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

Object storage is a type of cloud storage that stores data as objects, which consist of data, metadata, and a unique identifier. Object storage is ideal for backing up and retaining data for long periods of time, as it offers the following benefits:

• Scalability: Object storage can store virtually unlimited amounts of data, as objects are stored in a flat namespace that can span multiple servers, clusters, or regions. Object storage does not have the limitations of hierarchical file systems or block storage volumes, which can become fragmented or inefficient as they grow.
• Durability: Object storage can ensure high levels of data durability, as objects are replicated across multiple locations or zones. Object storage also supports versioning, which allows users to keep multiple versions of the same object and restore them if needed. Object storage can also use erasure coding, which splits objects into data and parity fragments and distributes them across different nodes, enabling data recovery in case of failures.
• Cost-effectiveness: Object storage can reduce the cost of storing data for long periods of time, as it typically uses commodity hardware and low-cost disks. Object storage also offers tiered storage options, which allow users to move data between different performance and price levels based on their access frequency and retention requirements. For example, users can store data in cold or archive tiers, which offer lower storage costs but higher retrieval latency and fees.

Solid state storage is a type of storage that uses flash memory chips to store data. Solid state storage offers high performance, low latency, and low power consumption, but it is also more expensive and less durable than other types of storage. Solid state storage is more suitable for storing data that requires frequent and fast access, such as databases, applications, or operating systems, rather than backing up and retaining data for long periods of time.

Block storage is a type of storage that divides data into fixed-sized blocks and assigns them unique identifiers. Block storage is commonly used to create storage volumes that can be attached to virtual machines or servers and act as local disks. Block storage offers high performance, low latency, and flexibility, but it also has some drawbacks for backing up and retaining data for long periods of time, such as:

• Scalability: Block storage has limited scalability, as storage volumes have a fixed size and capacity that cannot be easily changed. Block storage also requires more management and maintenance, as users have to provision, format, mount, and backup storage volumes manually or using scripts.
• Durability: Block storage has lower durability, as storage volumes are vulnerable to corruption, deletion, or failure. Block storage does not support versioning, which means users cannot restore previous versions of their data. Block storage also does not use erasure coding, which means users have to rely on RAID or other backup methods to ensure data redundancy and availability.
• Cost-effectiveness: Block storage has higher cost, as it typically uses more expensive and power-hungry disks. Block storage also charges users based on the provisioned size of the storage volumes, regardless of how much data they actually store. Block storage also incurs additional costs for data transfer, snapshot, and backup services.

File storage is a type of storage that organizes data into files and folders within a hierarchical file system. File storage is commonly used to store and share data that can be accessed by multiple users or applications using standard protocols, such as NFS or SMB. File storage offers simplicity, compatibility, and convenience, but it also has some limitations for backing up and retaining data for long periods of time, such as:

• Scalability: File storage has limited scalability, as file systems have a maximum number of files and folders that they can support. File storage also suffers from performance degradation and inefficiency as file systems grow larger and more complex. File storage also requires more management and maintenance, as users have to create, delete, move, and backup files and folders manually or using scripts.
• Durability: File storage has lower durability, as files and folders are susceptible to corruption, deletion, or failure. File storage does not support versioning, which means users cannot restore previous versions of their data. File storage also does not use erasure coding, which means users have to rely on RAID or other backup methods to ensure data redundancy and availability.
• Cost-effectiveness: File storage has higher cost, as it typically uses more expensive and power-hungry disks. File storage also charges users based on the provisioned size of the file systems, regardless of how much data they actually store. File storage also incurs additional costs for data transfer, snapshot, and backup services. References:
• CompTIA Cloud Essentials+ CLO-002 Study Guide, Chapter 2: Cloud Concepts, Section 2.5: Cloud Storage, pages 66-69
• 6 Types of Backups for Cloud Storage
• 4 Types of Cloud Backup Services and How to Choose
• Cloud or tape for long-term data retention?
• How to Set Up Backup Retention to Purge Older Backups

 Elasticity is the cloud computing characteristic that allows the cloud service to scale up or down the resources dynamically according to the demand. Elasticity can help the organization address the issue of performance degradation from oversubscription of memory in the virtual environment and exhausted physical RAM by automatically allocating more memory resources to the servers when needed and releasing them when not needed. This way, the organization can avoid the risk of running out of memory and ensure optimal performance of the servers. References: CompTIA Cloud Essentials+ CLO-002 Certification Study Guide, Chapter 1: Cloud Computing Concepts, Section 1.2: Cloud Computing Characteristics, Page 17

 Spot instances are instances that use spare cloud capacity that is available for less than the On-Demand price. They are suitable for low-budget projects that can tolerate interruptions and have flexible completion time. Spot instances can be reclaimed by the cloud provider when the demand for the capacity increases, so they are not guaranteed to run continuously. However, they can offer significant cost savings compared to other pricing models. References: Spot Instances - Amazon Elastic Compute Cloud, Amazon Web Services – Introduction to EC2 Spot Instances, What are AWS spot instances? - Spot.io

Data locality is the principle of storing data close to where it is used, such as in the same region, country, or jurisdiction. Data locality can improve the performance, security, and compliance of cloud applications, especially when dealing with sensitive data that is subject to legal or regulatory requirements. Data locality can also reduce the network latency and bandwidth costs associated with transferring data across long distances. Data locality can be achieved by choosing a cloud provider that has data centers in the desired locations, and by specifying the data placement and migration policies in the cloud design phase. Data locality is different from data classification, data certification, and data validation. Data classification is the process of categorizing data based on its sensitivity, value, and risk. Data certification is the process of verifying that data meets certain standards or criteria. Data validation is the process of checking that data is accurate, complete, and consistent. References: Data Locality - an overview | ScienceDirect Topics, Data Locality: What It Is and Why It Matters - Qumulo, Cloud Computing Design Principles - CompTIA Cloud Essentials+ (CLO-002) Cert Guide

Auto-scaling is a feature that helps to adjust the capacity of a system automatically based on its current demand. The goal of auto-scaling is to maintain the performance of the system and to reduce costs by only using the resources that are actually needed1. If the cloud administrator configures auto-scaling for the application, the system can scale out (add more instances) during the peak hours of 1:00 p.m. and 3:00 p.m. every day, and scale in (remove instances) when the demand is low. This way, the application can handle the increased workload without degrading its performance, and the users can have a better experience. References: CompTIA Cloud Essentials+ Certification Study Guide, Second Edition (Exam CLO-002), Chapter 2: Cloud Computing Concepts, pages 41-42.