CLOUD COMPUTING
UNIT – 1
Book: Cloud Computing Principles and Paradigms
By: Rajkumar Buyya, James Broberg, Andrzej Goscinski
INTRODUCTION
– Fully virtualized.
– Built from distributed components ( storage, data
& s/w resources)
– Technologies – cluster, grid and now is cloud
computing.
– Pay – as – you – go: water, electricity, gas,
telephone.
Cloud Computing
• On demand computing services: Amazon,
Google, etc.
• Denotes a model on which a computing
infrastructure is viewed as a “cloud”.
• Principle behind the model: offering
computing, storage and s/w “as a service”.
Buyya:
“Cloud is a parallel and distributed computing
system consisting of a collection of interconnected and virtualised computers that are
dynamically provisioned and presented as one
or more unified computing resources based on
service-level agreements (SLA) established
through negotiation between the service
provider and consumers.”
Vaquero:
“clouds are a large pool of easily usable and
accessible virtualized resources (such as hardware,
development platforms and/or services). These
resources can be dynamically reconfigured to adjust
to a variable load (scale), allowing also for an
optimum resource utilization. This pool of resources
is typically exploited by a pay-per-use model in
which guarantees are offered by the Infrastructure
Provider by means of customized Service Level
Agreements.”
McKinsey and Co. report:
“Clouds are hardware based services offering
compute, network, and storage capacity where:
Hardware management is highly abstracted
from the buyer, buyers incur infrastructure costs
as variable OPEX, and infrastructure capacity is
highly elastic.”
• A report from the University of California
Berkeley summarized the key characteristics
of cloud computing as:
1) The illusion of infinite computing resources;
2) The elimination of an up-front commitment
by cloud users
3) The ability to pay for use . . . as needed . . .
1.2 - Roots of Cloud Computing
• Advancement of technologies:
- Hardware ( virtualization, multi-core chips)
- Internet Technologies ( Web services ,
service oriented architectures)
- Distributed Computing ( Clusters, grids)
- System Management ( automatic
computing, data center automation)
1.2.1 - From mainframes to cloud
Computing - “On demand delivery of
infrastructure, applications, and business
processes in a security-rich, shared, scalable, and
based computer environment over the Internet for
a fee”
• Mainframe era collapsed -> fast and inexpensive
microprocessor.
• IT data centers -> collection of servers.
1.2.2 - SOA, Web Services, Web 2.0 and Mashups
• SOA - Service Oriented Architectures.
• Web services – application made available to
others.
• WS -> HTML, XML -> provides common
mechanism for delivering services, ideal for
SOA.
• Purpose of SOA – address requirements of
loosely coupled, standards-based, and
protocol-independent distributed computing.
• WS - intent of serving end-user applications
• Initially SOA application focused on Enterprise
Web.
• Gained space in consumer and became - Web
2.0.
• In the consumer Web, information and services
may be programmatically aggregated, acting as
building blocks of complex compositions, called
service mashups.
• Eg: Amazon, del.icio.us, Facebook, and Google
[Standard protocols :SOAP & REST]
• Popular APIs : Google Maps, Flickr, YouTube,
Amazon eCommerce, and Twitter
1.2.3 Grid Computing
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Aggregation of distributed resources.
Users don’t pay.
Resources have diverse s/w configuration.
Applications would run on specially
customized environment.
• So, portability is a barrier.
1.2.4 Utility Computing
• Users are assigned a “Utility” value to their
jobs.
• Utility: a fixed or time varying valuation that
captures various QoS constraints(deadline,
importance, satisfaction)
1.2.5 Hardware Virtualization
• Perfect fit the overcome operational issues of
data center building & maintenance.
• It allows running multiple OS & s/w stacks on
a single physical platform.
1.2.5 Hardware Virtualization
1.2.5 Hardware Virtualization
• Researchers emphasize on basic capabilities
regarding workload in a virtualized
environment.
1) Isolation
2) Consolidation
3) Migration
Types of VM
1) VMWare ESXi
2) Xen
3) KVM
VMWare ESXi:
• Pioneer in virtualization.
• Bare Metal Hypervisor: Installs directly on the
physical server, while others require host PC.
• Memory Ballooning & Page sharing.
Xen:
• Initially started as open source, then shifted to
commercial and open source both.
• Pioneer in para-virtualization: guest OS with the
help of kernel, can interact with the hypervisors.
