EMC has developed a shared vision for the private cloud along with its key partners like VMware, Cisco, and AT&T. This group sees lots of opportunity in providing technology and services to companies looking for a better approach to managing IT infrastructure.

And although some companies may use private clouds as an entry point and then transition to public clouds, EMC sees the private cloud as much more than just a staging ground for public clouds. EMC and partners want to help you create a flexible set of IT resources by federating your private clouds with external infrastructures provided by third-party providers.

Not surprisingly, EMC’s contribution is concentrated on providing storage, backup, archiving, and security (from RSA) to support the data centers in a private cloud environment. When all IT resources (servers, network, and storage) are pooled in the virtualized data center model, many things need to change.

Storage must be designed and managed differently. For example, many EMC products require a dedicated pair of servers, and this requirement won’t fly in a virtualized environment. New tools and processes are required to plan and manage IT resources and ensure information security. For example, your company can use EMC’s Atmos cloud storage service to build a scalable internal storage cloud, and then tie it to an external cloud storage service. Cisco brings the network and capability of building a scalable network to the mix. VMware’s vSphere, as described later in this section, is the cloud operating system.

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HP has been working on cloudlike implementations with its customers since 2001. These implementations have typically included consulting and integration support and have leveraged HP’s extensive collection of technology management products.

Based on experiences in these customer engagements, HP has put a special emphasis on helping customers who want to create hybrid cloud environments. The company is leveraging its extensive services teams (including the EDS division) to help educate and lead their customers down an appropriate path to the cloud. EDS has significant experience with vertical marketmanaged services (hosted services specialized for different industries) and HP will leverage this knowledge and intellectual property (IP) in its evolving cloud strategy.

HP’s teams of business and IT consultants and engineers get involved with the design and implementation of many different types of cloud environments. For example, HP’s Infrastructure Design Service will help you design compute, storage, data center, and Infrastructure as a Service implementations. Other teams provide management consulting, business technology optimization, and testing services.

While companies can easily incorporate a CRM software as a service implementation into its IT environment, large-scale adoption of cloud computing requires IT to adopt a services focus; HP is designing some of its consulting services with this in mind. In addition, HP has expanded its cloud environment consulting teams to help companies focus in on the quality of service delivered across all business lines.

HP is packaging its hardware for private cloud implementations. Two key examples:

✓ Proliant SL, a scale-out server environment based on commodity servers

✓ Blade Matrix, a cloud in a box that includes the preintegration of networks, servers, storage, and automation capabilities

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With many of its large enterprise customers determined to transform their data centers to become more efficient, IBM has already done a lot of private and hybrid cloud implementations. While the majority of IBM’s initial efforts have been directed toward packaging private and hybrid solutions for enterprise data centers, in the longer term we expect to see a much broader strategy that includes all aspects of the cloud, including public clouds for SaaS, IaaS, and PaaS. IBM has created a centralized cloud computing organization with a goal of creating offerings that encompass software, hardware, and services.

IBM anticipates a lot of demand for solutions to manage the interface between public and private clouds. For example, IBM’s Blue Business platform supports both public and private cloud interfaces. In this scenario, the customer has a physical box on-site in the data center. This way the customer can have a private cloud inside the firewall that also supports the ability to burst out into the public cloud when they need additional compute capacity or storage.

A key element of the IBM private and hybrid cloud strategy is to offer solutions based on varying customer-driven workloads. These solutions are organized together as IBM Smart Business Cloud. IBM private and public cloud strategies offer solutions based on varying customer-centric workloads.

These solutions are delivered via three consumption models:

✓ Smart Business on the IBM Cloud (public cloud) is a set of standardized services delivered by IBM on the IBM cloud.

✓ Smart Business Cloud (private cloud) provides private cloud services, behind the client’s firewall, built and/or managed by IBM.

✓ Smart Business Systems (cloud in a box) are preintegrated, workloadoptimized systems for clients who want to build their own cloud with hardware and software.

In addition, IBM has a packaged private cloud offering. IBM combines the hardware, software, storage, virtualization, networking, and service management components in one package and adds options for services and financing. This package can include some preestablished connections to public cloud services.

As of August 2009, several categories of workload solutions are available for private cloud implementations, including the IBM Smart Analytics System. The following workloads are currently available:

✓ Development and test: Many organizations have a lot of variation in the demand for test and development resources, making these types of workloads a very practical first step for companies looking to improve data center and IT efficiency and cost-effectiveness. This offering is a private cloud implementation that provides customers with a self-service portal to develop and test on their own. This same service can be implemented inside a customer’s firewall. IBM also has a public cloud offering for this area.

✓ Desktop and devices: End-user connections to desktops and mobile devices are another workload type that IBM has identified as a requirement for private clouds. Companies want their users to access applications from anywhere (at any time) by using thin clients or other Internet-connected devices. This cloud service provides the technology infrastructure for these user environments.

✓ Infrastructure storage: IBM is offering access to storage on demand in various ways. Customers can install the IBM Smart Business Storage Cloud behind the firewall in the data center. Customers can also buy hardware with the virtual image of hardware and software required for additional storage. IBM also has an option for customers to buy on demand storage on the IBM public cloud.

✓ Infrastructure compute: This offering is IBM’s version of computing power on demand. This large enterprise offering has shared virtual images on the IBM cloud. IBM has partnered with Amazon and Google to add its middleware Software as a Service model in the Amazon and Google cloud environments.

In keeping with its strategy of providing packaged solutions to help companies get up to speed quickly, IBM also offers its IBM Cloudburst appliance, a family of preintegrated hardware, storage, virtualization, and networking with built-in service management.

