Essay Example on Cloud Computing: Front-End & Back-End Explained

1 Introduction

The complete cloud computing system will have two components: the front end and the back end. The front end is the user-facing part, which comprises applications and interfaces that enable the user to access the computing power. The components include web browsers, web applications, and local networks. The back end comprises servers, virtual machines, security mechanisms, data storage, and other resources required for cloud computing. While the front end is under user control, the back end will be controlled by the providers. The user part and the back-end architectures will connect to the cloud through the internet. The entire system will use the IaaS cloud-based delivery.

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1.1 File System Distribution

Cloud computing distributes data over different storage locations such that if one fails, the other takes over the ongoing job automatically. Therefore, this technology offers a stable, distributed environment that allows businesses to store, secure, and access data remotely efficiently. The data files are divided into chunks, which are stored on different machines. In the case of Al Bashayer Meat Company, the machines are in a private cloud. The data is stored in a tree structure, with every node representing a directory. Also, the nodes allow operations on the data. To complete such functions, distributed file systems in cloud computing require robust algorithms.

For proper file management in the cloud environment, Al Bashayer Meat Company requires the Hadoop Distributed File System (HDFS) software. The software is cost-saving and reliable. According to Borthakur (2019), it runs on low-cost hardware and offers high fault tolerance and throughput. Moreover, HDFS supports applications with massive data sets. HDFS will help to protect Al Bashayer Meat Company’s data in numerous ways. Hardware failures are virtually unavoidable. The Primary goal of HDFS is to identify the faults and recover from them automatically. HDFS is portable across heterogeneous hardware; hence, it can be adopted quickly from one platform to the other within Al Bashayer Meat Company.

1.2 Request Management Using Multiple Virtual Machines

Multiple customers using the system simultaneously can result in degraded performance and reduced reliability and availability. If this problem is not controlled, it can cause overall failure. Therefore, the computing resources should be scaled effectively, and a load balancing system should be used to distribute the running workloads across several computing resources. Load-balancing technology is configured with related algorithms to achieve this solution. For example, if the IT specialists at Al Bashayer Meat Company decide to employ the Weighted Round Robin algorithm, each server is assigned a static numeric weighing. The higher, with more ratings, will be allowed to handle more customer requests. The load balancers continually check the health of the servers and remove them from the pool if damaged. The processes conducted under this method ensure optimal application responsiveness by making every server take the workload it can handle. Apart from the factors mentioned above, the workload distribution architecture allows audit monitoring, runtime workload tracking and data processing, and the hypervisor mechanism.

1.3 Requirements to Become a Service Provider in the Future

Al Bashayer Meat Company can readily become a cloud service in the future because it already has a vast market – its clients. However, the organisation should ensure that it does not separate its meat delivery services from the provision of cloud computing resources. This will enable Al Bashayer Meat Company to understand its customers and to provide relevant applications. Also, before Al Bashayer Meat Company becomes a valid provider, it should meet the Service-Level Agreement (SLA) requirements. SLAs ensure that the provider maintains a minimum level of service to the customer. The quality metrics in question are availability, reliability, performance, scalability, and resiliency. These factors should be quantifiable and comparable.

Availability refers to the up-time, outages, and service duration, expressed in percentage. The quantity is measured regularly; weekly, monthly, and yearly.