• Eg: Critix XenServer & Oracle VM
KVM:
• Kernel Based VM – Linux virtualization system.
• Supports: Memory management &
Scheduling.
• Which makes KVM simpler
1.2.6 Virtual Appliances & the open
virtualization format
• Virtual Appliances: An application combined with the
“environment” needed to run.
• “environment” -> OS, libraries, compilers, database,
applications, etc.
• Vendors providing the packing & distribution of the s/w
(Eg: VMWare, IBM, Critix, Cisco, Microsoft, Dell, HP)
• OVF – Open Virtualization Format
• Open, secure, portable, efficient & extensible.
• OVF package: File/set of files -> describe VM
characteristics. (memory, n/w cards, disks, OS details,
startup & Shut down, meta data of the product, license
info.)
1.2.7 Autonomic Computing
• Systems manage themselves.
• Systems
- Monitoring probes
- Gauges(sensors)
- An adaption engine(autonomic manager).
• IBM autonomic computing initiative has 4 properties:
1) Self Configuration
2) Self Optimization
3) Self healing
4) Self protection
Other Eg: MAPE – K[Monitor Analyze Plan Execute –
Knowledge]
1.3 Layers and types of cloud
1) Infrastructure as a Service
2) Platform as a Service
3) Software as a Service
1.3.1 Infrastructure as a Service(IaaS)
• On demand servers.
• Users are given privileges to perform the
activities on the server (Eg: start, stop,
customizing, installing, attaching virtual disks,
configuring access permissions and firewall
rules)
• Bottom layer of cloud computing systems.
• Eg: Amazon Web Service
1.3.2 Platform as a Service(PaaS)
• Iaas - Provide raw computing and storage services.
• PaaS - higher level of abstraction to make a cloud easily
programmable.
• Developers create and deploy applications.
• Multiple programming models and specialized services
(e.g., data access, authentication, and payments) are
offered.
• Eg: PaaS - Google AppEngine
• Building blocks-> in-memory object cache(memcache),
mail service, instant messaging (XMPP), Image
manipulation service, integration with google service.
• Paas - Middle layer in cloud computing system
1.3.3 Software as a Service(SaaS)
• Top layer in cloud computing systems.
• Services provided can be accessed by end
users through Web portals.
• Traditional desktop – excel, word -> service on
the web.
• Reduces the burden of s/w maintenance.
• Eg: Saas - SalesForce.com
1.3.4 Deployment Models
Cloud can be classified as:
1) Public
2) Private
3) Community
4) Hybrid
Cloud Bursting: Temporarily renting -> to handle
load
1.4 Desired Features of Cloud
1.4.1 : Self Service
1.4.2 : Per-Usage Metering and Billing
1.4.3 : Elasticity
1.4.4 : Customization
1.5 Cloud Infrastructure Management
• Virtual Infrastructure Manager(VIM)
• Cloud OS
Category of cloud echo system tools:
1) Cloud Toolkits
2) The virtual Infrastructure manager
1.5.1 Features
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Virtualization Support
Self service, On-demand resource planning
Multiple Backend Hypervisors
Storage Virtualization
Interface to public clouds
Virtual Networking
Dynamic Resource Allocation
Virtual Clusters
Reservation & Negotiation Mechanism
High Availability & Data Recovery
Case Studies
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Apache VCL
AppLogic
Critix Essentials
Enomaly ECP
Eucalyptus
Nimbus
Open Nebula
Open PEX
Ovirt
Platfoem ISP
VMWare Vsphere & VCloud
1.6 Infrastructure as a service provider
Features:
• Geographic Presence
• User Interfaces and access to servers
• Advance reservation of capacity
• Automatic scaling & load balancing
• Service level agreement
• Hypervisor & Operating System choice
Case Studies
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AWS
Elexiscale
Joyent
GoGrid
RackSpace Cloud Services
Comparision chart: page 29 Table 1.2
1.6 Platform as a service provider
Features:
• Programming Models, Languages, and
Frameworks.
• Persistence Options
Case Studies
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Aneka
AppEngine
Microsoft Azure
Force.com
Heroku
Comparision chart: page 33 Table 1.3
1.8 Challenges and Risks
• Security, privacy and trust
• Data lock-in standardization
• Availability, fault tolerance and disaster
recovery
• Resource Management and Energy Efficiency