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We wish we could tell you that there are clear distinctions between private and public clouds. Unfortunately, the lines are blurring between these two approaches. Hybrid approaches also are starting to take hold. For example, some public cloud companies are now offering private versions of their public clouds. Some companies that only offered private cloud technologies are now offering public versions of those same capabilities. In this section we offer some issues to consider when you’re making your business decision.


Going public
When is a public cloud the obvious choice? Here are some examples:
✓ Your standardized workload for applications is used by lots of people. Email is an excellent example.
✓ You need to test and develop application code.
✓ You have SaaS (Software as a Service) applications from a vendor who has a well-implemented security strategy.
✓ You need incremental capacity (to add compute capacity for peak times).
✓ You’re doing collaboration projects.
✓ You’re doing an ad-hoc software development project using a Platform as a Service (PaaS) offering.


Many IT department executives are concerned about public cloud security and reliability. You need to get security right and handle any legal and governance issues, or the short-term cost savings could turn into a long-term nightmare.


Keeping things private
In contrast, when would a private cloud be the obvious choice? Here are some examples:
✓ Your business is your data and your applications. Therefore, control and security are paramount.

✓ Your business is part of an industry that must conform to strict security and data privacy issues. A private cloud will meet those requirements.

✓ Your company is large enough that you have the economies of scale to run a next generation cloud data center efficiently and effectively.


Driving a hybrid
Now add one more choice into the mix: the hybrid cloud. When would you use it? It isn’t about making an either/or choice between a public or private cloud. In most situations, we think a hybrid environment will satisfy many business needs. Here are a few examples:

✓ Your company likes a SaaS application and wants to use it as a standard throughout the company; you’re concerned about security. To solve this problem, your SaaS vendor creates a private cloud just for your company inside their firewall. They provide you with a virtual private network (VPN) for additional security. Now you have both public and private cloud ingredients.

✓ Your company offers services that are tailored for different vertical markets. For example, you might offer to handle claims payments for insurance agents, shipping services for manufacturers, or credit checking services for local banks. You may want to use a public cloud to create an online environment so each of your customers can send you requests and review their account status. However, you might want to keep the data that you manage for these customers within your own private cloud.


Although private and public cloud environments each have management requirements by themselves, these requirements become much more complex when you need to manage private, public, and traditional data centers all together. You need to add capabilities for federating (linking distributed resources) these environments. In addition, your service levels need to focus on how a service is working rather than how a server is working.

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There’s confusion — as well as passionate debate — over the definition of a private cloud. When we say private cloud, we mean a highly virtualized cloud data center located inside your company’s firewall. It may also be a private space dedicated to your company within a cloud vendor data center designed to handle your company’s workloads.

The characteristics of the private cloud are as follows:
✓ Allows IT to provision services and compute capability to internal users in a self-service manner
✓ Automates management tasks and lets you bill business units for the services they consume
✓ Provides a well-managed environment
✓ Optimizes the use of computing resources such as servers
✓ Supports specific workloads
✓ Provides self-service based provisioning of hardware and software resources

You might think this sounds a lot like a public cloud! A private cloud exhibits the key characteristics of a public cloud, including elasticity, scalability, and self-service provisioning. (Please refer to Chapter 1 for detailed information on cloud characteristics.) The major difference is control over the environment. In a private cloud, you (or a trusted partner) control the service management.

It might help to think of the public cloud as the Internet and the private cloud as the intranet.

If private and public clouds are so similar, why would you develop a private cloud instead of ordering capacity on demand from an Infrastructure as a Service provider or using Software as a Service? Here are several good reasons companies are using a private rather than a public cloud:

✓ Your organization has a huge, well-run data center with a lot of spare capacity. It would be more expensive to use a public cloud even if you have to add new software to transform that data center into a cloud.

✓ Your organization offers IT services to a large ecosystem of partners as part of your core business. Therefore, a private cloud could be a revenue source.

✓ Your company’s data is its lifeblood. You feel that to keep control you must keep your information behind your own firewall.

✓ You need to keep your data center running in accordance with rules of governance and compliance.

✓ You have critical performance requirements, meaning you need 99.9999 percent availability. Therefore, a private cloud may be your only option. This higher level of service is more expensive, but is a business requirement.

Some early adopters of private cloud technology have experienced server use rates of up to 90 percent. This is a real breakthrough, particularly in challenging economic times.

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You’re thinking about using some of the data services in the cloud. Before you sign the contract, remember that data (especially your company’s data) is a precious asset and you need to treat it as such.

In addition to issues surrounding security and privacy of your data that we cover earlier in the chapter, we recommend asking your potential vendor about the following topics:

✓ Data integrity: What controls do you have to ensure the integrity of my data? For example, are there controls to make sure that all data input to any system or application is complete, accurate, and reasonable? What about any processing controls to make sure that data processing is accurate? And, there also need to be output controls in place to ensure that any output from any system, application, or process can be verified and trusted. This dovetails with the next bullet about any specific compliance issues that your particular industry might have.

✓ Compliance: You are probably aware of any compliance issues particular to your industry. Obviously, you need to make sure that your provider can comply with these regulations.

✓ Loss of data: What provisions are in the contract if the provider does something to your data (loses it because of improper backup and recovery procedures, for instance)? If the contract says that your monthly fee is simply waived, you need to ask some more questions.

✓ Business continuity plans: What happens if your cloud vendor’s data center goes down? What business continuity plans does your provider have in place: How long will it take the provider to get your data back up and running? For example, a SaaS vendor might tell you that they back up data every day, but it might take several days to get the backup onto systems in another facility. Does this meet your business imperatives?

✓ Uptime: Your provider might tell you that you will be able to access your data 99.999 percent of the time — however, read the contract. Does this uptime include scheduled maintenance?

