cloud computing and its applications
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Published Date:10-07-2017
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LECTURE NOTES ON CLOUD COMPUTING Unit-1 INTRODUCTION TO CLOUD COMPUTING CLOUD COMPUTING IN A NUTSHELL Computing itself, to be considered fully virtualized, must allow computers to be built from distributed components such as processing, storage, data, and software resources. Technologies such as cluster, grid, and now, cloud computing, have all aimed at allowing access to large amounts of computing power in a fully virtualized manner, by aggregating resources and offering a single system view. Utility computing describes a business model for on-demand delivery of computing power; consumers pay providers based on usage (“payas-you- go”), similar to the way in which we currently obtain services from traditional public utility services such as water, electricity, gas, and telephony. Cloud computing has been coined as an umbrella term to describe a category of sophisticated on-demand computing services initially offered by commercial providers, such as Amazon, Google, and Microsoft. It denotes a model on which a computing infrastructure is viewed as a “cloud,” from which businesses and individuals access applications from anywhere in the world on demand . The main principle behind this model is offering computing, storage, and software “as a service.” Many practitioners in the commercial and academic spheres have attempted to define exactly what “cloud computing” is and what unique characteristics it presents. Buyya et al. have defined it as follows: “Cloud is a parallel and distributed computing system consisting of a collection of inter-connected 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 et al. have stated “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.” A recent McKinsey and Co. report claims that “Clouds are hardwarebased 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; and (3) the ability to pay for use ... as needed .. .” The National Institute of Standards and Technology (NIST) characterizes cloud computing as “... a pay-per-use model for enabling available, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” In a more generic definition, Armbrust et al. define cloud as the “data center hardware and software that provide services.” Similarly, Sotomayor et al. point out that “cloud” is more often used to refer to the IT infrastructure deployed on an Infrastructure as a Service provider data center. While there are countless other definitions, there seems to be common characteristics between the most notable ones listed above, which a 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; and (iv) resources that are abstracted or virtualised. ROOTS OF CLOUD COMPUTING We can track the roots of clouds computing by observing the advancement of several technologies, especially in hardware (virtualization, multi-core chips), Internet technologies (Web services, service-oriented architectures, Web 2.0), distributed computing (clusters, grids), and systems management (autonomic computing, data center automation). Figure 1.1 shows the convergence of technology fields that significantly advanced and contributed to the advent of cloud computing. Some of these technologies have been tagged as hype in their early stages of development; however, they later received significant attention from academia and were sanctioned by major industry players. Consequently, a specification and standardization process followed, leading to maturity and wide adoption. The emergence of cloud computing itself is closely linked to the maturity of such technologies. We present a closer look at the technol ogies that form the base of cloud computing, with the aim of providing a clearer picture of the cloud ecosystem as a whole. From Mainframes to Clouds We are currently experiencing a switch in the IT world, from in-house generated computing power into utility-supplied computing resources delivered over the Internet as Web services. This trend is similar to what occurred about a century ago when factories, which used to generate their own electric power, realized that it is was cheaper just plugging their machines into the newly formed electric power grid . Computing delivered as a utility can be defined as “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” . Internet Technologies Hardware Hardware Virtualization Multi-core chips SOA Utility & Web 2.0 Cloud Grid Web Services Computing Computing Mashups Autonomic Computing Data Center Automation Systems Management FIGURE 1.1. Convergence of various advances leading to the advent of cloud computing. This model brings benefits to both consumers and providers of IT services. Consumers can attain reduction on IT-related costs by choosing to obtain cheaper services from external providers as opposed to heavily investing on IT infrastructure and personnel hiring. The “on-demand” component of this model allows consumers to adapt their IT usage to rapidly increasing or unpredictable computing needs. Providers of IT services achieve better operational costs; hardware and software infrastructures are built to provide multiple solutions and serve many users, thus increasing efficiency and ultimately leading to faster return on investment (ROI) as well as lower total cost of ownership (TCO). The mainframe era collapsed with the advent of fast and inexpensive microprocessors and IT data centers moved to collections of commodity servers. The advent of