The Nature of Cloud Computing

Posted on July 14th, 2009
A blog post by DN (4 Comments)

Building on established trends
Cloud computing builds on established trends for driving the cost out of the delivery of services while increasing the speed and agility with which services are deployed. It shortens the time from sketching out an application architecture to actual deployment. Cloud computing incorporates virtualization, on-demand deployment, Internet delivery of services, and open source software. From one perspective, cloud
computing is nothing new because it uses approaches, concepts, and best practices that have already been established. From another perspective, everything is new because cloud computing changes how we invent, develop, deploy, scale, update, maintain, and pay for applications and the infrastructure on which they run. In this chapter, we examine the trends and how they have become core to what cloud
computing is all about.
Virtual machines as the standard deployment object
Over the last several years, virtual machines have become a standard deployment object. Virtualization further enhances flexibility because it abstracts the hardware to the point where software stacks can be deployed and redeployed without being tied to a specific physical server. Virtualization enables a dynamic datacenter where servers provide a pool of resources that are harnessed as needed, and where the
relationship of applications to compute, storage, and network resources changes dynamically in order to meet both workload and business demands. With application deployment decoupled from server deployment, applications can be deployed and scaled rapidly, without having to first procure physical servers.
Virtual machines have become the prevalent abstraction — and unit of deployment — because they are the least-common denominator interface between service providers and developers. Using virtual machines as deployment objects is sufficient for 80 percent of usage, and it helps to satisfy the need to rapidly deploy
and scale applications. Virtual appliances, virtual machines that include software that is partially or fully
configured to perform a specific task such as a Web or database server, further enhance the ability to create and deploy applications rapidly. The combination of virtual machines and appliances as standard deployment objects is one of the key features of cloud computing. Compute clouds are usually complemented by storage clouds that provide virtualized storage through APIs that facilitate storing virtual machine images, source files for components such as Web servers, application state data, and general business data.

The on-demand, self-service, pay-by-use model
The on-demand, self-service, pay-by-use nature of cloud computing is also an extension of established trends. From an enterprise perspective, the on-demand nature of cloud computing helps to support the performance and capacity aspects of service-level objectives. The self-service nature of cloud computing allows organizations to create elastic environments that expand and contract based on the workload and target performance parameters. And the pay-by-use nature of cloud computing may take the form of equipment leases that guarantee a minimum level of service from a cloud provider. Virtualization is a key feature of this model. IT organizations have understood for years that virtualization allows them to quickly and easily create copies of existing environments —sometimes involving multiple virtual machines — to support test, development, and staging activities. The cost of these environments is minimal
because they can coexist on the same servers as production environments because they use few resources.
Likewise, new applications can be developed and deployed in new virtual machines on existing servers, opened up for use on the Internet, and scaled if the application is successful in the marketplace. This lightweight deployment model has already led to a “Darwinistic” approach to business development where beta versions of software are made public and the market decides which applications deserve to be
scaled and developed further or quietly retired. Cloud computing extends this trend through automation. Instead of negotiating with an IT organization for resources on which to deploy an application, a compute
cloud is a self-service proposition where a credit card can purchase compute cycles, and a Web interface or API is used to create virtual machines and establish network relationships between them. Instead of requiring a long-term contract for services with an IT organization or a service provider, clouds work on a pay-by-use, or payby-the-sip model where an application may exist to run a job for a few minutes or hours, or it may exist to provide services to customers on a long-term basis. Compute clouds are built as if applications are temporary, and billing is based on resource consumption: CPU hours used, volumes of data moved, or gigabytes of data stored. The ability to use and pay for only the resources used shifts the risk of how much
infrastructure to purchase from the organization developing the application to the cloud provider. It also shifts the responsibility for architectural decisions from application architects to developers. This shift can increase risk, risk that must be managed by enterprises that have processes in place for a reason, and of system, network, and storage architects that needs to factor in to cloud computing designs.
Infrastructure is programmable
This shift of architectural responsibility has significant consequences. In the past, architects would determine how the various components of an application would be laid out onto a set of servers, how they would be interconnected, secured, managed, and scaled. Now, a developer can use a cloud provider’s API to create not only an application’s initial composition onto virtual machines, but also how it scales and
evolves to accommodate workload changes. Consider this analogy: historically, a developer writing software using the Java™ programming language determines when it’s appropriate to create new threads to
allow multiple activities to progress in parallel. Today, a developer can discover and attach to a service with the same ease, allowing them to scale an application to the point where it might engage thousands of virtual machines in order to accommodate a huge spike in demand.
The ability to program an application architecture dynamically puts enormous power in the hands of developers with a commensurate amount of responsibility. To use cloud computing most effectively, a developer must also be an architect, and that architect needs to be able to create a self-monitoring and self-expanding application. The developer/architect needs to understand when it’s appropriate to create a new thread versus create a new virtual machine, along with the architectural patterns for
how they are interconnected. When this power is well understood and harnessed, the results can be spectacular. A story that is already becoming legendary is Animoto’s mashup tool that creates a
video from a set of images and music. The company’s application scaled from 50 to 3,500 servers in just three days due in part to an architecture that allowed it to scale easily. For this to work, the application had to be built to be horizontal scaled, have limited state, and manage its own deployment through cloud APIs. For every success story such as this, there will likely be a similar story where the application is not
capable of self-scaling and where it fails to meet consumer demand. The importance of this shift from developer to developer/architect cannot be understated. Consider whether your enterprise datacenter could scale an application this rapidly to accommodate such a rapidly growing workload, and whether cloud computing could augment your current capabilities.
Applications are composed and are built to be composable
Another consequence of the self-service, pay-by-use model is that applications are composed by assembling and configuring appliances and open-source software as much as they are programmed. Applications and architectures that can be refactored in order to make the most use of standard components are those that will be the most successful in leveraging the benefits of cloud computing. Likewise, application
components should be designed to be composable by building them so they can be consumed easily. This requires having simple, clear functions, and well-documented APIs. Building large, monolithic applications is a thing of the past as the library of existing tools that can be used directly or tailored for a specific use becomes ever larger.
For example, tools such as Hadoop, an open-source MapReduce implementation, can be used in a wide range of contexts in which a problem and its data can be refactored so that many parts of it can execute in parallel. When The New York Times wished to convert 11 million articles and images in its archive to PDF format, their internal IT organization said that it would take seven weeks. In the mean time, one
developer using 100 Amazon EC2 simple Web service interface instances running Hadoop completed the job in 24 hours for less than $300. (This did not include the time required to upload the data or the cost of the storage.)
Even large corporations can use cloud computing in ways that solve significant problems in less time and at a lower cost than with traditional enterprise computing.
Example Web application deployment
As an example of how the combination of virtualization and self service facilitate application deployment, consider a two-tier Web application deployment into a cloud (Figure 1):
1. A developer might choose a load balancer, Web server, and database server appliances from a library of preconfigured virtual machine images.
2. The developer would configure each component to make a custom image. The load balancer would be configured, the Web server populated with its static content by uploading it to the storage cloud, and the database server appliances populated with dynamic content for the site.
3. The developer layers custom code into the new architecture, making the components meet specific application requirements.
4. The developer chooses a pattern that takes the images for each layer and deploys them, handling networking, security, and scalability issues.