✓ Data storage costs: Pay-as-you-go and no-capital-purchase options sound great, but read the fine print. For example, how much will it cost to move your data into the cloud? What about other hidden integration costs? How much will it cost to store your data? You should do your own calculations so you’re not caught off guard. Find out how the provider charges for data storage. Some providers offer a tiered pricing structure. Others offer pricing based on server capacity.

✓ Contract termination: How will data be returned if the contract is terminated? If you’re using a SaaS provider and it has created data for you too, will any of that get turned over to you? You need to ask yourself if this is an issue. Some companies just want the data destroyed. Understand how your provider would destroy your data to make sure that it isn’t floating around in the cloud.

✓ Data ownership: Who owns your data after it goes into the cloud? Some service providers might want to take your data, merge it with other data, and do some analysis.

✓ Switching vendors: If you create applications with one cloud vendor and then decide to move to another vendor, how difficult will it be to move your data? In other words, how interoperable are the services? Some of these vendors may have proprietary APIs and it might be costly to switch. You need to know this before you enter into an agreement.

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Given the scale of some of these applications, it isn’t surprising that new database technologies are being developed to support this kind of computing.

Some database experts believe that relational database models may have difficulty processing data across large numbers of servers — in other words, when the data is distributed across multiple machines. Performance can be slow when you’re executing complex queries that involve a join across a distributed environment. Additionally, in an old-style database cluster, data must either be replicated across the boxes in the cluster or partitioned between them. According to other database experts, this makes it hard to provision servers on demand.

In response, some large cloud providers have developed their own databases. Here’s a sample listing:

✓ Google Bigtable: This hybrid is sort of like one big table. Because tables can be large, they’re split at row boundaries into tablets, which might be 100 megabytes or so. MapReduce is often used for generating and modifying data stored in Bigtable. Bigtable is also the data storage vehicle behind Google’s App Engine (a platform for developing applications).

✓ Amazon SimpleDB: This Web service is for indexing and querying data. It’s used with two other Amazon products to store, process, and query data sets in the cloud. Amazon likens the database to a spreadsheet in that it has columns and rows with attributes and items stored in each. Unlike a spreadsheet, however, each cell can have multiple values and each item can have its own set of associated attributes. Amazon then automatically indexes the data.

✓ Cloud-based SQL: Microsoft has introduced a cloud-based SQL relational database called SQL Database (SDS). SDS provides data storage by using a relational model in the cloud and access to that data from cloud and client applications. It runs on the Microsoft Azure services platform. The Azure platform is an Internet-scale cloud-services platform hosted in Microsoft data centers; the platform provides an operating system and a set of developer services.

Numerous open-source databases are also being developed:
✓ MongoDB (schema-free, document-oriented data store written in C++)
✓ CouchDB (Apache open-source database)
✓ LucidDB (Java/C++ open-source data warehouse)

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The lure of cloud computing is its elasticity: You can add as much capacity as you need to process and analyze your data. The data might be processed on clusters of computers. This means that the analysis is occurring across machines.

Companies are considering this approach to help them manage their supply chains and inventory control. Or, consider the case of a company processing product data, from across the country, to determine when to change a price or introduce a promotion. This data might come from the point-of-sale (POS) systems across multiple stores in multiple states. POS systems generate a lot of data, and the company might need to add computing capacity to meet demand.

This model is large-scale, distributed computing and a number of frameworks are emerging to support this model, including

✓ MapReduce, a software framework introduced by Google to support distributed computing on large sets of data. It is designed to take advantage of cloud resources. This computing is done across large numbers of computers, called clusters. Each cluster is referred to as a node. MapReduce can deal with both structured and unstructured data. Users specify a map function that processes a key/value pair to generate a set of intermediate pairs and a reduction function that merges these pairs.

✓ Apache Hadoop, an open-source distributed computing platform written in Java and inspired by MapReduce. It creates a computer pool, each with a Hadoop file system. It then uses a hash algorithm to cluster data elements that are similar. Hadoop can create a map function of organized key/value pairs that can be output to a table, to memory, or to a temporary file to be analyzed. Three copies of the data exist so that nothing gets lost.

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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. Availability zones are “distinct locations that are engineered to be insulated from failures in other availability zones and provide inexpensive, low-latency network connectivity to other availability zones in the same region.” Regions, in turn, “are geographically dispersed and will be in separate geographic areas or countries.”


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 (e.g., start and shutdown a number of virtual servers at regular intervals). WS APIs offer programmatic access to a cloud using standard HTTP requests, thus allowing complex services to be built on top of IaaS clouds.


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. Amazon Reserved Instances is a form of advance reservation of capacity, allowing users to pay a fixed amount of money in advance to guarantee resource availability at anytime during an agreed period and then paying a discounted hourly rate when resources are in use. However, only long periods of 1 to 3 years are offered; therefore, users cannot express their reservations in finer granularities—for example, hours or days.


Automatic Scaling and Load Balancing. 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. It allow users to set conditions for when they want their applications to scale up and down, based on application-specific metrics such as transactions per second, number of simultaneous users, request latency, and so forth. When the number of virtual servers is increased by automatic scaling, incoming traffic must be automatically distributed among the available servers. This activity enables applications to promptly respond to traffic increase while also achieving greater fault tolerance.


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. Most IaaS providers focus their SLA terms on availability guarantees, specifying the minimum percentage of time the system will be available during a certain period. For instance, Amazon EC2 states that “if the annual uptime Percentage for a customer drops below 99.95% for the service year, that customer is eligible to receive a service credit equal to 10% of their bill.3”


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. More recently, there has been an emergence of turnkey IaaS platforms such as VMWare vCloud and Citrix Cloud Center (C3) which have lowered the barrier of entry for IaaS competitors, leading to a rapid expansion in the IaaS marketplace.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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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.


