云計算（cloud computing，臺灣譯作云端運算），是分布式計算技術的一種，其最基本的概念，是透過網(wǎng)絡將龐大的計算處理程序自動分拆成無數(shù)個較小的子程序，再交由多部服務器所組成的龐大系統(tǒng)經(jīng)搜尋、計算分析之后將處理結果回傳給用戶。透過這項技術，網(wǎng)絡服務提供者可以在數(shù)秒之內，達成處理數(shù)以千萬計甚至億計的信息，達到和“超級計算機”同樣強大效能的網(wǎng)絡服務。

云計算是一種資源交付和使用模式，指通過網(wǎng)絡獲得應用所需的資源（硬件、平臺、軟件）。提供資源的網(wǎng)絡被稱為“云”?！霸啤敝械馁Y源在使用者看來是可以無限擴展的，并且可以隨時獲取。這種特性經(jīng)常被比喻為像水電一樣使用硬件資源，按需購買和使用。^[1]（Cloud computing is a resource delivery and usage model, it means get resource (Hardware, software)via network. The network of providing resource is called ‘Cloud’. The hardware resource in the ‘Cloud’ seems scalable infinitely and can be used whenever.）^[2]

最簡單的云計算技術在網(wǎng)絡服務中已經(jīng)隨處可見，例如搜尋引擎、網(wǎng)絡信箱等，使用者只要輸入簡單指令即能得到大量信息。

未來如手機、GPS等行動裝置都可以透過云計算技術，發(fā)展出更多的應用服務。

進一步的云計算不僅只做資料搜尋、分析的功能，更可計算一些像是分析DNA結構、基因圖譜定序、解析癌癥細胞等。

稍早之前的大規(guī)模分布式計算技術即為“云計算”的概念起源^[1]。

Google目前的云技術，主要由MapReduce、GFS及BigTable三項所組成

云是指因特網(wǎng)，因過去一直將因特網(wǎng)畫成一朵云。

云端儲存（cloud storage）是一種將數(shù)據(jù)保存在虛擬服務器上的數(shù)據(jù)類型，通常意義上，數(shù)據(jù)存儲在第三方媒介，而非特定單一服務器上。

2007年10月，Google與IBM開始在美國大學校園，包括卡內基美隆大學、麻省理工學院、史丹佛大學、加州大學柏克萊分校及馬里蘭大學等，推廣云計算的計劃，這項計劃希望能降低分布式計算技術在學術研究方面的成本，并為這些大學提供相關的軟硬件設備及技術支援（包括數(shù)百臺個人計算機及BladeCenter與System x服務器，這些計算平臺將提供1600個處理器，支援包括Linux、Xen、Hadoop等開放源代碼平臺）。而學生則可以透過網(wǎng)絡開發(fā)各項以大規(guī)模計算為基礎的研究計劃^[1]。

2008年1月30日，Google宣布在臺灣啟動“云計算學術計劃”，將與臺灣大學、臺灣交通大學等學校合作，將這種先進的大規(guī)模、快速計算技術推廣到校園^[3]。

2008年8月3日，美國專利商標局(以下簡稱“SPTO”)網(wǎng)站信息顯示，戴爾正在申請“云計算”(Cloud Computing)商標，此舉旨在加強對這一未來可能重塑技術架構的術語的控制權。戴爾在申請文件中稱，云計算是“在數(shù)據(jù)中心和巨型規(guī)模的計算環(huán)境中，為他人提供計算機硬件定制制造”。^[4]。

云計算是隨著處理器技術、虛擬化技術、分布式存儲技術、寬帶互聯(lián)網(wǎng)技術和自動化管理技術的發(fā)展而產生的. 這種大規(guī)模的計算能力通常是由分布式的大規(guī)模集群和服務器虛擬化軟件搭建。(Cloud computing and technology:New advances in processors, virtualization technology, distributed storage, broadband Internet access , automated management and fast, inexpensive servers have all combined to make cloud computing a compelling paradigm.This vast process power is usually got with a distributed, large-scale server cluster and server virtualization software.)

