CLO-002 Exam Dumps - CompTIA Cloud Essentials Questions and Answers

Orchestration is the best option for coordinating the processes of several applications and assigning a manager to oversee the technical coordination to improve efficiency. Orchestration is the combined automation of apps, workloads, supporting resources, and infrastructure across one or more cloud platforms1. It commonly includes imperative and/or declarative methods to drive automation1. Orchestration introduces and enforces a workflow for automated activities of various processes to deliver the desired service to its client2. Orchestration helps IT organizations reduce manual, repetitive work, better standardize their deployments and operations, and accelerate delivery1. Orchestration also enables businesses to easily add or remove computing resources, on demand, without significant hardware investment or infrastructure changes2. Orchestration ensures that businesses can efficiently and seamlessly handle varying workloads, optimize resource utilization, and enhance the overall reliability and performance of cloud computing systems3.

Orchestration is different from the other options listed in the question, which are not directly related to coordinating the processes of several applications. Scripting is the use of code to perform a specific task or operation on a single component of an application, workload, resource, or infrastructure within a cloud platform1. Scripting is one of the building blocks for delivering cloud orchestration, but it does not provide the coordination, arrangement, or end-to-end automation of the deployment of services in a cloud-based environment2. Continuous integration is the practice of merging code changes from multiple developers into a shared repository frequently, usually several times a day, to detect and resolve errors early4. Continuous integration is a part of the DevOps methodology, which aims to improve the quality and speed of software delivery, but it does not address the orchestration of the processes of several applications across multiple cloud platforms1. Continuous delivery is the practice of releasing software updates to production in small increments, usually after passing automated tests, to ensure that the software is always in a deployable state4. Continuous delivery is another part of the DevOps methodology, which aims to reduce the risk and cost of software deployment, but it does not address the orchestration of the processes of several applications across multiple cloud platforms1.

References: Orchestration in Cloud Computing - GeeksforGeeks, Cloud Orchestration. What Is Cloud Orchestration? - Cisco, Cloud orchestration. What Is Cloud Orchestration? 8 Tools To Get You Started - CloudZero, Cloud orchestration. What is Continuous Integration? | Atlassian, Continuous integration. What is Continuous Delivery? | Atlassian, Continuous delivery.

Geo-redundancy and backup are two methods that can ensure the availability of data that is accessed across multiple sites. Geo-redundancy is the practice of storing data in more than one geographic location, such as different regions, countries, or continents. This can improve the data availability by reducing the impact of natural disasters, network failures, or malicious attacks that may affect one site. Geo-redundancy can also improve the data performance by allowing users to access the data from the nearest or fastest site. Backup is the process of creating and storing copies of data that can be used to restore the original data in case of data loss, corruption, or deletion. Backup can ensure the data availability by providing a way to recover the data from a previous state, such as before a hardware failure, software error, or human error. Backup can also protect the data from accidental or intentional modifications that may compromise its integrity or security.

Geo-redundancy and backup are different from other options, such as auto-scaling, provisioning, locality, and zones. Auto-scaling is the ability of a cloud service to automatically adjust the amount of resources allocated to a workload based on the demand or usage. Provisioning is the process of allocating and configuring the resources needed to run a cloud service or application. Locality is the principle of storing data close to where it is used, such as in the same region, country, or jurisdiction. Zones are logical or physical subdivisions of a cloud region that provide isolation and redundancy for the cloud resources. While these options may also affect the data availability, they do not directly address the data access across multiple sites, which is the focus of the question. References: Extending a Datastore Across Two Sites with Stretched Clusters, SQL Server Multi-Subnet Clustering - SQL Server Always On, What Is a Distributed Database? {Features, Benefits & Drawbacks}, Cloud Computing Availability - CompTIA Cloud Essentials+ (CLO-002) Cert Guide

Multifactor authentication (MFA) is a method of verifying a user’s identity by requiring more than one factor, such as something the user knows, something the user has, or something the user is1. A short message service (SMS) message sent to a phone and an access PIN is an example of MFA, as it combines two factors: something the user has (the phone) and something the user knows (the PIN). This makes the authentication process more secure than using only a password, which is a single factor. Other examples of MFA include using a biometric scan (such as a fingerprint or a face recognition) and a password, or using a hardware token (such as a smart card or a USB key) and a password1. References: 1: CompTIA Cloud Essentials+ Certification Study Guide, Second Edition (Exam CLO-002), Chapter 3: Cloud Planning, Section 3.2: Cloud Adoption, Subsection 3.2.1: Identity and Access Management