Apache VCL. The Virtual Computing Lab 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. Since its inception, the main objective of VCL has been providing desktop (virtual lab) and HPC computing environments anytime, in a flexible costeffective way and with minimal intervention of IT staff. In this sense, VCL was one of the first projects to create a tool with features such as: self-service Web portal, to reduce administrative burden; advance reservation of capacity, to provide resources during classes; and deployment of customized machine images on multiple computers, to provide clusters on demand. In summary, Apache VCL provides the following features: (i) multi-platform controller, based on Apache/PHP; (ii) Web portal and XML-RPC interfaces; (iii) support for VMware hypervisors (ESX, ESXi, and Server); (iv) virtual networks; (v) virtual clusters; and (vi) advance reservation of capacity. 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. Several components such as firewalls, load balancers, Web servers, application servers, and database servers can be set up and linked together. Whenever the application is started, the system manufactures and assembles the virtual infrastructure required to run it. Once the application is stopped, AppLogic tears down the infrastructure built for it. AppLogic offers dynamic appliances to add functionality such as Disaster Recovery and Power optimization to applications. The key differential of this approach is that additional functionalities are implemented as another pluggable appliance instead of being added as a core functionality of the VI manager. 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.


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.
By providing several access interfaces, it facilitates both human and programmatic interaction with the controller. Automation of tasks is also aided by a workflow orchestration mechanism. In summary, Citrix Essentials provides the following features: Windowsbased controller; GUI, CLI, Web portal, and XML-RPC interfaces; support for XenServer and Hyper-V hypervisors; Citrix Storage Link storage virtualization; virtual networks; dynamic resource allocation; three-level high availability (i.e., recovery by VM restart, recovery by activating paused duplicate VM, and running duplicate VM continuously); data protection with Citrix Consolidated Backup.


Enomaly ECP. The Enomaly Elastic Computing Platform, in its most complete edition, offers most features a service provider needs to build an IaaS cloud. Most notably, ECP Service Provider Edition offers a Web-based customer dashboard that allows users to fully control the life cycle of VMs. Usage accounting is performed in real time and can be viewed by users. Similar to the functionality of virtual appliance marketplaces, ECP allows providers and users to package and exchange applications. 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. Therefore, users can interact with a Eucalyptus cloud using the same tools they use to access Amazon EC2. It also distinguishes itself from other tools because it provides a storage cloud API—emulating the Amazon S3 API—for storing general user data and VM images. In summary, Eucalyptus provides the following features: Linux-based controller with administration Web portal; EC2-compatible (SOAP, Query) and S3- compatible (SOAP, REST) CLI and Web portal interfaces; Xen, KVM, and VMWare backends; Amazon EBS-compatible virtual storage devices; interface to the Amazon EC2 public cloud; virtual networks.


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. However, it distinguishes from others by providing a Globus Web Services Resource Framework (WSRF) interface. It also provides a backend service, named Pilot, which spawns VMs on clusters managed by a local resource manager (LRM) such as PBS and SGE. 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. Its architecture is modular, encompassing several specialized pluggable components. The Core module orchestrates physical servers and their hypervisors, storage nodes, and network fabric. Management operations are performed through pluggable Drivers, which interact with APIs of hypervisors, storage and network technologies, and public clouds. The Scheduler module, which is in charge of assigning pending VM requests to physical hosts, offers dynamic resource allocation features. Administrators can choose between different scheduling objectives such as packing VMs in fewer hosts or keeping the load balanced. Via integration with the Haizea lease scheduler, OpenNebula also supports advance reservation of capacity and queuing of best-effort leases. In summary, OpenNebula provides the following features: Linux-based controller; CLI, XML-RPC, EC2-compatible Query and OCA interfaces; Xen, KVM, and VMware backend; interface to public clouds (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 allocatingVMinstances. It distinguishes from other VI managers by its leases negotiation mechanism, which incorporates a bilateral negotiation protocol that allows users and providers to come to an agreement by exchanging offers and counter offers when their original requests cannot be satisfied. In summary, OpenPEX provides the following features: multi-platform (Java) controller; Web portal and Web services (REST) interfaces; Citrix XenServer backend; advance reservation of capacity with negotiation.


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. The oVirt admin node, which is also a VM, provides a Web server, secure authentication services based on freeIPA, and provisioning services to manage VM image and their transfer to the managed nodes. Each managed node libvirt, which interfaces with the hypervisor. In summary, oVirt provides the following features: Fedora Linux-based controller packaged as a virtual appliance; Web portal interface;KVMbackend.


Platform ISF. Infrastructure Sharing Facility (ISF) is the VI manager offering from Platform Computing. The company, mainly through its LSF family of products, has been serving the HPC market for several years. ISF’s architecture is divided into three layers. The top most Service Delivery layer includes the user interfaces (i.e., self-service portal and APIs); the Allocation Engine provides reservation and allocation policies; and the bottom layer—Resource Integrations—provides adapters to interact with hypervisors, provisioning tools, and other systems (i.e., external public clouds). The Allocation Engine also provides policies to address several objectives, such as minimizing energy consumption, reducing impact of failures, and maximizing application performance. 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. In summary, ISF provides the following features: Linux-based controller packaged as a virtual appliance; Web portal interface; dynamic resource allocation; advance reservation of capacity; high availability.