increasingly fast fiber-optics networks has relit the fire, and new technologies for enabling sharing of computing power over great distances have appeared. SOA, Web Services, Web 2.0, and Mashups • 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 Distributed Computing 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 Grid Computing Grid computing enables aggregation of distributed resources and transparently access to them. Most production grids such as TeraGrid and EGEE seek to share compute and storage resources distributed across different administrative domains, with their main focus being speeding up a broad range of scientific applications, such as climate modeling, drug design, and protein analysis. Globus Toolkit is a middleware that implements several standard Grid services and over the years has aided the deployment of several service-oriented Grid infrastructures and applications. An ecosystem of tools is available to interact with service grids, including grid brokers, which facilitate user interaction with multiple middleware and implement policies to meet QoS needs. Virtualization technology has been identified as the perfect fit to issues that have caused frustration when using grids, such as hosting many dissimilar software applications on a single physical platform. In this direction, some research projects. Utility Computing In utility computing environments, users assign a “utility” value to their jobs, where utility is a fixed or time-varying valuation that captures various QoS constraints (deadline, importance, satisfaction). The valuation is the amount they are willing to pay a service provider to satisfy their demands. The service providers then attempt to maximize their own utility, where said utility may directly correlate with their profit. Providers can choose to prioritize high yield (i.e., profit per unit of resource) user jobs, leading to a scenario where shared systems are viewed as a marketplace, where users compete for resources based on the perceived utility or value of their jobs. Hardware Virtualization The idea of virtualizing a computer system’s resources, including processors, memory, and I/O devices, has been well established for decades, aiming at improving sharing and utilization of computer systems . Hardware virtualization allows running multiple operating systems and software stacks on a single physical platform. As depicted in Figure 1.2, a software layer, the virtual machine monitor (VMM), also called a hypervisor, mediates access to the physical hardware presenting to each guest operating system a virtual machine (VM), which is a set of virtual platform interfaces . Virtual Machine 1 Virtual Machine 2 Virtual Machine N User software User software User software Facebook App Email Server App A App X Ruby on Data Web Java App B App Y Rails base Server Linux Guest OS Virtual Machine Monitor (Hypervisor) Hardware FIGURE 1.2. A hardware virtualized server hosting three virtual machines, each one running distinct operating system and user level software stack. Workload isolation is achieved since all program instructions are fully confined inside a VM, which leads to improvements in security. Better reliability is also achieved because software failures inside one VM do not affect others . Moreover, better performance control is attained since execution of one VM should not affect the performance of another VM . VMWare ESXi. VMware is a pioneer in the virtualization market. Its ecosystem of tools ranges from server and desktop virtualization to high-level management tools . ESXi is a VMM from VMWare. It is a bare-metal hypervisor, meaning that it installs directly on the physical server, whereas others may require a host operating system. Xen. The Xen hypervisor started as an open-source project and has served as a base to other virtualization products, both commercial and open-source.In addition to an open-source distribution , Xen currently forms the base of commercial hypervisors of a number of vendors, most notably Citrix XenServer and Oracle VM. KVM. The kernel-based virtual machine (KVM) is a Linux virtualization subsystem. Is has been part of the mainline Linux kernel since version 2.6.20, thus being natively supported by several distributions. In addition, activities such as memory management and scheduling are carried out by existing kernel features, thus making KVM simpler and smaller than hypervisors that take control of the entire machine . KVM leverages hardware-assisted virtualization, which improves performance and allows it to support unmodified guest operating systems ; currently, it supports several versions of Windows, Linux, and UNIX . Virtual Appliances and the Open Virtualization Format An application combined with the environment needed to run it (operating system, libraries, compilers, databases, application containers, and so forth) is referred to as a “virtual appliance.” Packaging application environments in the shape of virtual appliances eases software customization, configuration, and patching and improves portability. Most commonly, an appliance is shaped as a VM disk image associated with hardware requirements, and it can be readily deployed in a hypervisor. In a multitude of hypervisors, where each one supports a different VM image format and the formats are incompatible with one another, a great deal of interoperability issues arises. For instance, Amazon has its Amazon machine image (AMI) format, made popular on the Amazon EC2 public cloud. Other formats are used by Citrix