Example cloud-based deployment of an application onto a two-tier Web server architectural pattern.

For a description of how this feat was
accomplished, please visit: http://open.
blogs.nytimes.com/2007/11/01/self-serviceprorated-
super-computing-fun/

5. The secure, high-availability Web application is up and running. When the application needs to be updated, the virtual machine images can be updated, versioned, copied across the development-test-production chain, and the entire infrastructure redeployed. Cloud computing assumes that everything is
temporary, and it’s just as easy to redeploy an entire application than it is to manually patch a set of individual virtual machines. In this example, the abstract nature of virtual machine images supports a
composition-based approach to application development. By refactoring the problem, a standard set of components can be used to quickly deploy an application. With this model, enterprise business needs can be met quickly, without the need for the time-consuming, manual purchase, installation, cabling, and configuration of servers, storage, and network infrastructure.
Services are delivered over the network
It almost goes without saying that cloud computing extends the existing trend of making services available over the network. Virtually every business organization has recognized the value of Web-based interfaces to their applications, whether they are made available to customers over the Internet, or whether they are internal applications that are made available to authorized employees, partners, suppliers,
and consultants. The beauty of Internet-based service delivery, of course, is that applications can be made available anywhere, and at any time. While enterprises are well aware of the ability to secure communications
using Secure Socket Layer (SSL) encryption along with strong authentication, bootstrapping trust in a cloud computing environment requires carefully considering the differences between enterprise computing and cloud computing. When properly architected, Internet service delivery can provide the flexibility and security required by enterprises of all sizes.
The role of open source software
Open source software plays an important role in cloud computing by allowing its basic software elements — virtual machine images and appliances — to be created from easily accessible components. This has an amplifying effect:
• Developers, for example, can create a database appliance by layering MySQL software onto an instance of the OpenSolaris™ Operating System and performing customizations (Figure 2). Appliances such as these enable cloud computing applications to be created, deployed, and dynamically scaled on demand. Consider, for example, how open source software allows an application such as that created by Animoto to scale to 3,500 instances in a matter of days.

Figure 2. Appliances can be created by layering open source software into a virtual machine image and performing customizations that simplify their deployment. In this example, a database appliance is created by layering MySQL software on top of the OpenSolaris Operating System.
• The ease with which open source components can be used to assemble large applications generates more open source components. This, in turn, makes the role of open source software even more important. The need, for example, to have a MapReduce algorithm that can run in a cloud-computing environment, was one
of the factors stimulating its development. Now that the tool has been created, it is being used to further raise the level at which developers ‘program’ cloud computing applications.