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. The Distributed Resource Scheduler (DRS) makes allocation decisions based on predefined rules and policies. It continuously monitors the amount of resources available to VMs and, if necessary, makes allocation changes to meet VM requirements. In the storage virtualization realm, vStorage VMFS is a cluster file system to provide aggregate several disks in a single volume. VMFS is especially optimized to store VM images and virtual disks. It supports storage equipment that use Fibre Channel or iSCSI SAN. In its basic setup, vSphere is essentially a private administration suite. Selfservice VM provisioning to end users is provided via the vCloud API, which interfaces with vCenter Server. In this configuration, vSphere can be used by service providers to build public clouds. In terms of interfacing with public clouds, vSphere interfaces with the vCloud API, thus enabling cloud-bursting into external clouds. In summary, vSphere provides the following features: Windows-based controller (vCenter Server); CLI, GUI, Web portal, and Web services interfaces; 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).

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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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. Virtualized resources (CPUs, memory, etc.) can be sized and resized with certain flexibility. These features make hardware virtualization, the ideal technology to create a virtual infrastructure that partitions a data center among multiple tenants.


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, such as spawning the creation of a server and tailoring its software, configurations, and security policies, without interacting with a human system administrator. This capability “eliminates the need for more time-consuming, labor-intensive, humandriven procurement processes familiar to many in IT”. Therefore, exposing a self-service interface, through which users can easily interact with the system, is a highly desirable feature of a VI manager.


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. This characteristic is more visible in open-source VI managers, which usually provide pluggable drivers to interact with multiple hypervisors [7]. In this direction, the aim of libvirt is to provide a uniform API that VI managers can use to manage domains (a VM or container running an instance of an operating system) in virtualized nodes using standard operations that abstract hypervisor specific calls.


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. Storage devices are commonly organized in a storage area network (SAN) and attached to servers via protocols such as Fibre Channel, iSCSI, and NFS; a storage controller provides the layer of abstraction between virtual and physical storage. 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. A VI manager can be used in a hybrid cloud setup if it offers a driver to manage the life cycle of virtualized resources obtained from external cloud providers. To the applications, the use of leased resources must ideally be transparent.


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. Additionally, a VLAN can be configured to block traffic originated from VMs from other networks. Similarly, the VPN (virtual private network) concept is used to describe a secure and private overlay network on top of a public network (most commonly the public Internet). Support for creating and configuring virtual networks to group VMs placed throughout a data center is provided by most VI managers. Additionally, VI managers that interface with public clouds often support secure VPNs connecting local and remote VMs.


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. Energy consumption reduction and better management of SLAs can be achieved by dynamically remapping VMs to physical machines at regular intervals. Machines that are not assigned any VM can be turned off or put on a low power state. In the same fashion, overheating can be avoided by moving load away from hotspots. A number of VI managers include a dynamic resource allocation feature that continuously monitors utilization across resource pools and reallocates available resources among VMs according to application needs.


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. To support complex requests, such as AR, a VI manager must allow users to “lease” resources expressing more complex terms (e.g., the period of time of a reservation). This is especially useful in clouds on which resources are scarce; since not all requests may be satisfied immediately, they can benefit of VM placement strategies that support queues, priorities, and advance reservations. Additionally, leases may be negotiated and renegotiated, allowing provider and consumer to modify a lease or present counter proposals until an agreement is reached. This feature is illustrated by the case in which an AR request for a given slot cannot be satisfied, but the provider can offer a distinct slot that is still satisfactory to the user. This problem has been addressed in OpenPEX, which incorporates a bilateral negotiation protocol that allows users and providers to come to an alternative agreement by exchanging offers and counter offers.


High Availability and Data Recovery. The high availability (HA) feature of VI managers aims at minimizing application downtime and preventing business disruption. A few VI managers accomplish this by providing a failover mechanism, which detects failure of both physical and virtual servers and restarts VMs on healthy physical servers. This style of HA protects from host, but not VM, failures. 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. In this style, redundant and synchronized VMs (running or in standby) are kept in a secondary physical server. The HA solution monitors failures of system components such as servers, VMs, disks, and network and ensures that a duplicate VM serves the application in case of failures. Data backup in clouds should take into account the high data volume involved in VM management. Frequent backup of a large number of VMs, each one with multiple virtual disks attached, should be done with minimal interference in the systems performance. In this sense, some VI managers offer data protection mechanisms that perform incremental backups of VM images. The backup workload is often assigned to proxies, thus offloading production server and reducing network overhead.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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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 software toolkit responsible for this orchestration is called a virtual infrastructure manager (VIM). This type of software resembles a traditional operating system—but instead of dealing with a single computer, it aggregates resources from multiple computers, presenting a uniform view to user and applications. The term “cloud operating system” is also used to refer to it. Other terms include “infrastructure sharing software” and “virtual infrastructure engine.”

Sotomayor et al., in their description of the cloud ecosystem of software tools, propose a differentiation between two categories of tools used to manage clouds. The first category—cloud toolkits—includes those that “expose a remote and secure interface for creating, controlling and monitoring virtualize resources,” but do not specialize in VI management. Tools in the second category—the virtual infrastructure managers—provide advanced features such as automatic load balancing and server consolidation, but do not expose remote cloud-like interfaces. However, the authors point out that there is a superposition between the categories; cloud toolkits can also manage virtual infrastructures, although they usually provide less sophisticated features than specialized VI managers do.

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.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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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. For these reasons, clouds must implement features to allow efficient trading of service such as pricing, accounting, and billing [2]. Metering should be done accordingly for different types of service (e.g., storage, processing, and bandwidth) and usage promptly reported, thus providing greater transparency.


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.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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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.

On-line marketplaces have been set up to allow the exchange of ready-made appliances containing popular operating systems and useful software combinations, both commercial and open-source. Most notably, the VMWare virtual appliance marketplace allows users to deploy appliances on VMWare hypervisors or on partners public clouds [30], and Amazon allows developers to share specialized Amazon Machine Images (AMI) and monetize their usage on Amazon EC2. 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.

