Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to facilitate the development of cloud data centers. Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge. The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues. After laying a foundation of cloud concepts and definitions, the book addresses data center creation, infrastructure development, cost modeling, and simulations in decision-making, each part building on the previous. In this way the authors bridge technology, management, and infrastructure as a service, in one complete guide to data centers that facilitates educated decision making.
- Explains how to balance cloud computing functionality with data center efficiency
- Covers key requirements for power management, cooling, server planning, virtualization, and storage management
- Describes advanced methods for modeling cloud computing cost including Real Option Theory and Monte Carlo Simulations
- Blends theoretical and practical discussions with insights for developers, consultants, and analysts considering data center development
Caesar Wu is a Senior Domain Specialist on Cloud Computing and Data Centers at Telstra, as well as a Principle Research Fellow, at The University of Melbourne, Australia. He has over 18 years' of experience in ICT architecture, solution design, services delivery and operation management, IT data center lifecycle and transformation. For the past five years he has been responsible for cost modeling of all Telstra cloud computing projects, for both enterprise and government clients, and designed and managed eight data centers in Australia. In 2012, Wu supervised three University of Melbourne PhD students in cloud computing strategic investment decision making.
Caesar Wu and Rajkumar Buyya, Melbourne, Australia, 2014
How can we measure the sky? This question sometimes refers to how to measure the cost of cloud computing. For many people, it is a very challenging and tough question. And yet, many C-class senior executives (CEO, CFO, and CIO), stakeholders, and cloud investors would not only want to know "how" (cost model assumptions and calculations), but also want to know "why" (logic behind these assumptions).
Why is this so important? The simple answer is it is too big to be ignored. We have heard many stories about how some decision makers just throw big money into cloud projects without proper understanding of cloud technology and expect to catch up to the "wind" (win). This book will lay out the basic concepts and foundation of cloud computing and data center facilities and then provide tools and practical approaches for decision makers to make the right strategic investment decisions. It will help the decision maker to not only rely on "gut feelings" or previous experiences but also count on the scientific method.
One of the goals of this book is to establish a practical framework to enable IT executives to make a rational choice when they are facing a multimillion-dollar investment decision for a cloud project, which is to determine whether IT workloads should stay local or fly to a cloud. (inhouse or cloud computing).
Almost five years ago, this challenging task was assigned to us because a senior IT executive wanted to justify a multimillion investment decision that he had already made but he was not sure whether the decision was a rational choice or not. The original idea of this exercise was to check his intuition, estimate the strategic value, communicate with all the stakeholders, and change the scope of the cloud investment project if necessary.
At that time, many trial projects of cloud computing, server virtualization, and software multitenancy had just taken off. Various companies made different investment decisions in order to test the water or get a foothold on the cloud market.
With these intentions in our mind plus many years' practical experience in cost modeling of utilities and grid computing, hosting services management, network design, construction, operation, lifecycles, and service delivery, we elicited eight basic questions about this cost modeling exercise:
What is the ultimate goal of measuring the sky?
How many cost models are there?
How can we make a logical and rational comparison with different models?
Why is the TCO/ROI model is so popular? If we use TCO/ROI, would it be the right choice?
What are the assumptions of these models?
How can I select the right model to fit a particular business need?
How can we establish both revenue- and nonrevenue-based cost models?
What are the risks of keeping the IT workload in house versus migrating to the cloud?
We believe that most people, whether they are cloud service providers or cloud service consumers, will also face similar questions if they are asked to measure "the sky" or to prepare a business case for a cloud investment project. From this perspective, this book is also targeted for IT business analysts and MBA students as reference material.
In essence, the core objective of this book is to demonstrate how to build a cloud cost model. It will illustrate the process of establishing the cost framework and calculating the costs. One of the main reasons to address the cloud cost modeling issue is that many ordinary people have two popular misconceptions:
1. The cloud is free.
2. My data is stored anyway up in the air.
If this is so, why should we bother to measure the sky? The answer is dependent on who you are. If you are just an individual consumer and require very limited cloud resources, it is quite clear that you can obtain nearly free cloud resources. However, if you are a business consumer, especially for medium- and large-scale businesses, there will be no free lunch. You have to pay for what you have consumed. This leads to the issue of how to make the rational investment decision for the usage of IT resources.