傳統(tǒng)的計算模式下，單臺臺式機的資源用來完成任務。在客戶服務器模式下，服務器用來執(zhí)行任務。在云計算模式下，網(wǎng)絡超級計算機—“云”用來執(zhí)行任務。用戶能在任何時間任何地點通過互聯(lián)網(wǎng)獲取計算、存儲、網(wǎng)絡資源，并且能夠按照處理器利用率、存儲使用量、帶寬消耗付費。(Cloud computing usage model:In traditional computing model, tasks are completed using a single desktop computer. In the client/serer model, tasks are completed using a remote server. In cloud computing model, tasks are completed using ‘Cloud’-a network super computer.Cloud computing allows users and companies to pay for and use the services and storage that they need, when they need them and, as wireless broadband connection options grow, where they need them. Customers can be billed based upon server utlilization, processing power used or bandwidth consumed.)

云計算有可能顛覆軟件產業(yè)，應用和許可被隨時購買和生效，應用在網(wǎng)絡上而不是本機上運行。這種轉變將數(shù)據(jù)中心放在網(wǎng)絡的核心位置，而所有的應用所需要的計算能力、存儲、帶寬、電力都由數(shù)據(jù)中心提供。云計算不僅影響商業(yè)模式，還影響開發(fā)、部署、運行、交付應用的方式。(Cloud computing impact:As a result, cloud computing has the potential to upend the software industry entirely, as applications are purchased, licensed and run over the network instead of a user's desktop. This shift will put data centers and their administrators at the center of the distributed network, as processing power, electricity, bandwidth and storage are all managed remotely. It affects not only business models, but the underlying architecture of how we develop, deploy, run and deliver applications.)^[5]

• 快速部署(Fast Provision)

• 縮小主機規(guī)模(Reduce servers scale)

• 提高資源利用率(Increase resource utilization rate)

• 提高管理效率(Improve management efficiency)

• 降低運維成本(Lower maintenance cost)

• 基礎設施可以放置在低土地和能源成本的地區(qū)(Location of infrastructure in areas with lower costs of real estate and electricity)

• 提供商業(yè)連續(xù)性服務(Provide business continuity service)

• 提高管理效率(Improve management efficiency)

• 提高服務水平(Improve service levels)

• 復雜的體系結構(Complex architecture)

• 商業(yè)模式和理念的轉變(Change of business model and faith)

• 用戶端負載降低(Lower client workload)

• 降低總體擁有成本(Lower Total Cost Ownership)

• 可能將應用的開發(fā)與基礎設施維護相對分離(Separation of infrastructure maintenance duties from domain-specific application development)

• 可能將程序代碼與物理資源分離(Separation of application code from physical resources)

• 不需要為一次性任務或罕見的負載狀況準備大量設備(Not have to purchase assets for one-time or infrequent intensive computing tasks)

• 按需擴展資源(Expand resource on-demand)

• 使應用具有高可用性(Make the application have high availability)

• 快速部署應用(Quickly deploy application)

• 按使用付費(Pay per use)

• 自愈合(Self-healing)

• 多用戶使用(Multi-tenancy)

• 虛擬化(Virtualized)

• 線形擴展(Linearly ScalableLinearly Scalable)

• 資源監(jiān)控和測量(Resource Monitor and measure)

• 資源注冊和發(fā)現(xiàn)(Resource registration and discovery)

云計算正成為行業(yè)中的熱點概念。它和下面的詞匯產生了或多或少的關連：網(wǎng)格計算，效用計算，虛擬化，服務器集群，主機租用，主機托管。云計算平臺普遍用到了虛擬化技術，并且基于一個集群來構建，和網(wǎng)格計算和效用計算以及SaaS有著天然的聯(lián)系，而且被用在IDC行業(yè)與主機租用和主機托管業(yè)務競爭。(Cloud computing’s brother buzzwords:Cloud computing is becoming one of the next industry buzz words. And it has more or less relation with these words: grid computing, utility computing, virtualization, server cluster, Dedicated server, Colocation. Cloud computing infrastructure usually use virtualization technology, and is built based on a server cluster, have nature relation to grid computing and utility computing, and is use to compete with Dedicated server and Colocation.)

云計算異軍突起

相對與云計算的兄弟概念而言，云計算只是剛剛興起。從Google Trend 獲取的信息我們可以看到，云計算在2007年末才被該系統(tǒng)統(tǒng)計，并且一直處于上升趨勢。而同時，網(wǎng)格計算、效用計算、分布式計算的概念卻呈現(xiàn)下降趨勢。云計算和虛擬化應該會在托管平臺上有所作為，而主機租用已經(jīng)呈現(xiàn)下降趨勢。(Cloud computing break out:Compared to its brother buzzwords, cloud computing is just beginning. Trends in usage of the terms from Google searches shows Cloud Computing is a relatively new term introduced in the past year. There has also been a decline in general interest of Grid, Utility and Distributed computing. Cloud Computing and Virtualization are the next hot hosting platforms; the Dedicated server term is slowly starting to lose ground vs. Virtualization and Cloud Computing.)