Shared responsibility is the cloud principle that states that the security and compliance of the cloud service are shared between the cloud service provider and the cloud customer. The cloud service provider is responsible for securing the cloud infrastructure, such as the hardware, software, networking, and facilities, while the cloud customer is responsible for securing the cloud data, applications, and access, such as the encryption, backup, authentication, and authorization. By following the shared responsibility principle, the cloud customer can manage the risk of a network breach by implementing appropriate security measures and controls on their end, such as firewalls, antivirus, VPNs, and IAM. The cloud customer can also leverage the security features and services offered by the cloud service provider, such as encryption, monitoring, auditing, and incident response. References: CompTIA Cloud Essentials+ CLO-002 Certification Study Guide, Chapter 5: Managing Cloud Security, Section 5.1: Understanding Cloud Security Concepts, Page 1611

RPO stands for recovery point objective, which is the maximum amount of data loss that a company can tolerate in the event of a disaster, failure, or disruption. RPO is measured in time, from the point of the incident to the last valid backup of the data. RPO helps determine how frequently the company needs to back up its data and how much data it can afford to lose. For example, if a company has an RPO of one hour, it means that it can lose up to one hour’s worth of data without causing significant harm to the business. Therefore, it needs to back up its data at least every hour to meet its RPO.

RPO is different from other metrics such as RTO, TCO, MTTR, and ROI. RTO stands for recovery time objective, which is the maximum amount of time that a company can tolerate for restoring its data and resuming its normal operations after a disaster. TCO stands for total cost of ownership, which is the sum of all the costs associated with acquiring, maintaining, and operating a system or service over its lifetime. MTTR stands for mean time to repair, which is the average time that it takes to fix a faulty component or system. ROI stands for return on investment, which is the ratio of the net profit to the initial cost of a project or investment. References: Recovery Point Objective: A Critical Element of Data Recovery - G2, What is a Recovery Point Objective? RPO Definition + Examples, Cloud Computing Pricing Models - CompTIA Cloud Essentials+ (CLO-002) Cert Guide

Geo-redundancy is the best option for a company that needs to ensure data availability in multiple datacenters around the world. Geo-redundancy is the duplication of IT infrastructure and data across geographically dispersed locations, such as different regions or continents1. Geo-redundancy provides several benefits for cloud-based applications, such as:

• High availability: Geo-redundancy can improve the availability of cloud services by reducing the impact of regional outages, disasters, or network failures. If one datacenter becomes unavailable, the application can switch to another datacenter that has a copy of the data and continue to operate2.
• Performance: Geo-redundancy can enhance the performance of cloud services by reducing the latency and bandwidth consumption for users who are located far from the primary datacenter. By having datacenters closer to the users, the application can deliver faster and more consistent responses3.
• Compliance: Geo-redundancy can help the company comply with regulatory or legal requirements that mandate data sovereignty or data protection. By having datacenters in different jurisdictions, the company can store and process data according to the local laws and regulations4.

The other options are not as suitable as geo-redundancy for the company’s needs because:

• Auto-scaling: Auto-scaling is the ability of cloud services to automatically adjust the amount of resources allocated to an application based on the demand and workload. Auto-scaling can improve the scalability and cost-efficiency of cloud services, but it does not guarantee data availability in multiple datacenters5.
• Disaster recovery: Disaster recovery is the process of restoring the normal operation of an application after a disruption or failure. Disaster recovery can involve backup, restore, and failover mechanisms, but it does not necessarily require data replication across multiple datacenters.
• High availability: High availability is the degree to which an application can operate without interruption or downtime. High availability can be achieved by using redundant components, load balancing, and fault tolerance techniques, but it does not imply data distribution across multiple datacenters.

References:

• 1: Georedundancy - Open Telekom Cloud
• 2: Why geo-redundancy for cloud infrastructure is a ‘must have’
• 3: Use geo-redundancy to design highly available applications
• 4: Protect your cloud infrastructure with geo-redundancy - Data Centre Review
• 5: What is Auto Scaling? - Amazon Web Services
• : What is Disaster Recovery? - Microsoft Azure
• : What is High Availability? - IBM Cloud

Spot instances are cloud computing resources that are available at a lower price than the regular on-demand price, but can be interrupted and reclaimed by the cloud provider at any time1. Spot instances are ideal for batch jobs that have flexible completion times and can tolerate failures, as they can provide faster and cheaper computing power than regular instances2. Spot instances can also be combined with other pricing options, such as on-demand or reserved instances, to optimize the performance and cost of batch jobs3.

Implementing right-sizing is a technique of adjusting the size and type of cloud resources to match the actual needs and usage patterns of an application4. Right-sizing can help reduce the cost and improve the efficiency of cloud resources, but it does not necessarily make the batch job faster, as it depends on the workload and demand of the job.

Increasing CPU usage is a measure of how much processing power is being consumed by an application or a system. Increasing CPU usage can make the batch job faster, but it can also increase the cost and risk of overloading the system. Increasing CPU usage is not a solution by itself, but rather a consequence of using more or larger cloud resources.