XenServer, several Linux distributions that ship with KVM, Microsoft Hyper-V, and VMware ESX. OVF’s extensibility has encouraged additions relevant to management of data centers and clouds. Mathews et al. have devised virtual machine contracts (VMC) as an extension to OVF. A VMC aids in communicating and managing the complex expectations that VMs have of their runtime environment and vice versa. Autonomic Computing The increasing complexity of computing systems has motivated research on autonomic computing, which seeks to improve systems by decreasing human involvement in their operation. In other words, systems should manage themselves, with high-level guidance from humans . In this sense, the concepts of autonomic computing inspire software technologies for data center automation, which may perform tasks such as: management of service levels of running applications; management of data center capacity; proactive disaster recovery; and automation of VM provisioning . LAYERS AND TYPES OF CLOUDS Cloud computing services are divided into three classes, according to the abstraction level of the capability provided and the service model of providers, namely: (1) Infrastructure as a Service, (2) Platform as a Service, and (3) Software as a Service . Figure 1.3 depicts the layered organization of the cloud stack from physical infrastructure to applications. These abstraction levels can also be viewed as a layered architecture where services of a higher layer can be composed from services of the underlying layer. Infrastructure as a Service Offering virtualized resources (computation, storage, and communication) on demand is known as Infrastructure as a Service (IaaS) . A cloud infrastructure Service Main Access & Service content Class Management Tool Cloud Applications Web Browser Social networks, Office suites, CRM, Video processing SaaS Cloud Platform Cloud Development Programming languages, Frameworks, Environment PaaS Mashups editors, Structured data Cloud Infrastructure Virtual Infrastructure Compute Servers, Data Storage, Manager IaaS Firewall, Load Balancer 17 FIGURE 1.3. The cloud computing stack. enables on-demand provisioning of servers running several choices of operating systems and a customized software stack. Infrastructure services are considered to be the bottom layer of cloud computing systems . Platform as a Service In addition to infrastructure-oriented clouds that provide raw computing and storage services, another approach is to offer a higher level of abstraction to make a cloud easily programmable, known as Platform as a Service (PaaS).. Google AppEngine, an example of Platform as a Service, offers a scalable environment for developing and hosting Web applications, which should be written in specific programming languages such as Python or Java, and use the services’ own proprietary structured object data store. Software as a Service Applications reside on the top of the cloud stack. Services provided by this layer can be accessed by end users through Web portals. Therefore, consumers are increasingly shifting from locally installed computer programs to on-line software services that offer the same functionally. Traditional desktop applications such as word processing and spreadsheet can now be accessed as a service in the Web. Deployment Models Although cloud computing has emerged mainly from the appearance of public computing utilities. In this sense, regardless of its service class, a cloud can be classified as public, private, community, or hybrid based on model of deployment as shown in Figure 1.4. Public/Internet Private/Enterprise Hybrid/Mixed Clouds Clouds Clouds Mixed usage of 3rd party, Cloud computing private and public multi-tenant Cloud model run Clouds: infrastructure within a company’s Leasing public & services: own Data Center/ cloud services infrastructure for available on when private cloud internal and/or subscription basis capacity is (pay as you go) partners use. insufficient FIGURE 1.4. Types of clouds based on deployment models. Armbrust propose definitions for public cloud as a “cloud made available in a pay-as-you-go manner to the general public” and private cloud as “internal data center of a business or other organization, not made available to the general public.” A community cloud is “shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations) .” A hybrid cloud takes shape when a private cloud is supplemented with computing capacity from public clouds . The approach of temporarily renting capacity to handle spikes in load is known as “cloud-bursting” . DESIRED FEATURES OF A CLOUD Certain features of a cloud are essential to enable services that truly represent the cloud computing model and satisfy expectations of consumers, and cloud offerings must be (i) self-service, (ii) per-usage metered and billed, (iii) elastic, and (iv) customizable. Self-Service Consumers of cloud computing services expect on-demand, nearly instant access to resources. To support this expectation, clouds must allow self-service access so that customers can request, customize, pay, and use services without intervention of human operators . Per-Usage Metering and Billing Cloud computing eliminates up-front commitment by users, allowing them to request and use only the necessary amount. Services must be priced on a shortterm basis (e.g., by the hour), allowing users to release (and not pay for) resources as soon as they are not needed. Elasticity Cloud computing gives the illusion of infinite computing resources available on demand . Therefore