云計算和效用計算的比較

效用計算是一種提供計算資源的商業(yè)模式，用戶從計算資源供應商獲取和使用計算資源并基于實際使用的資源付費。簡單說，是一種基于資源使用量的付費模式。效用計算主要給用戶帶來經(jīng)濟效益。企業(yè)數(shù)據(jù)中心的資源利用率普遍在20%左右，這主要是因為超額部署—購買比平均所需資源更多的硬件一邊處理峰值負載，可預計到的或不可預計的。效用計算則允許用戶只為他們所需要用到并且已經(jīng)用到的那部分資源付費。（Utility computing is a business model of providing computing resource， user get and use the computing resource from service provider and pay for practically used resource. To say it simply, it is a price model based on resource usage quantity. The main benefit of utility computing is better economics. Corporate data centers are notoriously underutilized, with resources such as servers often idle 85 percent of the time. This is due to overprovisioning — buying more hardware than is needed on average in order to handle peaks (such as the opening of the Wall Street trading day or the holiday shopping season), to handle expected future loads and to prepare for unanticipated surges in demand. Utility computing allows companies to only pay for the computing resources they need, when they need them.）

效用計算是是一種分發(fā)應用所需資源的計費模式。 云計算是一種計算模式， 代表了在某種程度上共享資源進行設計、開發(fā)、部署、運行應用，以及資源的可擴展收縮和對應用連續(xù)性的支持。效用計算通常需要云計算基礎設施支持，但并不是一定需要。同樣，在云計算之上可以提供效用計算，也可以不采用效用計算。（Comparison of Utility Computing and Cloud Computing：Utility computing is a business model, it is a type of price model to deliver application infrastructure resource. Cloud computing is a computing model, relates to the way we design, build, deploy and run applications that operate in a sharing resources and boasting the ability to dynamically grow, shrink and self-heal. Utility computing is often need a cloud computing infrastructure, but not must need. Sameness, above the cloud computing, we can adopt utility computing, and, we can adopt other price model.）^[6][7][8]

分布式計算

分布式計算是指在一個松散或嚴格約束條件下使用一個硬件和軟件系統(tǒng)處理任務，這個系統(tǒng)包含多個處理器單元或存儲單元，多個并發(fā)的過程，多個程序。一個程序被分成多個部分，同時在通過網(wǎng)絡連接起來的計算機上運行。分布式計算類似于并行計算，但并行計算通常用于指一個程序的多個部分同時運行于某臺計算機上的多個處理器上。所以，分布式計算通常必須處理異構環(huán)境、多樣化的網(wǎng)絡連接、不可預知的網(wǎng)絡或計算機錯誤。(Distributed Computing:Distributed computing deals with hardware and software systems containing more than one processing element or storage element, concurrent processes, or multiple programs, running under a loosely or tightly controlled regime.In distributed computing， a program is split up into parts that run simultaneously on multiple computers communicating over a network. Distributed computing is a form of parallel computing, but parallel computing is most commonly used to describe program parts running simultaneously on multiple processors in the same computer. Both types of processing require dividing a program into parts that can run simultaneously, but distributed programs often must deal with heterogeneous environments, network links of varying latencies, and unpredictable failures in the network or the computers.)^[9][10]

云計算與網(wǎng)格計算的不同點

網(wǎng)格計算是指分布式計算中兩類比較廣泛使用的子類型。一類是，在分布式的計算資源支持下作為服務被提供的在線計算或存儲。另一類是，一個松散連接的計算機網(wǎng)絡構成的一個虛擬超級計算機，可以用來執(zhí)行大規(guī)模任務。該技術通常被用來通過志愿者計算解決計算敏感型的科研、數(shù)學、學術問題，也被商業(yè)公司用來進行電子商務和網(wǎng)絡服務所需的后臺數(shù)據(jù)處理、經(jīng)濟預測、地震分析等。(Grid computing:Grid computing is a term for either of two broad subcategories of distributed computing: 1 Online computation or storage offered as a service supported by a pool of distributed computing resources, also known as utility computing, on-demand computing, or cloud computing. Data grids provide controlled sharing and management of large amounts of distributed data, often used in combination with computational grids. 2 The creation of a "virtual supercomputer" composed of a network of loosely-coupled computers, acting in concert to perform very large tasks. This technology has been applied to computationally-intensive scientific, mathematical, and academic problems through volunteer computing, and it is used in commercial enterprises for such diverse applications as drug discovery, economic forecasting, seismic analysis, and back-office data processing in support of e-commerce and web services.^[11]