Adding storage is a process of increasing the amount or capacity of data that can be stored in the cloud. Adding storage can help store more data or backup data for the batch job, but it does not directly affect the speed or cost of the batch job, as it depends on the type and performance of the storage service. References: CompTIA Cloud Essentials+ CLO-002 Study Guide, Chapter 5: Cloud Resource Management, pages 191-192.

Right-sizing compute resource instances is the process of matching instance types and sizes to workload performance and capacity requirements at the lowest possible cost. It’s also the process of identifying opportunities to eliminate or downsize instances without compromising capacity or other requirements, which results in lower costs and higher efficiency1. Right-sizing is a key mechanism for optimizing cloud costs, but it is often ignored or delayed by organizations when they first move to the cloud. They lift and shift their environments and expect to right-size later. Speed and performance are often prioritized over cost, which results in oversized instances and a lot of wasted spend on unused resources2.

Right-sizing compute resource instances is the best action that the analyst should consider to lower costs and improve efficiency, as it can help reduce the amount of resources and money spent on instances that operate at a fraction of the full processing capacity. Right-sizing can also improve the performance and reliability of the instances by ensuring that they have enough resources to meet the workload demands. Right-sizing is an ongoing process that requires continuous monitoring and analysis of the instance usage and performance metrics, as well as the use of tools and frameworks that can simplify and automate the right-sizing decisions1.

Consolidating into fewer instances, using spot instances, or negotiating better prices on the company’s reserved instances are not the best actions that the analyst should consider to lower costs and improve efficiency, as they have some limitations and trade-offs compared to right-sizing. Consolidating into fewer instances can reduce the number of instances, but it does not necessarily optimize the type and size of the instances. Consolidating can also introduce performance and availability issues, such as increased latency, reduced redundancy, or single points of failure3. Using spot instances can reduce the cost of instances, but it also introduces the risk of interruption and termination, as spot instances are subject to fluctuating prices and availability based on the supply and demand of the cloud provider4. Negotiating better prices on the company’s reserved instances can reduce the cost of instances, but it also requires a long-term commitment and upfront payment, which reduces the flexibility and scalability of the cloud environment5. References: Right Sizing - Cloud Computing Services; The 6-Step Guide To Rightsizing Your Instances - CloudZero; Consolidating Cloud Services: How to Do It Right | CloudHealth by VMware; Spot Instances - Amazon Elastic Compute Cloud; Reserved Instances - Amazon Elastic Compute Cloud.

 Disaster recovery is the process of restoring the normal operations of an organization after a disruptive event, such as a natural disaster, a cyberattack, or a human error. Disaster recovery involves the planning, preparation, and implementation of strategies and procedures to minimize the impact and duration of the disruption, and to ensure the continuity and availability of the critical functions and data of the organization1

RTO and RPO are two key metrics that are used to measure and evaluate the disaster recovery capabilities and objectives of an organization. RTO stands for Recovery Time Objective, which is the maximum acceptable amount of time that an application or a service can be offline or unavailable after a disruption. RPO stands for Recovery Point Objective, which is the maximum acceptable amount of data that can be lost or unrecoverable after a disruption2

When designing a new cloud-enabled application, an organization that is considering RTO and RPO is most likely concerned about disaster recovery, as these metrics can help the organization to determine the optimal level of backup, redundancy, and recovery for the application, as well as the potential costs and risks of downtime or data loss. RTO and RPO can also help the organization to choose the appropriate cloud service model, provider, and deployment option that can meet the disaster recovery requirements and expectations of the organization and its customers3

References: CompTIA Cloud Essentials+ Certification Exam Objectives4, CompTIA Cloud Essentials+ Study Guide, Chapter 7: Cloud Security5, Cloud Essentials+ Certification Training

 Vendor lock-in is the type of risk that is most likely to be associated with moving all data to one cloud provider. Vendor lock-in refers to the situation where a customer is dependent on a particular vendor’s products and services to such an extent that switching to another vendor becomes difficult, time-consuming, or expensive. Vendor lock-in can limit the customer’s flexibility, choice, and control over their cloud environment, and expose them to potential issues such as price increases, service degradation, security breaches, or compliance violations. Vendor lock-in can also prevent the customer from taking advantage of new technologies, innovations, or opportunities offered by other vendors. Vendor lock-in can be caused by various factors, such as proprietary formats, standards, or protocols, lack of interoperability or compatibility, contractual obligations or penalties, or high switching costs12

References: CompTIA Cloud Essentials+ Certification Exam Objectives3, CompTIA Cloud Essentials+ Study Guide, Chapter 2: Business Principles of Cloud Environments2, Moving All Data to One Cloud Provider: Understanding Risks1