Cloud computing virtualization

 Introduction
 The Cloud Ecosystem
 Virtualization
 Virtual Infrastructure Management
 Virtual Infrastructure Manager
(OpenNebula)
 Conclusion
 Question/Answer Session
 References

 What is cloud computing?
In General,
› A simple metaphor for the internet, based on the
symbol used to represent the worlwide network in
computer network diagrams

In technical terms
› Cloud computing is a model for enabling
ubiquitous, convenient, on-demand network access
to a shared pool of configurable computing
resources (e.g.
networks, servers, storage, applications, and services)
that can be rapidly provisioned and released with
minimal management effort or service provider
interaction.[*]

* The NIST Definition of Cloud Computing by Peter Mell, Timothy
Grance, Sep 2011

 Characteristics of Cloud model
› On-demand self-service
› Broad Network Access
› Resource pooling
› Rapid elasticity
› Measured services

 Architectural Layers of Cloud Computing
› Software as a service (SaaS)
 Offers a complete application as a service on demand
 A single instance of software runs on cloud and provides
service to multiple end users or organizations
 Examples are Google apps, salesforce.com etc.
› Platform as a service (PaaS)
 Encapsulates a layer of software and provides it as
service which is used to build higher-level services
 Consumers creates the software using tools and libraries
from the provider
 Consumer controls deployment and configuration
settings
 Provider provides networks, servers and storage
 Example, Google Apps Engine

 Architectural Layers of Cloud Computing
(cont)

› Infrastructure as a service (IaaS)
 Most basic cloud service model
 Provider provides computers (physical or a virtual
machine), storage, firewalls, and networks
 Provider provides these facilities on demand
 Consumer is responsible for maintaining
application software and operating system
 Cloud provider bill the consumer on the basis of
amount of resources allocated and consumed

 Cloud Computing Infrastructure Model
› Public Clouds
 Run by third parties
 Resources like applications and storage is available to
general public over internet for free or on a pay-per-
usage model
› Private Clouds
 Build for exclusive use of one client
 Provides utmost control over data, security and QoS
 Provides access to external resources through web
services
› Hybrid Clouds
 Hybrid cloud uses local infrastructure with cloud
computing capacity from public cloud

 Cloud ecosystem consists of :
1. Cloud Consumers
2. Cloud Management
 Used for controlling and monitoring of virtualized
resources
 Contains cloud toolkits like, Amazon EC2, Globus
Nimbus and Eucalyptus
3. Virtual Infrastructure Management
 Used for schedule and manage virtual machines
across multiple hosts
 It contains tools like OpenNebula, Vmware vSphere
for infrastructure management
4. Virtual Machine Manager
 Xen, KVM, Vmware etc

 What is virtualization?
› Virtualization is the creation of virtual (instead
of actual ) version of something, such as an
operating system, a server, a storage device
or network resources.[*]

* Definition from whatis.com

 Types of Virtualization
1. Server Virtualization
2. Storage Virtualization
3. Network I/O virtualization

 Server Virtualization
› There are three popular approaches to
server virtualization
1. Virtual Machine Model
 Based on host/guest pradigm
 Each guest runs on a virtual imitation of hardware
layer
 Guest operating systems runs without modification
 Guest requires real computing resources therefore
it uses a virtual machine monitor (VMM) to
coordinate instructions to cpu
 Examples are VMware and Microsoft Virtual server

 Server Virtualization (cont)
2. Paravirtual machine Model
 Based on host/guest model
 Uses VMM
 VMM can access and modify the guest operating
system code. This modification is called Porting
 Paravirtual machines are capable of running
multiple operating systems
 Examples are, Xen and UML

 Server Virtualization (cont)
3. Virtualization at operating system layer
 Host runs a single OS kernel as its core and exports
operating system functionality to each of the
guest
 Guest must use the same operating system as the
host
 Different distributions of same system are allowed
 Common binaries and libraries of host are shared
in this model, allowing thousands of guest to host
at the same time
 Examples are, OpenVZ and Linux-Vserver

 Storage Virtualization
› Pooling of physical storage from multiple
network storage devices into single storage
device
› Storage pool is managed from a central
console
› Used in Storage Area Network (SAN)
› Storage virtualization helps in
backup, archiving and recovery more easily
and in less time

 Network I/O Virtualization
› Virtual machines are logical computing
entities on a physical computers
› VMs are realized on top of virtualization
software layer that presents abstraction of
the underlying physical resources
› Network I/O virtualization provides multiple
VMs to share common bandwidth and
network links

 Network I/O virtualization (cont)
› Network bridging
 Network bridging is the first step in network
virtualization

› To address the complexity and performance
issues following hardware and software
oriented approaches are used
1. NIC Bonding
Software oriented

Hardware
1. Virtual Machine Device Queues (VMDq) oriented
2. Single Root I/O Virtualization (SR-IOV)

