CLO-002 Exam Dumps - CompTIA Cloud Essentials+

 Chargeback is the best approach to match some of the cloud operating costs with the appropriate departments. Chargeback is a process where the IT department bills each department for the amount of cloud resources they use, such as compute, storage, network, or software. Chargeback can help the company to allocate the cloud costs more accurately and fairly, as well as to encourage the departments to optimize their cloud consumption and reduce waste. Chargeback can also provide the company with more visibility and accountability of the cloud usage and spending across the organization12

Chargeback is different from showback, which is a process where the IT department shows each department the amount of cloud resources they use, but does not charge them for it. Showback can also help the company to increase the awareness and transparency of the cloud costs, but it may not have the same impact on the behavior and efficiency of the departments as chargeback12

Right-sizing and scaling are not approaches to match the cloud costs with the departments, but rather techniques to adjust the cloud resources to the actual demand and performance of the applications or services. Right-sizing and scaling can help the company to save money and improve the cloud utilization, but they do not address the issue of cost allocation or attribution34

References: CompTIA Cloud Essentials+ Certification Exam Objectives, CompTIA Cloud Essentials+ Study Guide, Chapter 2: Business Principles of Cloud Environments, IT Chargeback vs Showback: What’s The Difference?2, Cloud Essentials+ Certification Training

A subscription agreement is a type of pay-as-you-go licensing model within a cloud service, where the user pays a recurring fee for the access to the cloud resources and services. The fee is usually based on the number of users, the amount of data, or the duration of the subscription. A subscription agreement allows the user to scale up or down the cloud usage as needed, and only pay for what they use. A subscription agreement is different from a perpetual agreement, which is a one-time payment for a perpetual license to use the cloud service. A subscription agreement is also different from an enterprise agreement, which is a long-term contract that offers discounts and benefits for large-scale cloud usage. A promotional agreement is a temporary offer that provides free or discounted access to the cloud service for a limited time or under certain conditions. References: Cloud Service Models - CompTIA Cloud Essentials+ (CLO-002) Cert Guide, Cloud Computing Pricing Models - CompTIA Cloud Essentials+ (CLO-002) Cert Guide

 The SLA should include the Recovery Time Objective (RTO) to satisfy this requirement. The RTO is the maximum acceptable time that an application or service can be unavailable after a disaster or disruption. It defines the target duration for restoring the functionality and performance of the application or service. The RTO is usually measured in hours or days, depending on the criticality of the application or service. In this case, the requirement states that the application must be restored within six hours, which means that the RTO should be six hours or less. The other options are not relevant to this requirement. The Mean Time to Repair (MTTR) is the average time that it takes to fix a faulty component or system. The Recovery Point Objective (RPO) is the maximum acceptable amount of data loss that can occur after a disaster or disruption. It defines the point in time to which the data must be restored. The RPO is usually measured in minutes or hours, depending on the frequency of data backups. The Return on Investment (ROI) is the ratio of the net profit to the initial cost of an investment. It measures the financial benefit of an investment over time. References: CompTIA Cloud Essentials+ Certification Study Guide, Second Edition (Exam CLO-002), Chapter 3: Business Principles of Cloud Environments, Section 3.2: Cloud Assessments, p. 103-104.

Spot instances are cloud resources that are available at a lower price than on-demand instances, but can be terminated by the cloud provider at any time based on supply and demand. Therefore, the application that will run on these instances needs to handle unpredictable instance termination, such as by saving state information, implementing fault tolerance, or using checkpoints12.

The other options are not directly related to the use of spot instances. The application may or may not need to store data in a database, depending on its functionality and design. There is no inherent restriction for distributed network communications when using spot instances, as long as the application can handle network latency and bandwidth issues. Resource-intensive compute loads are not forbidden, but they may increase the likelihood of instance termination, as the cloud provider may reclaim the resources for higher-paying customers.