網(wǎng)格計算強調資源共享，任何人都可以做為請求者使用其它節(jié)點的資源，任何人都需要貢獻一定資源給其他節(jié)點。網(wǎng)格計算強調將工作量轉移到遠程的可用計算資源上。云計算強調專有，任何人都可以獲取自己的專有資源，并且這些資源是由少數(shù)團體提供的，使用者不需要貢獻自己的資源。在云計算中，計算資源被轉換形式去適應工作負載，它支持網(wǎng)格類型應用，也支持非網(wǎng)格環(huán)境，比如運行傳統(tǒng)或Web2.0應用的三層網(wǎng)絡架構。

網(wǎng)格計算側重并行的計算集中性需求，并且難以自動擴展。云計算側重事務性應用，大量的單獨的請求，可以實現(xiàn)自動或半自動的擴展。(Grid computing emphasizes on resource sharing, every grid node can apply for resource from other nodes, and every node should contribute resource to the grid. The focus of grid computing is on the ability of moving a workload to the location of theneeded computing resources, which are mostly remote and are readily available for use.Grids also require applications to conform to the grid software interfaces.Cloud computing emphasize on proprietary, every user out of the cloud can get it’s own private resource from the cloud, and the cloud resource are provided by the specific service provider, the user need not contribute its resource. In a cloud environment, computing resouces, such as servers, can be dynamically shaped or carved out from its underlying hardware infrastructure and made available to a workload. In addition, while a cloud does support grid, a cloud can also support nongrid environments,such as a three-tier Web architecture running traditional or Web 2.0 applications.Grid computing emphasizes on computing sensitive task, and is difficult to automated scale. Cloud computing emphasizes on transactional application, a great amount of separate request, and can scale automatically or semiautomatically.)^[12][13][14]

服務器集群

服務器集群是指將一組服務器關聯(lián)起來，使它們在外界從很多方面看起來如同一臺服務器。集群內的服務器之間通常通過局域網(wǎng)連接，通常用來改善性能和可用性，但一般而言比具有同等性能功能和可用性的單臺主機具有更低的成本。(Computer cluster:A computer cluster is a group of coupled computers that work together closely so that in many respects they can be viewed as though they are a single computer. The components of a cluster are commonly, but not always, connected to each other through fast local area networks. Clusters are usually deployed to improve performance and/or availability over that provided by a single computer, while typically being much more cost-effective than single computers of comparable speed or availability.^[15])

網(wǎng)格通常更加松散連接、異構、地理位置分散，主機之間信任度更低。(Grids tend to be more loosely coupled, heterogeneous, and geographically dispersed, grid computers do not fully trust each other.)

虛擬化

虛擬化指對計算資源進行抽象的一個廣義概念。虛擬化對上層應用或用戶隱藏了計算資源的底層屬性。它既包括使單個的資源（比如一個服務器，一個操作系統(tǒng)，一個應用程序，一個存儲設備）劃分成多個虛擬資源，也包括將多個資源（比如存儲設備或服務器）整合成一個虛擬資源。虛擬化技術是指實現(xiàn)虛擬化的具體的技術性手段和方法的集合性概念。虛擬化技術根據(jù)對象可以分成存儲虛擬化、計算虛擬化、網(wǎng)絡虛擬化等。計算虛擬化可以分為操作系統(tǒng)級虛擬化，應用程序級，和虛擬機管理器。虛擬機管理器分為宿主虛擬機和客戶虛擬機。(Virtualization:Virtualization is a broad term that refers to the abstraction of computer resources. Virtualization hides the physical characteristics of computing resources from their users, be they applications, or end users.^[15] This includes making a single physical resource (such as a server, an operating system, an application, or storage device) appear to function as multiple virtual resources; it can also include making multiple physical resources (such as storage devices or servers) appear as a single virtual resource.^[15] Virtualization technology is a aggregative term of technical means and methods to implement virtualization. It can be divided to many types based on objects: storage virtualization, computing virtualization, network virtualization. Computing virtualization include：OS level virtualization, application level virtualization, hyper visor. Hypervisor include: host vm and guest vm.)