In order to facilitate packing and distribution of software to be run on VMs several vendors, including VMware, IBM, Citrix, Cisco, Microsoft, Dell, and HP, have devised the Open Virtualization Format (OVF). It aims at being “open, secure, portable, efficient and extensible”. An OVF package consists of a file, or set of files, describing the VM hardware characteristics (e.g., memory, network cards, and disks), operating system details, startup, and shutdown actions, the virtual disks themselves, and other metadata containing product and licensing information. OVF also supports complex packages composed of multiple VMs (e.g., multi-tier applications).

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. A simple example of a VMC is when a cloud consumer wants to specify minimum and maximum amounts of a resource that a VM needs to function; similarly the cloud provider could express resource limits as a way to bound resource consumption and costs.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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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.

A key aspect of the grid vision realization has been building standard Web services-based protocols that allow distributed resources to be “discovered, accessed, allocated, monitored, accounted for, and billed for, etc., and in general managed as a single virtual system.” The Open Grid Services Architecture (OGSA) addresses this need for standardization by defining a set of core capabilities and behaviors that address key concerns in grid systems.

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.

The development of standardized protocols for several grid computing activities has contributed—theoretically—to allow delivery of on-demand computing services over the Internet. However, ensuring QoS in grids has been perceived as a difficult endeavor. Lack of performance isolation has prevented grids adoption in a variety of scenarios, especially on environments where resources are oversubscribed or users are uncooperative. Activities associated with one user or virtual organization (VO) can influence, in an uncontrollable way, the performance perceived by other users using the same platform. Therefore, the impossibility of enforcing QoS and guaranteeing execution time became a problem, especially for time-critical applications.

Another issue that has lead to frustration when using grids is the availability of resources with diverse software configurations, including disparate operating systems, libraries, compilers, runtime environments, and so forth. At the same time, user applications would often run only on specially customized environments.
Consequently, a portability barrier has often been present on most grid infrastructures, inhibiting users of adopting grids as utility computing environments.

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 (e.g., Globus VirtualWorkspaces) aimed at evolving grids to support an additional layer to virtualize computation, storage, and network resources.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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The emergence of Web services (WS) open standards has significantly contributed to advances in the domain of software integration. Web services can glue together applications running on different messaging product platforms, enabling information from one application to be made available to others, and enabling internal applications to be made available over the Internet.

Over the years a rich WS software stack has been specified and standardized, resulting in a multitude of technologies to describe, compose, and orchestrate services, package and transport messages between services, publish and discover services, represent quality of service (QoS) parameters, and ensure security in service access.

WS standards have been created on top of existing ubiquitous technologies such as HTTP and XML, thus providing a common mechanism for delivering services, making them ideal for implementing a service-oriented architecture (SOA). The purpose of a SOA is to address requirements of loosely coupled, standards-based, and protocol-independent distributed computing. In a SOA, software resources are packaged as “services,” which are well-defined, selfcontained modules that provide standard business functionality and are independent of the state or context of other services. Services are described in a standard definition language and have a published interface.

The maturity of WS has enabled the creation of powerful services that can be accessed on-demand, in a uniform way. While some WS are published with the intent of serving end-user applications, their true power resides in its interface being accessible by other services. An enterprise application that follows the SOA paradigm is a collection of services that together perform complex business logic.

This concept of gluing services initially focused on the enterprise Web, but gained space in the consumer realm as well, especially with the advent of Web 2.0. In the consumer Web, information and services may be programmatically aggregated, acting as building blocks of complex compositions, called service mashups. Many service providers, such as Amazon, del.icio.us, Facebook, and Google, make their service APIs publicly accessible using standard protocols such as SOAP and REST. Consequently, one can put an idea of a fully functional Web application into practice just by gluing pieces with few lines of code.

In the Software as a Service (SaaS) domain, cloud applications can be built as compositions of other services from the same or different providers. Services such user authentication, e-mail, payroll management, and calendars are examples of building blocks that can be reused and combined in a business solution in case a single, ready-made system does not provide all those features. Many building blocks and solutions are now available in public marketplaces. For example, Programmable Web1 is a public repository of service APIs and mashups currently listing thousands of APIs and mashups. Popular APIs such as Google Maps, Flickr, YouTube, Amazon eCommerce, and Twitter, when combined, produce a variety of interesting solutions, from finding video game retailers to weather maps. Similarly, Salesforce.com’s offers AppExchange,2 which enables the sharing of solutions developed by third-party developers on top of Salesforce.com components.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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When plugging an electric appliance into an outlet, we care neither how electric power is generated nor how it gets to that outlet. This is possible because electricity is virtualized; that is, it is readily available from a wall socket that hides power generation stations and a huge distribution grid. When extended to information technologies, this concept means delivering useful functions while hiding how their internals work. 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. In addition, an important aim of these technologies has been delivering computing as a utility. 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 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; 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.

In addition to raw computing and storage, cloud computing providers usually offer a broad range of software services. They also include APIs and development tools that allow developers to build seamlessly scalable applications upon their services. The ultimate goal is allowing customers to run their everyday IT infrastructure “in the cloud.”

A lot of hype has surrounded the cloud computing area in its infancy, often considered the most significant switch in the IT world since the advent of the Internet. In midst of such hype, a great deal of confusion arises when trying to define what cloud computing is and which computing infrastructures can be termed as “clouds.”

Indeed, the long-held dream of delivering computing as a utility has been realized with the advent of cloud computing. However, over the years, several technologies have matured and significantly contributed to make cloud computing viable. In this direction, this introduction tracks the roots of cloud computing by surveying the main technological advancements that significantly contributed to the advent of this emerging field. It also explains concepts and developments by categorizing and comparing the most relevant R&D efforts in cloud computing, especially public clouds, management tools, and development frameworks. The most significant practical cloud computing realizations are listed, with special focus on architectural aspects and innovative technical features.