users expect clouds to rapidly provide resources in any quantity at any time. In particular, it is expected that the additional resources can be (a) provisioned, possibly automatically, when an application load increases and (b) released when load decreases (scale up and down) . Customization In a multi-tenant cloud a great disparity between user needs is often the case. Thus, resources rented from the cloud must be highly customizable. In the case of infrastructure services, customization means allowing users to deploy specialized virtual appliances and to be given privileged (root) access to the virtual servers. Other service classes (PaaS and SaaS) offer less flexibility and are not suitable for general-purpose computing , but still are expected to provide a certain level of customization. CLOUD INFRASTRUCTURE MANAGEMENT A key challenge IaaS providers face when building a cloud infrastructure is managing physical and virtual resources, namely servers, storage, and networks, in a holistic fashion . The orchestration of resources must be performed in a way to rapidly and dynamically provision resources to applications . The availability of a remote cloud-like interface and the ability of managing many users and their permissions are the primary features that would distinguish “cloud toolkits” from “VIMs.” However, in this chapter, we place both categories of tools under the same group (of the VIMs) and, when applicable, we highlight the availability of a remote interface as a feature. Virtually all VIMs we investigated present a set of basic features related to managing the life cycle of VMs, including networking groups of VMs together and setting up virtual disks for VMs. These basic features pretty much define whether a tool can be used in practical cloud deployments or not. On the other hand, only a handful of software present advanced features (e.g., high availability) which allow them to be used in large-scale production clouds. Features We now present a list of both basic and advanced features that are usually available in VIMs. Virtualization Support. The multi-tenancy aspect of clouds requires multiple customers with disparate requirements to be served by a single hardware infrastructure. Self-Service, On-Demand Resource Provisioning. Self-service access to resources has been perceived as one the most attractive features of clouds. This feature enables users to directly obtain services from clouds. Multiple Backend Hypervisors. Different virtualization models and tools offer different benefits, drawbacks, and limitations. Thus, some VI managers provide a uniform management layer regardless of the virtualization technology used. Storage Virtualization. Virtualizing storage means abstracting logical storage from physical storage. By consolidating all available storage devices in a data center, it allows creating virtual disks independent from device and location. In the VI management sphere, storage virtualization support is often restricted to commercial products of companies such as VMWare and Citrix. Other products feature ways of pooling and managing storage devices, but administrators are still aware of each individual device. Interface to Public Clouds. Researchers have perceived that extending the capacity of a local in-house computing infrastructure by borrowing resources from public clouds is advantageous. In this fashion, institutions can make good use of their available resources and, in case of spikes in demand, extra load can be offloaded to rented resources . Virtual Networking. Virtual networks allow creating an isolated network on top of a physical infrastructure independently from physical topology and locations. A virtual LAN (VLAN) allows isolating traffic that shares a switched network, allowing VMs to be grouped into the same broadcast domain. Dynamic Resource Allocation. Increased awareness of energy consumption in data centers has encouraged the practice of dynamic consolidating VMs in a fewer number of servers. In cloud infrastructures, where applications have variable and dynamic needs, capacity management and demand prediction are especially complicated. This fact triggers the need for dynamic resource allocation aiming at obtaining a timely match of supply and demand. Virtual Clusters. Several VI managers can holistically manage groups of VMs. This feature is useful for provisioning computing virtual clusters on demand, and interconnected VMs for multi-tier Internet applications. Reservation and Negotiation Mechanism. When users request computational resources to available at a specific time, requests are termed advance reservations (AR), in contrast to best-effort requests, when users request resources whenever available . Additionally, leases may be negotiated and renegotiated, allowing provider and consumer to modify a lease or present counter proposals until an agreement is reached. High Availability and Data Recovery. The high availability (HA) feature of VI managers aims at minimizing application downtime and preventing business disruption. For mission critical applications, when a failover solution involving restarting VMs does not suffice, additional levels of fault tolerance that rely on redundancy of VMs are implemented. Data backup in clouds should take into account the high data volume involved in VM management. Case Studies In this section, we describe the main features of the most popular VI managers available. Only the most prominent and distinguishing features of each tool are discussed in detail. A detailed