• 連續(xù)高可用性(Continuous high availability)
  • 某個集群的失效處理

• 一致性(Consistency)
  • 不同集群的同步

• 互操作性和標準化(Interoperability and standarlization)
  • 在萌芽和成長期，各廠商都試圖建立自己的接口API

• 所有構件的擴展(Scalability of all components)

• 信息保密(Data secrecy)

• 跨地區(qū)存儲和數(shù)據(jù)傳輸可能會引發(fā)法律和政治問題(Legal and political problem of data store and translation across regions)

• 性能問題(Performance issue)

• 差異化定制問題(Difficulty customizing)

• 組織障礙(Organizational obstacle)

云計算平臺一般分為以下幾層：物理設施，虛擬化，管理，服務提供。物理設施被虛擬化，提供一個靈活的資源池體提高資源利用率。管理層負責物理資源和虛擬資源池的管理、部署、監(jiān)控、報警等。服務提供層組合管理層的功能提供某種形式的服務。(he physical hardware layer is virtualized to provide a flexible adaptive platform to improve resource utilization. The keys to new enterprise data center infrastructure services are the next two layers, the virtualization environment and management layer. The combination of these two layers ensure that resources in a data center are efficiently managed and can be provisioned, deployed, and configured rapidly.)

1. The NY Times(Amazon EC2)

2. Nasdaq(Amazon S3)

3. Major League Baseball(Joyent)

4. ESPN(Rightscale using Amazon EC2)

5. Hasbro(Amazon EC2)

6. British Telecom(3Tera)

7. Taylor Woodrow(Google Apps)

8. CSS(Amazon EC2)

9. Activision(Amazon EC2)

10. Business Objects (A SAP Company)(Rightscale using Amazon EC2)

云計算技術和方案提供者

• 3Tera - AppLogic grid OS used as cloud computing platform by service providers and enterprises

• Appistry - Cloud computing middleware - Enables easily scalable cloud computing in the enterprise.

• Cassatt - Cassatt Active Response platform enables administrators to set policies to power physical and virtual servers safely on and off and pool their computing resources.

• CloudScale Networks - Cloud enabler. Currently in private ALPHA only

• CloudHan - Cloud tech and infrastructure consultant, in China.

• Enomaly Inc - Service Provider & Cloud Enabler - Developer of the Enomalism Elastic Computing Platform & Elastic Drive

• Q-layer - provides software for data centers that enables cloud computing, support VSAN, VLAN, VPDC, currently support VMware ESX.

• Skytap - IaaS service optimized for QA, Training, Demo, and Ops Testing. Supports VMware, Xen hypervisors & Windows, Linux & Solaris OS guests.

云計算基礎設施層服務

• Agathon Group - Cloud provider. Services include highly available VPS, virtual private datacenters and ready-to-use LAMP stacks. Self-service ordering. Custom development and managed services available.

• Amazon Web Services - Amazon EC2/S3 (Hardware-a-a-S & Cloud Storage)

• CohesiveFT - CohesiveFT Elastic Server On-Demand

• ElasticHosts - UK-based instant, on-demand servers in the cloud

• Flexiscale - Another instant provisioner of web servers with some advanced features like auto-scaling coming soon.

• GoGrid - instant, on-demand servers offering "control in the cloud". Deploy Windows/Linux servers via web-interface in minutes

• GridLayer - Cloud Provider. A service by Layered Technologies that delivers Virtual Private Datacenters and virtual private servers from grids of commodity servers

• LayeredTechnologies - Cloud Provider. provider of on-demand hosting and cloud and utility computing solutions through its brand GridLayer

• Mosso - Rackspace's cloud hosting service

• Newservers - Instant provisioning of web servers either Windows or Linux

云計算平臺層服務

• Bungee Connect - Provides end to end tools and systems required to develop, deploy and host web applications (Platform as a Service)

• Coherence - Oracle Coherence Data Grid for EC2 and other cloud platforms

• Force.com - Salesforce.com's application development platform (PaaS)

• GigaSpaces - middleware for the cloud, "cloudware"

• Google AppEngine - (PaaS)Now support python

• Heroku - Ruby on Rails in their Cloud

• Qrimp - An AJAX based PaaS

• RightScale - RightScale provides a platform and expertise that enable companies to create scalable web applications running on Amazon’s Web Services that are reliable, easy to manage, and cost less

基于云計算的服務（Saas，云存儲）

• CAM Solutions - SaaS Provider. Cloud Event Management, Autonomics and Monitoring-as-a-Service(TM)

• CloudStatus- CloudEnabler. Real-time performance trending of cloud infrastructure (currently AWS).

