbs) (seek/s)

Virtual 14014 34851 150.7

Physical 45678 49719 64.7

Table 3: Bonnie++ create test - 1Gb blocks.

Server type Sequential Random

Create (s) Create (s)

Virtual 0.0000 0.0000

Physical 1621 891

Table 4: Consumption of 6 physical and 35 virtual servers.

Servers Consumption Total

(KWh/year) (KWh/year)

35 virtual 222.6 7791

6 physical 516 3096

Nowadays, ReCarta creates systems compound of

Xen (Barham et al., 2003) virtual machines. It has

been used because it is proved that a paravirtualized

virtual machine only loses 5-10% of CPU perfor-

mances respect to equivalent physical machine.

Table 1 presents HPCC benchmark execution re-

sults. As expected, performances of the physical ma-

chine are better than virtualized machine. However, it

is observed that the performance is about the same in

both cases, so we can conclude that the proposal can

be accepted as valid.

Table 2 and Table 3 show Bonnie++ execution

results for virtual machine memory and equivalent

physical machine. Also, a signiﬁcant decrease in per-

formance between virtual and physical machine can

be seen for writing action to disc in these latter cases.

In this case, the differences are slightly higher be-

cause the benchmark is performed on disk access. In

this process, a virtual machine generates a very in-

tense trafﬁc on its virtual hard disk, especially read-

ing.

The power consumption can see in Table 4. The

use of virtualization allows the power consumption to

be reduced to 39% can be seen in it.

6 CONCLUSIONS

Although the CICA GRID is still in its experimen-

tal phase, some case studies have been carried out.

One of them is the creation of a small virtual cluster

to be used with Apache Hadoop (Borthakur, 2007).

Also, the project objectives have enabled that more

job requests could be served without exceed the nor-

mal workload for a HPC cluster.

From the point of view of the energy-saving in-

volved in virtualized environments, the CICA GRID

renders research advances for the research groups

with less cost by releasing electrical consumption.

We have learned during the launching of our pilot

project of Cloud Computing that our users appreciate

two advantages: i) the illusion of having a huge com-

puting resource reserved exclusively for them; and ii)

the possibility of increasing and decreasing the re-

sources according to their needs.

ACKNOWLEDGEMENTS

This research is partially supported by the projects of

the Spanish Ministry of Economy and Competitive-

ness ARTEMISA (TIN2009-14378-C02-01) and Si-

mon (TIC-8052) of the Andalusian Regional Ministry

of Economy, Innovation and Science.

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