side-by-side feature comparison of VI managers is presented in Table 1.1. Apache VCL. The Virtual Computing Lab 60, 61 project has been incepted in 2004 by researchers at the North Carolina State University as a way to provide customized environments to computer lab users. The software components that support NCSU’s initiative have been released as open-source and incorporated by the Apache Foundation. AppLogic. AppLogic is a commercial VI manager, the flagship product of 3tera Inc. from California, USA. The company has labeled this product as a Grid Operating System. AppLogic provides a fabric to manage clusters of virtualized servers, focusing on managing multi-tier Web applications. It views an entire application as a collection of components that must be managed as a single entity. In summary, 3tera AppLogic provides the following features: Linux-based controller; CLI and GUI interfaces; Xen backend; Global Volume Store (GVS) storage virtualization; virtual networks; virtual clusters; dynamic resource allocation; high availability; and data protection. TABLE 1.1. Feature Comparison of Virtual Infrastructure Managers Installation Client UI, Advance Platform of API, Language Backend Storage Interface to Virtual Dynamic Resource Reservation of High Data License Controller Bindings Hypervisor(s) Virtualization Public Cloud Networks Allocation Capacity Availability Protection Apache Apache v2 Multi- Portal, VMware No No Yes No Yes No No VCL platform XML-RPC ESX, ESXi, (Apache/ Server PHP) AppLogic Proprietary Linux GUI, CLI Xen Global No Yes Yes No Yes Yes Volume Store (GVS) Citrix Essentials Proprietary Windows GUI, CLI, XenServer, Citrix No Yes Yes No Yes Yes Portal, Hyper-V Storage XML-RPC Link Enomaly ECP GPL v3 Linux Portal, WS Xen No Amazon EC2 Yes No No No No Eucalyptus BSD Linux EC2 WS, CLI Xen, KVM No EC2 Yes No No No No Nimbus Apache v2 Linux EC2 WS, Xen, KVM No EC2 Yes Via Yes (via No No WSRF, CLI integration with integration with OpenNebula OpenNebula) OpenNEbula Apache v2 Linux XML-RPC, Xen, KVM No Amazon EC2, Yes Yes Yes No No CLI, Java Elastic Hosts (via Haizea) OpenPEX GPL v2 Multiplatform Portal, WS XenServer No No No No Yes No No (Java) oVirt GPL v2 Fedora Linux Portal KVM No No No No No No No Platform Proprietary Linux Portal Hyper-V No EC2, IBM CoD, Yes Yes Yes Unclear Unclear ISF XenServer, HP Enterprise VMWare ESX Services Platform VMO Proprietary Linux, Portal XenServer No No Yes Yes No Yes No Windows VMWare Proprietary Linux, CLI, GUI, VMware VMware VMware Yes VMware No Yes Yes vSphere Windows Portal, WS ESX, ESXi vStorage vCloud partners DRM VMFS Citrix Essentials. The Citrix Essentials suite is one the most feature complete VI management software available, focusing on management and automation of data centers. It is essentially a hypervisor-agnostic solution, currently supporting Citrix XenServer and Microsoft Hyper-V. Enomaly ECP. The Enomaly Elastic Computing Platform, in its most complete edition, offers most features a service provider needs to build an IaaS cloud. In summary, Enomaly ECP provides the following features: Linux-based controller; Web portal and Web services (REST) interfaces; Xen back-end; interface to the Amazon EC2 public cloud; virtual networks; virtual clusters (ElasticValet). Eucalyptus. The Eucalyptus framework was one of the first open-source projects to focus on building IaaS clouds. It has been developed with the intent of providing an open-source implementation nearly identical in functionality to Amazon Web Services APIs. Nimbus3. The Nimbus toolkit is built on top of the Globus framework. Nimbus provides most features in common with other open-source VI managers, such as an EC2-compatible front-end API, support to Xen, and a backend interface to Amazon EC2. Nimbus’ core was engineered around the Spring framework to be easily extensible, thus allowing several internal components to be replaced and also eases the integration with other systems. In summary, Nimbus provides the following features: Linux-based controller; EC2-compatible (SOAP) and WSRF interfaces; Xen and KVM backend and a Pilot program to spawn VMs through an LRM; interface to the Amazon EC2 public cloud; virtual networks; one-click virtual clusters. OpenNebula. OpenNebula is one of the most feature-rich open-source VI managers. It was initially conceived to manage local virtual infrastructure, but has also included remote interfaces that make it viable to build public clouds. Altogether, four programming APIs are available: XML-RPC and libvirt for local interaction; a subset of EC2 (Query) APIs and the OpenNebula Cloud API (OCA) for public access 7, 65. (Amazon EC2, ElasticHosts); virtual networks; dynamic resource allocation; advance reservation of capacity. OpenPEX. OpenPEX (Open Provisioning and EXecution Environment) was constructed around the notion of using advance reservations as the primary method for allocating VM instances. oVirt. oVirt is an open-source VI manager, sponsored by Red Hat’s Emergent Technology group. It provides most of the basic features of other VI managers, including support for managing physical server pools, storage pools, user accounts, and VMs. All features are accessible through a Web interface. Platform ISF. Infrastructure Sharing Facility (ISF) is the VI manager offering from Platform Computing 68. The company, mainly through its LSF family of products, has been serving the HPC market for several years. ISF is built upon Platform’s VM Orchestrator, which, as a standalone product, aims at speeding up