Chapter 16: Define And Describe Total Cost Of Ownersh 937267 ✓ Solved

Chapter 16 Define and describe total cost of ownership. List at

Define and describe total cost of ownership. List at least 10 items to consider when determining a data center’s total cost of ownership. Define and describe a capital expense. How are capital expenses different from operational expenses? Define and describe economies of scale and provide a cloud-based example.

Define and describe “right sizing” as it pertains to cloud computing. Define Moore’s law and discuss how it might influence cloud migration. Given company revenues of $2.5 million and expenses of $2.1 million, calculate the company’s profit and profit margin. Chapter 17 Compare and contrast functional and nonfunctional requirements and provide an example of each. Discuss why a designer should avoid selecting an implementation platform for as long as possible during the design process.

Discuss various trade-offs a designer may need to make with respect to nonfunctional requirements. Discuss why the system maintenance phase is often the most expensive phase of the software development life cycle. Chapter 19 Define scalability. List five to ten potential relationships that align with the Pareto principle, such as how 80 percent of sales come from 20 percent of customers. Compare and contrast vertical and horizontal scaling.

Explain the importance of the database read/write ratio. Assume a site guarantees 99.99 percent uptime. How many minutes per year can the site be down? Chapter 20 List and describe five ways you think the cloud will change the future of TV. List and describe five potential uses for intelligent fabric.

List and describe five ways the cloud will influence the mobile application market, or vice versa. Discuss the importance of HTML 5. Discuss how the cloud will impact future operating systems. List and describe three potential location-aware applications. List and describe five ways intelligent devices may work together.

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The concept of Total Cost of Ownership (TCO) represents a comprehensive assessment of all costs associated with a product or service over its entire lifecycle. In the context of a data center, TCO encompasses initial procurement costs, operational expenses, and any costs associated with disposal or decommissioning. Understanding TCO is crucial for organizations looking to optimize their IT infrastructure investments and ensure long-term fiscal responsibility.

When considering the TCO of a data center, there are at least ten key items to assess:

1. Capital Expenditures (CapEx): The upfront costs for hardware, software, and infrastructure.
2. Operational Expenditures (OpEx): Ongoing costs related to maintenance, utilities, labor, and other recurring expenses.
3. Power Consumption: Energy costs associated with running servers, cooling systems, and other equipment.
4. Cooling Requirements: Expenses incurred by the HVAC systems necessary for temperature control.
5. Space Costs: Rental or real estate costs associated with the physical location of the data center.
6. Labor Costs: Personnel costs for IT support, maintenance, and operations staff.
7. Security Costs: Investments in physical and cyber security measures.
8. Software Licensing: Ongoing costs for operating systems, applications, and management tools.
9. Insurance: Costs for insuring the facility and its assets against various risks.
10. Decommissioning Costs: Expenses associated with disposing of outdated or obsolete equipment.

A capital expense refers to a long-term investment in a physical asset or system that will benefit the company over a more extended period, typically lasting more than one year. Capital expenses differ from operational expenses in that the latter are ongoing costs necessary for the day-to-day functioning of the organization. For instance, purchasing a new server represents a capital expense, while the monthly electricity bill to power that server constitutes an operational expense.

Economies of scale describe the cost advantages that organizations experience as they increase their output. In cloud computing, a cloud service provider can achieve economies of scale by serving numerous clients simultaneously, allowing them to spread the costs of hardware, maintenance, and infrastructure across a larger customer base. For example, cloud providers like AWS or Microsoft Azure provide resources such as storage and processing power at significantly reduced costs due to their scale, thus benefiting clients in terms of lower service fees.

"Right sizing" is the process of adjusting the resources allocated for cloud computing environments based on actual demand rather than projected usage. This ensures that businesses do not over-provision resources, which can lead to unnecessary costs. For example, a company that initially estimates it needs a significant amount of computing power may find that actual usage is much lower, thus allowing adjustments to save costs.

Moore’s Law states that the number of transistors on a microchip doubles approximately every two years, which leads to increases in computing power and decreases in relative costs. This phenomenon influences cloud migration by encouraging businesses to move to cloud services that regularly update hardware and benefit from advancements in technology, leading to improved performance and cost efficiencies over time.

In evaluating company performance, if a company generates revenues of $2.5 million and incurs expenses totaling $2.1 million, the profit can be calculated as follows:

Profit = Revenues - Expenses = $2.5 million - $2.1 million = $0.4 million.

The profit margin can be calculated by dividing the profit by the total revenue:

Profit Margin = (Profit / Revenue) 100 = ($0.4 million / $2.5 million) 100 = 16%.

In terms of functional versus nonfunctional requirements, functional requirements specify what a system should do, such as user authentication processes or transaction processing. In contrast, nonfunctional requirements pertain to how a system performs its functions, such as speed, scalability, and security. For example, a functional requirement might involve the ability for users to submit online forms, while a nonfunctional requirement could specify that the forms must be submitted within two seconds.

Designers are often advised to postpone selecting an implementation platform until later stages in the design process to maintain flexibility and avoid constraints that could limit functionality or innovation. An early platform choice might lead to forced decisions that could compromise the overall design and performance of the system.

Trade-offs regarding nonfunctional requirements often involve balancing performance against cost, usability against security, or flexibility against maintainability. For instance, a high-security system may require complex authentication processes that could hinder usability, indicating a necessary trade-off for the designer to consider.

The system maintenance phase is typically the most expensive part of the software development life cycle due to the cumulative nature of long-term support, bug fixes, updates, and potential overall system performance enhancements over time. As systems evolve, ongoing maintenance demands can lead to escalating costs if not adequately managed from the outset.

Scalability refers to a system's capability to handle an increasing amount of work or its potential to be enlarged to accommodate growth. According to the Pareto principle, or the 80/20 rule, a small percentage of causes often leads to a large percentage of the effects. For example, 80% of a business's sales may come from just 20% of its clients, highlighting the importance of understanding customer relationships and optimizing resources.

Vertical scaling involves adding more power (CPU, RAM) to an existing server to increase its capacity, while horizontal scaling refers to adding more servers to distribute the load. Both approaches have their advantages; vertical scaling provides simplicity, while horizontal scaling allows for greater redundancy and resilience.

The database read/write ratio is crucial as it impacts performance in systems where reads and writes are balanced. An optimal balance ensures that databases can handle the expected load without degradation in performance. In terms of uptime, a site guaranteeing 99.99% uptime can be down for approximately 53 minutes and 15 seconds per year.

Looking towards the future, the cloud is expected to significantly change television through aspects such as on-demand services, personalized content delivery, enhanced interactivity, increased accessibility, and integration of smart technologies. Moreover, intelligent fabrics, including wearables and smart textiles, will find applications in myriad fields, including healthcare, fashion, and fitness.

In the mobile application market, the influence of cloud computing can manifest through improved app performance, enhanced data synchronization, easier scalability, advanced analytics capabilities, and facilitating the development of more complex applications without needing substantial local resources. The move towards HTML5 has paved the way for richer web applications, enabling mobile app developers to create immersive user experiences across various devices, thus contributing to the growth and adaptability of cloud-based applications.

Lastly, future operating systems may be profoundly impacted by cloud technologies, emphasizing design for connectivity, seamless access to cloud resources, and support for applications that rely heavily on online interactions. Location-aware applications will harness GPS and other localization technologies to provide contextual services. Lastly, intelligent devices are likely to work together through integrated platforms, providing enhanced user experiences by sharing data across ecosystems.

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