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Essential Cloud Computing Characteristics
According to NIST the cloud model is composed of five essential characteristics, three service models, & four deployment models

If you ask five different experts you will get maybe five different opinions what cloud computing is. And all five may be correct. The best definition of cloud computing that I have ever found is the National Institute of Standards and Technology Definition of Cloud Computing. According to NIST the cloud model is composed of five essential characteristics, three service models, and four deployment models. In this post I will look at the essential characteristics only, and compare to the traditional computing models; in future posts I will look at the service and deployment models.

Because computing always implies resources (CPU, memory, storage, networking etc.), the premise of cloud is an improved way to provision, access and manage those resources. Let's look at each essential characteristic of the cloud:

On-Demand Self-Service
Essentially what this means is that you (as a consumer of the resources) can provision the resources at any time you want to, and you can do this without assistance from the resource provider.

Here is an example. In the old days if your application needed additional computing power to support growing load, the process you normally used to go through is briefly as follows: call the hardware vendor and order new machines; once the hardware is received you need to install the Operating System, connect the machine to the network, configure  any firewall rules etc.; next, you need to install your application and add the machine to the pool of other machines that already handle the load for your application. This is a very simplistic view of the process but it still requires you to interact with many internal and external teams in order to complete it - those can be but are not limited to hardware vendors, IT administrators, network administrators, database administrators, operations etc. As a result it can take weeks or even months to get the hardware ready to use.

Thanks to the cloud computing though you can reduce this process to minutes. All this lengthy process comes to a click of a button or a call to the provider's API and you can have the additional resources available within minutes without. Why is this important?

Because in the past the process involved many steps and usually took months, application owners often used to over provision the environments that host their application. Of course this results in huge capital expenditures at the beginning of the project, resource underutilization throughout the project, and huge losses if the project doesn't succeed. With cloud computing though you are in control and you can provision only enough resources to support your current load.

Broad Network Access
Well, this is not something new - we've had the Internet for more than 20 years already and the cloud did not invent this. And although NIST talks that the cloud promotes the use of heterogeneous clients (like smartphones, tablets etc.) I do think this would be possible even without the cloud. However there is one important thing that in my opinion  the cloud enabled that would be very hard to do with the traditional model. The cloud made it easier to bring your application closer to your users around the world. "What is the difference?", you will ask. "Isn't it that the same as Internet or the Web?" Yes and no. Thanks to the Internet you were able to make your application available to users around the world but there were significant differences in the user experience in different parts of the world. Let's say that your company is based on California and you had a very popular application with millions of users in US. Because you are based in California all servers that host your application are either in your basement or in a datacenter that is nearby so that you can easily go and fix any hardware issues that may occur. Now, think about the experience that your users will get across the country! People from East Coast will see slower response times and possibly more errors than people from the West. If you wanted to expand globally then this problems will be amplified. The way to solve this issue was to deploy servers on the East Cost and in any other part of the world that you want to expand to.

With cloud computing though you can just provision new resources in the region you want to expand to, deploy your application and start serving your users.

It again comes to the cost that you incur by deploying new data centers around the world versus just using resources on demand and releasing them if you are not successful. Because the cloud is broadly accessible you can rely on having the ability to provision resources in different parts of the world.

Resource Pooling
One can argue whether resource pooling is good or bad. The part that brings most concerns among users is the colocation of application on the same hardware or on the same virtual machine. Very often you can hear that this compromises security, can impact your application's performance and even bring it down. Those have been real concerns in the past but with the advancement in virtualization technology and the latest application runtimes you can consider them outdated. That doesn't mean that you should not think about security and performance when you design your application.

The good side of the resource pooling is that it enabled cloud providers to achieve higher application density on single hardware and much higher resource utilization (sometimes going up to 75% to 80% compared to the 10%-12% in the traditional approach). As a result of that the price for resource usage continues to fall. Another benefit of the resource pooling is that resources can easily be shifted where the demand is without the need for the customer to know where those resources come from and where are they located. Once again, as a customer you can request from the pool as many resources as you need at certain time; once you are done utilizing those you can return them to the pool so that somebody else can use them. Because you as a customer are not aware what the size of the resource pool is, your perception is that the resources are unlimited. In contrast in the traditional approach the application owners have always been constrained by the resources available on limited number of machines (i.e. the ones that they have ordered and installed in their own datacenter).

Rapid Elasticity
Elasticity is tightly related to the pooling of resources and allows you to easily expand and contract the amount of resources your application is using. The best part here is that this expansion and contraction can be automated and thus save you money when your application is under light load and doesn't need many resources.

In order to achieve this elasticity in the traditional case the process would look something like this: when the load on your application increases you need to power up more machines and add them to the pool of servers that run your application; when the load on your application decreases you start removing servers from the pool and then powering them off. Of course we all know that nobody is doing this because it is much more expensive to constantly add and remove machines from the pool and thus everybody runs the maximum number of machines all the time with very low utilization. And we all know that if the resource planning is not done right and the load on the application is so heavy that the maximum number of machines cannot handle it, the result is increase of errors, dropped request and unhappy customers.