delivery of VMs to end users. It also provides high availability by restarting VMs when hosts fail and duplicating the VM that hosts the VMO controller. VMWare vSphere and vCloud. vSphere is VMware’s suite of tools aimed at transforming IT infrastructures into private clouds. It distinguishes from other VI managers as one of the most feature-rich, due to the company’s several offerings in all levels the architecture. In the vSphere architecture, servers run on the ESXi platform. A separate server runs vCenter Server, which centralizes control over the entire virtual infrastructure. Through the vSphere Client software, administrators connect to vCenter Server to perform various tasks. VMware ESX, ESXi backend; VMware vStorage VMFS storage virtualization; interface to external clouds (VMware vCloud partners); virtual networks (VMWare Distributed Switch); dynamic resource allocation (VMware DRM); high availability; data protection (VMWare Consolidated Backup). INFRASTRUCTURE AS A SERVICE PROVIDERS Public Infrastructure as a Service providers commonly offer virtual servers containing one or more CPUs, running several choices of operating systems and a customized software stack. In addition, storage space and communication facilities are often provided. Features In spite of being based on a common set of features, IaaS offerings can be distinguished by the availability of specialized features that influence the cost—benefit ratio to be experienced by user applications when moved to the cloud. The most relevant features are: (i) geographic distribution of data centers; (ii) variety of user interfaces and APIs to access the system; (iii) specialized components and services that aid particular applications (e.g., loadbalancers, firewalls); (iv) choice of virtualization platform and operating systems; and (v) different billing methods and period (e.g., prepaid vs. post- paid, hourly vs. monthly). Geographic Presence. To improve availability and responsiveness, a provider of worldwide services would typically build several data centers distributed around the world. For example, Amazon Web Services presents the concept of “availability zones” and “regions” for its EC2 service. User Interfaces and Access to Servers. Ideally, a public IaaS provider must provide multiple access means to its cloud, thus catering for various users and their preferences. Different types of user interfaces (UI) provide different levels of abstraction, the most common being graphical user interfaces (GUI), command-line tools (CLI), and Web service (WS) APIs. GUIs are preferred by end users who need to launch, customize, and monitor a few virtual servers and do not necessary need to repeat the process several times. On the other hand, CLIs offer more flexibility and the possibility of automating repetitive tasks via scripts. Advance Reservation of Capacity. Advance reservations allow users to request for an IaaS provider to reserve resources for a specific time frame in the future, thus ensuring that cloud resources will be available at that time. However, most clouds only support best-effort requests; that is, users requests are server whenever resources are available. Automatic Scaling and Load Balancing. As mentioned earlier in this chapter, elasticity is a key characteristic of the cloud computing model. Applications often need to scale up and down to meet varying load conditions. Automatic scaling is a highly desirable feature of IaaS clouds. Service-Level Agreement. Service-level agreements (SLAs) are offered by IaaS providers to express their commitment to delivery of a certain QoS. To customers it serves as a warranty. An SLA usually include availability and performance guarantees. Additionally, metrics must be agreed upon by all parties as well as penalties for violating these expectations. Hypervisor and Operating System Choice. Traditionally, IaaS offerings have been based on heavily customized open-source Xen deployments. IaaS providers needed expertise in Linux, networking, virtualization, metering, resource management, and many other low-level aspects to successfully deploy and maintain their cloud offerings. Case Studies In this section, we describe the main features of the most popular public IaaS clouds. Only the most prominent and distinguishing features of each one are discussed in detail. A detailed side-by-side feature comparison of IaaS offerings is presented in Table 1.2. Amazon Web Services. Amazon WS (AWS) is one of the major players in the cloud computing market. It pioneered the introduction of IaaS clouds in 2006. The Elastic Compute Cloud (EC2) offers Xen-based virtual servers (instances) that can be instantiated from Amazon Machine Images (AMIs). Instances are available in a variety of sizes, operating systems, architectures, and price. CPU capacity of instances is measured in Amazon Compute Units and, although fixed for each instance, vary among instance types from 1 (small instance) to 20 (high CPU instance). In summary, Amazon EC2 provides the following features: multiple data centers available in the United States (East and West) and Europe; CLI, Web services (SOAP and Query), Web-based console user interfaces; access to instance mainly via SSH (Linux) and Remote Desktop (Windows); advanced reservation of capacity (aka reserved instances) that guarantees availability for periods of 1 and 3 years; 99.5% availability SLA; per hour pricing; Linux and Windows operating systems; automatic scaling; load balancing.

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