Source of Information : Wiley - Cloud Computing Principles and Paradigms 2011

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For more than a decade, Sun has been advancing the state of the art of large-scale computing infrastructure that has formed the foundation of cloud computing. Beginning in the 1990s, Sun has been a leader in helping service providers implement their large-scale networks so that they can serve up to millions of customers. Large numbers of Sun servers are employed by financial institutions and stock exchanges to handle tasks ranging from handling transactions to realtime fraud detection. Sun has been a leader in high-performance computing by developing rack-at-a-time deployment models, automatic provisioning from the bare metal to the application, and large scale virtual networking with one petabit per second throughput. Indeed, Sun pioneered the cloud’s predecessor, grid computing, by selling physical server time by the hour and helping customers implement internal grids to support their own operations. Just as much as these large-scale computing capabilities help Sun develop cloud computing solutions, they are done in the context of advancing the systemic qualities that these solutions require: scalability, availability, reliability, manageability, and security.



Innovations from the Sun community
Sun has developed foundational technologies for cloud computing and has been a central player in the community development processes they have promoted. While Sun has long maintained the Solaris Operating System’s industry leadership, it has also spawned a corresponding open source movement around the OpenSolaris Operating System. The MySQL database is the Web application database of choice, and the Java programming language powers Web sites and enterprise datacenters worldwide. The community-based, open source GlassFish application server provides a Java software execution container that has been extended to support Ruby applications and the Drupal content management system. OpenSolaris Project Crossbow has helped to expand the multi-tenancy support in Sun xVM hypervisor.

Beneath the rich, community-supported Software that Sun helps to foster comes the powerful server, storage, and networking products that make them perform — including standard, scalable x86-architecture servers, Sun’s UltraSPARC® processorpowered server product line, and servers that incorporate Sun’s energy-efficient, chip multithreaded (CMT) UltraSPARC T1, T2, and T2 Plus processors. Sun’s CMT processors process high-throughput workloads so efficiently that they are harnessed in content load balancing and application delivery products such as the Zeus Extensible Traffic Manager. Sun’s Open Storage products combine open source software with industry-standard hardware to help reduce reliance on high-priced, purpose-built systems. Indeed, Sun’s ground-breaking Sun Fire X4500 Server helped the industry see the benefits of combining server and storage technology in the same system. Sun delivers virtual networking for large-scale computing through InfiniBand to massive-scale compute grids with the Sun Datacenter Switch 3456, scaling up to 13,834 nodes.



Community and open standards
Working with a community breeds open standards-based products and helps to provide investment protection. In an emerging and rapidly changing market such as cloud computing, it’s easy to create applications that are locked in to one vendor’s cloud because of the use of proprietary APIs and formats. Using open standards and open source software is the best insurance that the applications you create today will still be useful tomorrow and will give you the needed flexibility to change cloud providers.

The open source communities with which Sun is involved develop to open standards where they exist, and establish new open standards as new products are developed. Open source, open standards, and open APIs lead to applications that have more portability and longevity. Sun’s credentials in the open source community are impeccable, with projects including the: OpenSolaris OS, Linux OS, StarOffice™ software, NetBeans™ platform application framework, OpenSPARC™ technology, Java programming language, Sun xVM hypervisor, Sun xVM VirtualBox, Sun Open Storage Solutions, MySQL database management system, and the Solaris ZFS™ File System.



The importance of choice
Sun’s hardware and software product line is synonymous with choice. Sun offers the choice of servers based on the x86 architecture, that are powered by powerful SPARC® and UltraSPARC processors, and those with CoolThreads™ technology. Sun offers all of these choices in form factors including rack-mount and blade systems, allowing customers a range of densities and I/O capacities to choose from. Sun offers virtualization solutions for every one of its server products, including support on its x86-architecture servers for Sun xVM hypervisor, VMware vSphere, and Microsoft Hyper-V. And of course your choice of operating system, including the Solaris OS, Linux, and Microsoft Windows.



Choosing a cloud computing provider
Sun innovations are the foundational technologies for cloud computing environments that are open, standards-based, and are the fruit of a community effort. Joining the Sun cloud computing community means having the choice of server, storage, and networking technologies that work at maximum scale. It means using software stacks, APIs, and standards that aren’t owned by a cloud provider, they’re owned by the companies that build their cloud applications to have lasting value. Sun offers choice —not just in using the right hardware and software components to get the job done —but in leveraging cloud computing for the greatest benefit.

Those joining the Sun community for cloud computing have a range of options. Sun can help organizations build their own private, local clouds as a way to transition enterprise datacenters toward this new computing model while retaining the utmost control over business-critical data. Sun can help companies build their own private, non-local clouds as a way to leverage the low cost of new large, energyefficient colocation facilities such as Switch Communications’ SuperNAP facility in Las Vegas, Nevada. Sun can help those wishing to become cloud providers with the hardware, software, and management capabilities that are required. And, starting now, organizations everywhere can augment their private clouds with Sun’s public cloud offering —either by collocating with Sun at the SuperNAP site and enjoying the benefits of high-speed, local infrastructure, or by using Sun’s services over the Internet. Whether you are looking to cloud computing for development and testing, experimenting with hosting applications in the cloud, offloading specific functions, or using the cloud for surge computing, Sun is in a unique position to help enterprises build and use cloud computing.

Source of Information : Introduction to Cloud Computing architecture White Paper 1st Edition, June 2009

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Good security practices permeate every aspect of system design, implementation, and deployment. Applications must be secure by design, with interfaces that present only the appropriate data to authorized users. During implementation, developers must take care to avoid coding practices that could result in vulnerability to techniques such as buffer overflow or SQL injection. When deployed, operating systems should be hardened and every layer of software kept up to date with the most recent security patches.