In the cloud scenario where you can add and remove resource within minutes you don't need to spend a great deal of time doing capacity planning. You can start very small, monitor the usage of your application and add more and more resources as you grow.

Measured Service
In order to make money the cloud providers need the ability to measure the resource usage. Because in most cases the cloud monetization is based on the pay-per-use model they need to be able to give the customers break down of how much and what resources they have used. As mentioned in the NIST definition this allows transparency for both the provider and the consumer of the service.

The ability to measure the resource usage is important in to you, the consumer of the service, in several different ways. First, based on historical data you can budget for future growth of your application. It also allows you to better budget new projects that deliver similar applications. It is also important for application architects and developers to optimize their applications for lower resource utilization (at the end everything comes to dollars on the monthly bill).

On the other side it helps the cloud providers to better optimize their datacenter resources and provide higher density per hardware. It also helps them with the capacity planning so that they don't end up with 100% utilization and no excess capacity to cover unexpected consumer growth.

Compare this to the traditional approach where you never knew how much of your compute capacity is utilized, or how much of your network capacity is used, or how much of your storage is occupied. In rare cases companies were able to collect such statistics but almost never those have been used to provide financial benefit for the enterprise.

Having those five essential characteristics you should be able to recognize the "true" cloud offerings available on the market. In the next posts I will go over the service and deployment models for cloud computing.

Read the original blog entry...

About Toddy Mladenov

Toddy Mladenov has more than 15 years experience in software development and technology consulting at companies like Microsoft, SAP and 3Com. Currently he is a CTO of Agitare Technologies, Inc. - a boutique consulting company that specializes in Cloud Computing and Big Data Solutions. Before Agitare Tech Toddy spent few years with PaaS startup Apprenda and more than six years working on Microsft's cloud computing platform Windows Azure, Windows Client and MSN/Windows Live. During his career at Microsoft he managed different aspects of the software development process for Windows Azure and Windows Services. He also evangelized Microsoft cloud services among open source communities like PHP and Java. In the past he developed enterprise software for German's software giant SAP and several startups in Europe, and managed the technical sales for 3Com in the Balkan region.

With his broad industry experience, international background and end-user point of view Toddy has an unique approach towards technology. He believes that technology should be develop to improve people's lives and is eager to share his knowledge in topics like cloud computing, mobile and web development.



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Cloud Expo - Cloud Looms Large on SYS-CON.TV


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[June 11-14, 2012]

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Introducing Big Data Expo
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There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Get a jump on that rapidly evolving trend at Big Data Expo, which we are introducing in June at
Cloud Expo New York.