› Nic Bonding
 Software oriented approach
 It groups multiple physical
network links and provide the
Network bandwidth as an
aggregate logic to the VMs

› Virtual Machine Device Queues (VMDq)
 Hardware oriented approach
 It is implemented at chipset level
 VMDq handles parallel queues of packets and
routes them to appropriate VM
 Network throughput can reach up to 9.5Gbps
compared to 4Gbps without VMDq

 Network I/O Virtualization (cont)
› Single Root I/O Virtualization (SR-IOV)
 It is a feature of Peripheral component
Interconnect (PCI)
 Multiple VMs running on a single computer
can share natively a single PCI device
 This feature helps reducing overheads in
resource sharing and overheads in controlling
network I/O virtualization

 Network I/O Virtualization
› Challenges
1. Each host has hundreds of VMs and VNICs
which increases complexity and
management of each host
2. Complexity of packet multiplexing.
3. The ever increasing line rate. A line rate of
10Gbps or more at host is expected which
can add workload at the host cpu

› Virtual Switching with Intelligent NICs
 Each NIC has its own packet processor
 Offloads the processing work from CPU

 Provide a uniform and homogenous view of
virtualized resources, regardless of
virtualization platform
 Manage VMs lifecycle
 Setting up networks dynamically for group
of VMs
 Managing storage requirements
 Support resource allocation to meet
organization’s specific goals
 Adapt to organization’s changing resource
needs

 OpenNebula
› To control VM’s life cycle, the OpenNebula
core orchestrates three different
management areas:
1. Image and storage technologies
 Virtual tools for preparing disk images for VMs
2. The network fabric
 DHCP servers, firewalls and switches
3. Underlying hypervisors
 For creating and controlling VMs

 OpenNebula (cont)
› The OpenNebula core also supports service
deployment
 Services typically include set of interrelated
components requiring several VMs

› The core handles the delivery of context
information
 Web server’s IP address, digital certificates and
software licenses

› A separate scheduler component makes VM
placement decisions
 Creating and updating resource schedule and
sending appropriate deployment command
to OpenNebula core
 The default scheduler provides a rank
scheduling policy that places VMs on physical
resources according to ranking algorithm that
the administrator can configure
 It relies on real time data from both the running
VMs and available physical resources

› OpenNebula can support a hybrid cloud
model
 Uses cloud drivers to interface with external
clouds
 It helps organizations supplement the local
infrastructure with computing capacity from
public cloud to meet peak demands
 Includes EC2 driver which can submit requests
to Amazon EC2 and Eucalyptus and also
includes ElasticHosts driver

OpenNebula VI Engine Components

 The Haizea lease Manager
› Open source resource lease manager
› Can act as a VM scheduler for OpenNebula
› Simulator to evaluate different scheduling strategies
performance over time
› Haizea provides resources to users on lease terms
› Haizea supports advance reservation lease in which
resources must be available at a specific time
› Best effort lease in which resources are allocated as
soon as possible
› Immediate lease in which resources are provisioned
when requested.

Comparison of tools providing VIM capabilities

Tool Provisioning Default Placement Policies Configurable Support For hybrid Cloud Remote
Model Placement Interface
Policies s

Amazon Best Effort Proprietary Proprietary No EC2 Web
EC2 services
API

VMware Immediate Initial placement on CPU No Only when both the local vCloud
vSphere load and dynamic and external cloud use API
placement to balance vSphere
average CPU or memory
load and consolidate servers

OpenNebul Best-effort Initial placement based on Support for any Driver-based architecture No
a 1.2 requirement/rank policies to static/dynamic allows interfacing with
prioritize those resources placement multiple external clouds;
more suitable for the virtual policy supports EC2-compatible
machine (VM) using dynamic clouds and ElasticHosts
information and dynamic
placement to consolidate
servers

OpenNebul Immediate, Dynamic placement to VM placement Driver-based architecture No
a 1.2/ best-effort, implement AR leases strategies allows interfacing with
Haizea and supporting multiple external clouds;
advance queues and supports EC2-compatible
reservation priorities clouds and ElasticHosts
(AR)

 As private and hybrid IaaS clouds
grows, the need for a diverse ecosystem of
tools and technologies to create and
manage clouds also grows
 Private and hybrid clouds will also face the
challenge of efficiently managing finite
resources
 Virtualization leads to better resource
utilization
 Increase performance

 Network I/O virtualization for cloud computing, by Yan
Lou, University of Massachusetts Lowell

 Virtual Infrastructure Management in Private and Hybrid
Clouds, by Borja Sotomayor, Unv. Of Chicago, Ruben S.
Montero and Ignacio M.Liorente, Universidad
Complutense de Madrid and Ian Foster, Argonne
National laboratory, Unv. Of Chicago

 Introduction to Cloud Computing Architecture, white
paper, 1st Edition, June 2009, by Sun Microsystem

 NIST definition of Cloud Computing by Peter Mell and
Timothy Grance, September 2011

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