cloud computing, Principle and Paradigms: 1 introdution
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Transcript of cloud computing, Principle and Paradigms: 1 introdution
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Cloud ComputingPrinciple and Paradigms
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Preface
• information processing can be done more efficiently centrally, on large farms of computing and storage systems accessible via the Internet.• “clouds” are the natural evolution of traditional data
centers• Offer subscription-based access to infrastructure(IaaS),
platforms(PaaS), and applications(SaaS)• many open research problems
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Book Content• Foundations• Introduction to cloud computing
• Infrastructure as a Service (IaaS )• Platform and Software as a Service (PaaS/SaaS)• Monitoring and Management• Applications• Governance and Case Studies
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Cloud Computing: In a Glance
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1.Introduction To Cloud computing• Electric Power• Virtualize
• means delivering useful functions while hiding how their internals work
• Cluster, grid, cloud• access to large amounts of computing power in a fully virtualized
manner, by aggregating resources and offering a single system view• Delivering Computing as a utility
• On-demand• Pay-as-you-go
• Service provider (Amazon, Google)• Computing infrastructure (Cloud)• Access from anywhere• As a service
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Defining• Buyya• Cloud is a parallel and distributed computing system consisting of
a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources based on service-level agreements (SLA)
• Vanquero• 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.
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Defining
• McKinsey• Clouds are hardware based services offering compute,
network, and storage capacity where: Hardware management is highly abstracted from the buyer, buyers incur infrastructure costs, and infrastructure capacity is highly elastic
• Berkeley• 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 . . .
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Defining• NIST• a pay-per-use model for enabling available, convenient, on-
demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction
• Armbrust• Data center hardware and software that provide services.
• Sotomayor• IT infrastructure deployed on an Infrastructure as a Service
provider data center
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Common Characteristic
• Cloud should have• (i) pay-per-use (no ongoing commitment, utility prices)• (ii) elastic capacity and the illusion of infinite resources• (iii) self-service interface• (iv) virtualized (abstracted) resources
• The ultimate goal is allowing customers to run their everyday IT infrastructure “in the cloud.”
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Roots of Cloud Computing
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Internet Technologies• Web Service• applications running on different messaging product platforms• enabling information from one application to be made available to
others• enabling internal applications to be made available over the Internet
• SOA• address requirements of loosely coupled, standards-based, and
protocol-independent distributed computing• WS ,HTTP, XML
• Common mechanism for delivering service• applications is a collection of services that together perform complex
business logic • Building block in IaaS
• User authentication, payroll management, calender
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Distributed Computing• Grid Computing• aggregation of distributed resources • transparently access• Problems
• QoS, Lack of performance• Availability, Virtualization
• Utility Computing• assign a “utility” value to users• QoS constraints (deadline, importance, satisfaction)
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Hardware• Hardware Virtualization• overcome most operational issues of data center building and
maintenance• improving sharing and utilization of computer systems • running multiple operating systems and software stacks on a
single physical platform• virtual machine monitor (VMM)• mediates access to the physical hardware• presenting to guest operating system a virtual machine (VM)
• is a set of virtual platform interfaces
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Virtualization
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Virtualization
• Capabilities• Workload isolation• security
• Reliability• Performance ??• Utilization • Workload migration• Load balancing• Disaster recovery• …
• WMM example• VMWare ESXi, KVM, Xen
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Autonomic Computing• improve systems by decreasing human involvement in their
operation. • manage themselves, with high-level guidance from humans
• Properties• Self-configuration• Self-optimization• Self-healing• Self-protection
• IBM reference Model• MAPE-K
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Layers and Types of cloud
• Three abstraction level of the capability• (1) Infrastructure as a Service• (2) Platform as a Service• (3) Software as a Service
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IaaS
• Offering virtualized resources on demand• computation, storage, communication
• Bottom layer of cloud systems• Example• Amazon EC2• Offering VM• Software stack
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PaaS
• make a cloud easily programmable• offers an environment • developers create and deploy applications • do not necessarily need to know how many processors or
how much memory that applications will be using• offered building blocks• Google AppEngine• Python, java• Building block
• Mail service, instance messaging service, image manipulation service
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SaaS
• Applications reside on the top of the cloud stack
• accessed by end users through Web portal
• From locale to on-line software with same functionally
• Example• Salseforce.com• CRM
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Delivery Models
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Deployment Models• Public, Private , Community (hybrid)
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Deployment Models• Public cloud• cloud made available in a pay-as-you-go manner to the general
public• Private cloud• internal data center of a business or other organization, not made
available to the general public• restructuring an existing infrastructure• adding virtualization and cloud-like interfaces
• Community cloud• shared by several organizations and supports a specific community
that has shared concerns• hybrid cloud• takes shape when a private cloud is supplemented with computing
capacity from public clouds
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Desired Features of cloud
• (i) self-service• (ii) per-usage metered and billed• (iii) elastic• (iv) customizable.
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CLOUD INFRASTRUCTURE MANAGEMENT• Management is a challenge• VIM
• The software toolkit responsible for rapidly and dynamically provision resources to applications
• Cloud operation system• Cloud toolkit vs. virtual infrastructure manager• Availability and management users
• Features• basic and advanced features that are usually available in VIMs
• Case Studies• The most popular VI managers available
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Features• Virtualization Support• Self-Service, On-Demand Resource Provisioning• Multiple Backend Hypervisors• Storage Virtualization• SAN
• Interface to Public Clouds• Virtual Networking• Dynamic Resource Allocation• Green computing
• Virtual Clusters• Reservation and Negotiation Mechanism• Advance reservation and best-effort request
• High Availability and Data Recovery• FailOver Mechanism, redundancy, backup
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Case studies• Apache VCL• AppLogic• Grid Operating System
• Citrix Essentials• Enomaly ECP• ..• OpenPEX• ..• ..• ..• VMWare vSphere and vCloud
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IaaS PROVIDERS• Features
i. geographic presence• To improve availability and responsiveness, Availability Zones
ii. user interfaces and access the system• GUI, CLI, WS
iii. Advance reservation of capacity• Amazon, long period
iv. Automatic scaling and load balancingv. Service Level Agreement
• Availability and performance guarantee, QoSvi. Hypervisor and operation system choice
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IaaS PROVIDERS• Case studies• Amazon Web Services
• S3, EC2, RDS, …• Flexiscale
• 100% SLA• Joyent
• Automatic scaling of cpu cores• GoGrid
• Pre-made windows and linux images• Rackspace Cloud Servers
• Fixed size instance
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PaaS Providers• Features• Programming Models, Languages, and Frameworks
• MapReduce, WebService, Workflow, computational task• Persistence Options
• Record state and recover, relational DB, distributed storage
• Case studies• Aneka
• .NET, amazon EC2, threads• AppEngine
• python-java, Google• Microsoft Azure
• .NET, Microsoft• Force.com
• Apex, own dc• Heroku
• Ruby, automatic scaling
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Challenges and Risks• Security, privacy and trust• Third party services• Countries laws
• Data lock-in and standardization• Portable user data• CCIF
• Availability, Fault tolerance, disaster Recovery• SLA
• Resource Management and Energy efficiency• Migration• Performance• Green
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INTRODUCTIONEND
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