For most small or medium size companies, the investment decision would be relatively simple. The decision criteria could be mainly based on financial or economic returns plus a decision maker's intuition or personal satisfaction. However, for a large enterprise, the strategic investment decision (very often involving millions of dollars) is not a simple intellectual exercise but rather than process of negotiation and compromise among different Line of Business (LoB) units.
However, to some degree, all models are subjective because cost modeling involves many subjective assumptions and selection of raw data and material. It would be impossible to avoid subjective assumptions and personal opinions. Strictly speaking, any data selected and assumption made are subjective. It is based on personal experiences and intuition or perhaps, a gut feeling.
Many people think a gut feeling is negative or nonscientific. As a matter of fact, a gut feeling is kind of a super-logic or sixth sense or recognition of a subconscious pattern. It gives us a shortcut to quickly reach a solution. Sometimes, this shortcut serves us quite well, especially if we do not have enough time to analyze the circumstances surrounding us or do not have enough information available. In this case, the sixth sense would be the only choice for us to reach a self-satisfactory conclusion. It is not purely arbitrary or an illogical guess but rather meta-knowledge built upon the subconscious mind. Actually, people's minds are always searching for a recognised pattern based on available information, knowledge, experiences and most importantly, wisdom. Perhaps that is why a gut feeling is very often called an "educated guess," self-learning, working experience, or armchair thinking.
Many strategic investment decisions made by IT legends such as Steve Jobs and Marc R. Benioff  led to great success for their companies. Why did they achieve what most people cannot achieve? Is it because they not only have years of working experiences and cumulative knowledge, but also have "gut feelings" or wisdom? People speculate that they may have absorbed wisdom from Eastern philosophy and religion because they both went to India for enlightenment. In Steve Jobs' own words, "Trust in destiny" and "Follow your heart." Walter Isaacson, the exclusive biographer of Steve Jobs, wrote it this way:
Jobs's interest in Eastern spirituality, Hinduism (Krishna/God Consciousness), Zen Buddhism, and the search for enlightenment was not merely the passing phase of a nineteen-year-old. Throughout his life he would seek to follow many of the basic precepts of Eastern religions, such as the emphasis on experiential prajña, wisdom or cognitive understanding that is intuitively experienced through concentration of the mind. Years later, sitting in his Palo Alto garden, he reflected on the lasting influence of his trip to India .
For the East, it is the soul. The soul did not come with body nor die with the body. The body is just a temporary home for the soul. The soul can be enlightened by many sophisticated methodologies and practices that have been developed by Eastern philosophy, religion, and culture for many thousands of years or by messages delivered by the Supreme God personally (e.g., Lord Krishna's teachings compiled as Bhagavad Gita) or his incarnations.
For the West, it is subconsciousness. In Sigmund Freud's teachings, it is the unconscious mind beneath consciousness and awareness. It is a repository of idea, desire, memories, and emotion. It consists of any information and data the mind collects from five senses but cannot consciously process to make meaningful sense of. However, it can be retrieved or recalled to consciousness by the simple direction of attention.
In order to make the right decision at the right time, the spiritual mind constantly needs not only information and knowledge but also wisdom. Without that, a strategic decision may just be a tactical one. Long-term success would be dependent on pure luck rather than a strategy. Here, wisdom means abstract pattern recognition at hierarchical level. It is the experience of cumulative knowledge. Cumulative knowledge has four different levels:
Level 1: You do not know what you do not know (ignorance).
Level 2: You know what you do not know (know unknowns).
Level 3: You know what you know and what you do not know (know your boundaries).
Level 4: You know all - knowledge of knowledge or meta-knowledge, wisdom (wizard).
For many people and under many circumstances, they are just wandering around atknowledge level 1. If we borrow the Indian philosophy term, it is so-called "ignorance." There are two different scenarios when people face the unknown. One is either leaving to chance or pretending to know. The other is to wonder about the unknown and continuously search for knowledge and wisdom. That is why people often say wondering is the beginning of wisdom.
Unfortunately, we have witnessed many IT strategic decisions made by some wayward people subject to purely static...