References:

• [CompTIA Cloud Essentials+ CLO-002 Study Guide], Chapter 2: Business Principles of Cloud Environments, Section 2.4: Cloud Service Costing, p. 81-82
• [CompTIA Cloud+ CV0-003 Study Guide], Chapter 6: Optimizing the Cloud Environment, Section 6.3: Cloud Optimization Techniques, p. 287-288
• [CompTIA Cloud Essentials+ CLO-002 Study Guide], ISBN: 978-1-119-64768-9, Publisher: Wiley
• [CompTIA Cloud+ CV0-003 Study Guide], ISBN: 978-1-119-64767-2, Publisher: Wiley

Geo-redundancy is the strategy of sending copies of data to a distant region from the original cloud storage location. This provides protection against regional disasters or outages that might affect the primary data center. A CSR (cloud service provider) is a third-party company that offers cloud-based services such as storage, computing, networking, or software. A company that uses a CSR to store its data in a geo-redundant manner is leveraging the benefits of cloud computing, such as scalability, availability, and cost-effectiveness. References: CompTIA Cloud Essentials+ CLO-002 Study Guide, page 103; CompTIA Cloud Storage Requirements- What You Need to Know

Machine learning is a branch of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. Machine learning can be used to forecast market trends by analyzing historical and current data, identifying patterns and relationships, and generating models that can extrapolate future outcomes. Machine learning can also adapt to changing data and environments, and improve its accuracy and performance over time1.

The other options are not commonly used to forecast market trends:

• Serverless computing: This is a type of cloud computing that allows customers to run applications or functions without managing or provisioning servers. Serverless computing can reduce the operational and infrastructure costs, and improve the scalability and availability of the applications or functions. However, serverless computing is not directly related to forecasting market trends, although it can be used to deploy or run machine learning models or applications2.
• Data warehouse: This is a centralized repository that stores structured and historical data from various sources, such as databases, applications, or files. Data warehouse can support business intelligence and analytics, and provide consistent and reliable data for reporting and decision making. However, data warehouse is not a forecasting method, but rather a data storage and integration system, that can be used as an input for machine learning or other forecasting methods3.
• Accelerated computing: This is a type of computing that uses specialized hardware, such as graphics processing units (GPUs) or field-programmable gate arrays (FPGAs), to accelerate the performance of certain applications or tasks, such as machine learning, gaming, or video processing. Accelerated computing can enhance the speed and efficiency of the applications or tasks, and reduce the power consumption and costs. However, accelerated computing is not a forecasting method, but rather a computing platform, that can be used to support or enable machine learning or other forecasting methods4.

References:

• Machine Learning for Forecasting Market Trends
• Serverless Computing for Machine Learning
• Data Warehouse for Business Intelligence and Analytics
• Accelerated Computing for Machine Learning

Avoidance is a risk response technique that involves changing the project plan to eliminate the risk or protect the project objectives from its impact. Avoidance can be done by modifying the scope, schedule, cost, or quality of the project. Avoidance is usually the most effective way to deal with a risk, but it may not always be possible or desirable. In this case, the cloud customer is transferring all of its cold storage data to servers in a safer geographic region, which means they are changing the location of their data storage to avoid the risk of a natural disaster affecting their data. This way, they are eliminating the possibility of losing their data due to a natural disaster in their original region. This is an example of avoidance as a risk response technique. References: CompTIA Cloud Essentials+ CLO-002 Study Guide, Chapter 4: Cloud Security, Section 4.2: Cloud Security Concepts, Page 153. 5 Risk Response Strategies - ProjectEngineer1

 The financial impact to the business is the amount of revenue lost due to the outage of the customer-facing e-commerce website. To calculate the financial impact, we can use the following formula:

Financial impact = Revenue loss per minute x Outage duration

Using this formula, we can find the financial impact as follows:

Financial impact = $25000 x 15 minutes = $375000

Therefore, the financial impact to the business is $375000, which is the product of the revenue loss per minute and the outage duration. Option C is the correct answer. Option A is incorrect because it is the product of the revenue loss per minute and the RTO, which is the maximum acceptable outage duration, not the actual outage duration. Option B is incorrect because it is the product of the revenue loss per minute and the time elapsed since the outage, not the outage duration. Option D is incorrect because it is the product of the revenue loss per minute and the sum of the RTO and the outage duration, which is not relevant to the financial impact calculation. References: CompTIA Cloud Essentials+ CLO-002 Study Guide, Chapter 6: Cloud Operations Principles, Section 6.2: Disaster Recovery Concepts, Page 179 and [How to Calculate the Cost of Downtime for Your Business | LogicMonitor]