In cloud computing, applications are deployed in a shared network environment, and very straightforward security techniques such as VLANs and port filtering are used to segment and protect various layers of an application deployment architecture as well as isolating customers from each other. Some approaches to network security include:

• Use security domains to group virtual machines together, and then control access to the domain through the cloud provider’s port filtering capabilities. For example, create a security domain for front-end Web servers, open only the HTTP or HTTPS ports to the outside world, and filter traffic from the Web server security domain to the one containing back-end databases.

• Control traffic using the cloud provider’s port-based filtering, or utilize more stateful packet filtering by interposing content switches or firewall appliances where appropriate. For even more fine-grained control over traffic, the concept of Immutable Service Containers (ISCs) allow multiple layers of software to be deployed in a single virtual machine, with pre-plumbed networking that is kept internal to the virtual machine. This technology uses Solaris™ Zones to support multiple secure virtual environments on a shared OS platform, and is available with both the Solaris and OpenSolaris Operating Systems.


Source of Information : Introduction to Cloud Computing architecture White Paper 1st Edition, June 2009

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Data physics considers the relationship between processing elements and the data on which they operate. Since most compute clouds store data in the cloud, not on a physical server’s local disks, it takes time to bring data to a server to be processed. Data physics is governed by the simple equation that describes how long it takes to move an amount of data between where it is generated, stored, processed, and archived. Clouds are good at storing data, not necessarily at archiving it and destroying it on a predefined schedule. Large amounts of data, or low-bandwidth pipes, lengthen the time it takes to move data:

time = bytes * 8 / bandwidth

This equation is relevant for both the moment-by-moment processing of data and for long-term planning. It can help determine whether it makes sense, for example, to implement a surge computing strategy where it might take longer to move the data to a public cloud than it does to process it. It can also help determine the cost of moving operations from one cloud provider to another: whatever data has accumulated in one cloud provider’s datacenter must be moved to another, and this process may take time.

The cost of moving data can be expressed both in time and bandwidth charges. The\ hybrid model illustrated in Figure 5, where a company’s private cloud is collocated with its cloud provider’s public cloud, can help to reduce costs significantly. Bandwidth within a colocation facility generally is both plentiful and free, making this strategy a win-win proposition for both the time and dollar cost of moving data around.



The relationship between data and processing
Data physics is a reminder to consider the relationship between data and processing, and that moving data from storage to processing can take both time and money. Some aspects of this relationship to consider include:

• Data stored without compute power nearby has limited value, and cloud providers should be transparent regarding the network relationship between these two components. What is the size of their pipes? What is the latency? What is the reliability of the connection? Cloud providers should be forthcoming with answers to all of these questions.

• Cloud architects should be able to specify the locality of virtual components and services so that there is a well-defined relationship between virtual machines and the storage they access.

• Cloud providers may optimize this relationship automatically for customers, but consider whether their optimization is right for the application at hand.

• In a networked environment, it is sometimes more efficient (faster, less latency) to calculate a value than it is to retrieve it from networked storage. Consider the trade-off between using compute cycles and moving data around.



Programming strategies
Cloud computing calls for using programming strategies that consider the movement of data:

• Moving pointers around is usually better than moving the actual data. Note how the scheduler/worker model illustrated in Figure 10 uses a central storage service and passes tokens between application components rather than the actual data.

• Pointers should be treated as a capability, with care taken to ensure that they are difficult to forge.

• Tools such as representational state transfer (REST) or Simple Object Access Protocol (SOAP) help to reduce application state while managing the transfer of state data.



Compliance and data physics
Maintaining compliance with governmental regulations and industry requirements adds another layer of considerations to the management of data. A cloud architect needs to be able to specify both topological and geographical constraints on data storage. A cloud provider should make it easy to specify the relationship between data and the virtual machines that process it, and also where the data is stored physically:

• Companies handling personal data may be required to adhere to governmental regulations regarding the handling of the data. For example, those doing business in the European Union may violate local laws if they store their data in the United States because of the difference in how the law protects their data. In cases like this, cloud providers should provide the capability to specify constraints on how and where data can be moved.

• Companies subject to industry standards, such as those imposed by credit card processing authorities, may face restrictions on where data is stored and how and when it is destroyed. In cases like this, freed disk blocks cannot be allowed to be incorporated into another customer’s block of storage. They must be securely erased before reuse.

When choosing a cloud provider for data storage, consider not just whether the provider is trustworthy. Consider whether the cloud provider is certified according to standards appropriate for the application.



Security and data physics
Data is often the most valuable of a company’s assets, and it must be protected with as much vigilance than any other asset. It is easy to argue that more vigilance is needed to protect data because of how an intruder can potentially reach a company’s data from anywhere on the Internet. Some steps to take include:

• Encrypt data at rest so that if any intruder is able to penetrate a cloud provider’s security, or if a configuration error makes that data accessible to unauthorized parties, that the data cannot be interpreted.

• Encrypt data in transit. Assume that the data will pass over public infrastructure and could be observed by any party in between.

• Require strong authentication between application components so that data is transmitted only to known parties.

• Pay attention to cryptography and how algorithms are cracked and are replaced by new ones over time. For example, now that MD5 has been proven vulnerable to attack, use a stronger technique such as SHA-256.

• Manage who has access to the application and how:
- Consider using strong, token-based authentication for administrator roles.
- For customer login/password access, consider who manages the authentication server and whether it is under the company or the cloud provider’s control.
- For anonymous access to storage, for example anonymous FTP, consider whether a customer would have to register with the cloud provider for access or whether the cloud provider could federate with the company’s authentication server.


Source of Information : Introduction to Cloud Computing architecture White Paper 1st Edition, June 2009

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