• Kaavo's IMOD is an easy to use online application. Cloud Computing Made Easy.

• Microsoft Mesh

• Nasstar - SaaS provider. Business grade Hosted Desktop service, UK market leaders.

• Nirvanix - Cloud Storage

• TrustSaaS - uptime monitoring and alerting service ('SaaS Weather Report') for Software as a Service (SaaS) run by an independent third party.

Enomalism, convirt, redhat genome, hyperVM, lxlabs, LN, OpenNEbula, reservoir-fp7, scalr,eucalyptus,ganeti,gplhost，ovirt。

Useful open source projects to build cloud platform:

Kenso, hyperic, virt-P2V。

• 優(yōu)先訪問權風險(Privileged user access.)

• 管理權限風險(Regulatory compliance.)

• 數(shù)據(jù)處所風險(Data location.)

• 數(shù)據(jù)隔離風險(Data segregation.)

• 數(shù)據(jù)恢復風險(Recovery.)

• 調查支持風險(Investigative support.)

• 長期發(fā)展風險(Long-term viability.)

下面是Dell描述的云計算模型：

解釋：

這是一個明顯學術化的模型圖，就像ISO七層網(wǎng)絡模型，永遠只有參考意義。

相比而言，下面這個示意圖更具有表現(xiàn)力：

下面是DELL描述的一個數(shù)據(jù)中心

事實上，這個數(shù)據(jù)中心和傳統(tǒng)的數(shù)據(jù)中心看起來沒有很大的不同，云計算的含義是不能通過一個數(shù)據(jù)中心示意圖來表達的。

市場分為如下幾個層次：

• Cloud Computing
• Platform as a Service (PaaS)
• Software as a Service (SaaS)
• Core Cloud Services

解釋如下：

• Infrastructure: the core computing resources and network fabric for the cloud deployment
• Platform: the software infrastructure that allows sys admins and developers to deploy an app to the cloud
• Core Services: additional services that can be woven into the cloud app, such as billing, storage, integration
• Applications: the ultimate cloud product - the actual cloud based application that the user touches. These number in the thousands.

市場視圖

下面是市場參與者列表：

• Public Cloud
  • Amazon EC2
  • ServePath GoGrid
  • Rackspace Mosso Cloud
  • Joyent Accelerators
  • AppNexus
  • Flexiscale
  • ElasticHosts
• Private Cloud
  • Eucalyptus
  • Cassatt Active Response
  • Enomaly Enomalism Platform
  • Grid
    • Globus Toolkit
    • Beowulf
    • Sun Project Caroline
• Open Cloud Platforms
  • Heroku
  • Morph Labs
  • Aptana CloudStudio
• Custom Cloud Platforms
  • Salesforce.com force.com
  • Google App Engine
  • Bungee Labs Connect
  • Intuit Quickbase
  • LongJump
  • Coghead
• Cloud Platform Tools
  • Fabric Mgmt
    • Rightscale
    • Scalr
    • Elastra Cloud Server
    • 3Tera AppLogic
    • Kaavo IMOD
  • Data Grids
    • Oracle Coherence
    • IBM eXtreme Scale
    • GigaSpaces Data Grid
    • Gemstone Gemfire
  • Virtual Appliances
    • rPath
    • CohesiveFT
  • Hyperic CloudStatus
  • Hadoop
• Storage
  • Amazon S3
  • Amazon SimpleDB
  • Microsoft SSDS
  • Rackspace Mosso CloudFS
  • Google BigTable
• Integration
  • Bungee Labs Connect
  • Boomi
  • MuleSource Mule OnDemand
  • Amazon SQS
  • Microsoft BizTalk Services
  • OpSource Connect
  • SnapLogic SaaS Solution Packs
  • gnip
  • CastIron
  • Appirio
  • Skemma
  • Appian Anywhere
• Value-Add
  • Billing
    • OpSource Billing
    • Aria
    • eVapt
    • Zuora
    • Vindicia
  • Security
    • Ping Identity
    • OpenID/OAuth
  • Strikeiron
• Applications
  • Salesforce.com
  • Netsuite
  • Taleo
  • Oracle OnDemand
  • Concur
  • Google Apps ^[18]