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Cloud Expo was a fantastic event for CSS Corp - we easily exceeded our objectives for engaging with clients and prospects."
AHMAR ABBAS
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With our launch at Cloud Expo, we successfully transformed the company from a relatively unknown European player into the dominant player in the market. Our competitors were taken by surprise and just blown away. We got a huge number of really high quality leads..."
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We were extremely pleased with Cloud Expo this year - I’d say it exceeded expectations all around. This is the same info we got from partners who attended as well. Nice job!"
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@CloudExpo Blogs
Microsoft took another step toward being king of the cloud hill when it announced in January that it was releasing its Azure stack to the public. There are many technical reasons why this is cool, but more importantly, it's the psychological advantage this gives Microsoft. Google has always had the ability for developers using its stack to develop locally on the same tools that run in Google App Engine. It recently forked its environments, so now the local and cloud environments are slightly different for some of the configurations -- I can't tell you how many nights I have lost sleep becaus...
Right off the bat, Newman advises that we should "think of microservices as a specific approach for SOA in the same way that XP or Scrum are specific approaches for Agile Software development". These analogies are very interesting because my expectation was that microservices is a pattern. So I might infer that microservices is a set of process techniques as opposed to an architectural approach. Yet in the book, Newman clearly includes some elements of concept model and architecture as well as process and organization.
Companies are exploiting technology advances in procurement and finance services to produce new types of productivity benefits. We'll now hear from a procurement expert on how companies can better manage their finances and have tighter control over procurement processes and their supply chain networks. This business process innovation exchange comes to you in conjunction with the Tradeshift Innovation Day held in New York on June 22, 2016.
Infrastructure complexity is not unique to enterprise datacenters. Just because a business or organization is small does not mean it is exempt from the feature needs of big enterprise datacenters. Small and mid-size organizations require fault tolerance, high availability, mobility, and flexibility as much as anyone. Unfortunately, the complexity of traditional datacenter and virtualization architecture hit the SMB the hardest.
Digital transformation typically begins as low cost POCs (proof of concepts), that evolve into mission critical corporate initiatives as positive results, consumer demands and market trends converge. Digital transformation becomes mission critical when consumers vote with their money to accept the digital replacements for physical products, services and processes.
Big Data. Analytics. Internet of Things. Cloud. In the last few years, you cannot have a discussion around technology without those terms entering the conversation. They have been major technology disruptors impacting all aspects of the business. Change seems to occur at breakneck speeds and shows no sign of slowing. Today, it appears the one constant in technology is change. Constant change requires constant innovation which thereby introduces more new technologies. One of the new technologies entering the conversation is machine learning. Gartner identified machine learning as one of the top...
I'm often guilty of sticking my head in the sand, ignoring very small details that could turn into big problems later on. Like when Netflix told me my credit card was about to expire, but it seemed like such a boring task, so I ignored them...till the day Netflix stopped working. I grumbled at the TV for awhile, then wasted another half hour remembering my login details and finding the credit card update page. Clearly, I should have followed the easy link in the first place. It was my oversight that led me to waste time and my good mood updating my info. I consider missing my favorite televis...
The Dean of the University of San Francisco School of Management, Elizabeth Davis, recently asked me to sit on a Big Data panel at the Direct Sales Association conference. I was given a 5-minute slot to “demystify” Big Data to a non-technical group of about 1,000 people; to help them understand where and how this thing called “Big Data” could help them. Well if you know me, I can barely introduce myself in 5 minutes. But this was particularly challenging for me, as I’m used to talking about Big Data with organizations with at least some level of Big Data experience or understanding (maybe the...
The Internet of Things (IoT) promises to change everything by enabling “smart” environments (homes, cities, hospitals, schools, stores, etc.) and smart products (cars, trucks, airplanes, trains, wind turbines, lawnmowers, etc.). I recently wrote about the importance of moving beyond “connected” to “smart” in a blog titled “Internet of Things: Connected Does Not Equal Smart”. The article discusses the importance of moving beyond just collecting the data, to transitioning to leveraging this new wealth of IoT data to improve the decisions that these smart environments and products need to make: t...
Continuous testing helps bridge the gap between developing quickly and maintaining high quality products. But to implement continuous testing, CTOs must take a strategic approach to building a testing infrastructure and toolset that empowers their team to move fast. Download our guide to laying the groundwork for a scalable continuous testing strategy.
When the Internet of Things (IoT) started to emerge as a popular topic, I had to stop and ask myself if I was once again going to provide commentary on this emerging field. I enjoy exploring new technology shifts and illustrating how they can benefit various industries and businesses. It’s what I’ve done for the past 20 years through Java, XML, Web Services, SOA, Cloud and DevOps. However, every time I started writing on IoT I seemed to run into the same conundrum; am I commenting on this to jump on the hype bandwagon or because I see a need to represent the pragmatics of implementing and adop...
The age of computers is over. You are now living in the age of intelligent processing by just about everything else. Like vacuum tubes and tape drives, desktops and laptops are on their way to becoming odd relics of a distant age, if people remember them at all. That may sound a bit extreme, but the fact is that applications are not married to any technological substrate, not even the most advanced mobile devices. That is why smart developers have already turned their attention to using JavaScript for building out next-generation technology like drone controllers, big data management tools, an...
It seems like every day we see reminders of the importance of thorough security testing from all areas of the software world. Security has become an especially critical consideration for APIs in recent years. Organizations rely on APIs to share and receive information - either from a third party or between internal applications - so the level of security between these applications is critical for anyone who uses them.
The data warehouse and data lake are two different types of data storage repository. The data warehouse integrates data from different sources and suits business reporting. The data lake stores raw structured and unstructured data in whatever form the data source provides. It does not require prior knowledge of the analyses you think you want to perform. A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. While a hierarchical data warehouse stores data in files or folders, a data lake uses a flat architecture to store data.
Opining about the future of AI at the recent Brilliant Minds event at Symposium Stockholm, Google Executive Chairman Eric Schmidt rejected warnings from Elon Musk and Stephen Hawking about the dangers of AI, saying, “In the case of Stephen Hawking, although a brilliant man, he’s not a computer scientist. Elon is also a brilliant man, though he too is a physicist, not a computer scientist.” This absurd dismissal of Musk and Hawking was in response to an absurd question about “the possibility of an artificial superintelligence trying to destroy mankind in the near future.” Schmidt went on to sa...
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Past SYS-CON Events
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Cloud Expo 2011 Allstar Conference Faculty

S.F.S.
Dell

Singer
NRO

Pereyra
Oracle

Ryan
OpSource

Butte
PwC

Leone
Oracle

Riley
AWS

Varia
AWS

Lye
Oracle

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AppZero

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RightScale

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Dell Boomi

Hillier
CiRBA

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Layer 7 Tech

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NYT

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Oracle

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