Cloud computing is the delivery of computer resources like data (cloud) storage and computing power on-demand, without direct management or deep knowledge of the user, and with pay, as we go (Wikipedia, 2021). Cloud removes the need for owning and maintaining physical data centres (Amazon Web Services, 2019).
Several companies are using the cloud for many use cases like backup, information recovery, emails, virtual desktops, big data analysis and software development (Amazon Web Services, 2019).
Cloud Architecture based on the convergence with AI/ML
Convergence between AI and data is a reality, not just at the macro level but also within specific industries and technologies. Cloud computing simple architecture consists of four basic parts: the cloud service, the cloud infrastructure, the cloud platform, and the cloud storage (Databases). AI/ML systems manipulate large amounts of data, so they need infrastructures that can scale based on the computation needs. This is where cloud computes infrastructure that can be scaled horizontally and on-demand becomes important (Roe, 2019). Building AI/ML systems need large volumes of training, validation and test data. So, big data analysis tools (Hadoop, Spark, etc.) are required in order to handle these types of volumes.
Another convergence is the Internet of Things IoT in which there are equipment generating data through hundreds of connected sensors, and the enterprise is deciding on maintenance. We need to store, transport, process (using AI/ML) and decide whether the machine needs maintenance. These processes require merging different technologies such as cloud, AI/ML and big data processing to work together to deliver the final result (Jarrahi, 2018).
Virtual assistance, for example, needs a cloud system so that they can connect multiple systems and data sources through the cloud wherever they need. Cloud services that have been created by service providers such as Amazon, Microsoft, Google, and Rackspace (Dong, Xiong, Castañe, & Morrison, 2018), are divided into three layers: the infrastructure layer, the cloud management layer and the service delivery layer.
Cloud infrastructure design balances requirements ensuring data centre scalability, maintaining server fault tolerance and minimizing costs. Traditional data centre infrastructure stands on a hierarchical structure consisting of a three-tier design, including the Access Layer, the Aggregation Layer, and the Core Layer. The access layer connects servers residing in the same rack. In contrast, the aggregation layer is a multi-purpose system connecting the access and core layers to keep various communication domains separated. The last infrastructure layer is the core layer which provides high-speed, scalable and reliable communications among the entire data centre (Dong, Xiong, Castañe, & Morrison, 2018).
Cloud management platforms follow the same design, but their implementations differ significantly. Cloud management consists of three main components: the security part (privacy, authentication and data protection), the management services (monitoring, computational management, networking resource management, storage resource management), and the user interface part.
The last layer in the cloud computing system is the service delivery layer. There are three basic service delivery models (Dong, Xiong, Castañe, & Morrison, 2018) (Ecourse Review, 2017) known as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). IaaS gives end-users the ability to tangible infrastructures (physical servers, storage databases, network equipment). IaaS provides powerful flexibility to the end-users so that they can access their virtual machines. IaaS targets end-users who are interested in building Information Technology infrastructure. PaaS, on the other hand, reduces the configuration complexity and operational costs by providing pre-configured platforms and offer ready-to-use platforms to end-users such as operating systems (Linux, Windows), workflow engines (Apache Director Engine), Messaging frameworks (RabbitMQ, ZeroMQ), programming-language execution environment and Web application servers (e.g., Apache Tomcat, Oracle Glassfish Red Hat JBoss). SaaS gives users access to application software and databases. It is known as “on-demand software” and priced on a pay-per-use basis. SaaS providers install and operate software in the cloud so that users access them from cloud clients (Wikipedia, 2021) (Ecourse Review, 2017) (Rountree, Castrillo, & Hai Jiang, 2014). Figure1 includes the cloud design layers.
Fig.1 Cloud system layers
Another service called Mobile “backend” as a service (MBaaS) provides web application and mobile application developers with a flexible approach to link their applications to the cloud computing servers and storage. This service includes user management, integration with social network services and other push notifications (Roe, 2019).
Amazon Web Services. (1 21, 2019). What is Cloud Computing? Retrieved from: Youtube: https://www.youtube.com/watch?v=dH0yz-Osy54
Dong, D., Xiong, H.. Castañe, G. G. & Morrison. J.P. (2018) Cloud Architectures and Management Approaches. Palgrave Studies in Digital Business & Enabling Technologies (p 31-61).
David Roe. (8 8, 2019). Why Big Data, IoT, AI and Cloud Are Converging in the Enterprise. Retrieved from: CMS Wire: https://www.cmswire.com/digital-workplace/why-big-data-iot-ai-and-cloud-are-converging-in-the-enterprise/
Rountree, D., Castrillo, I. & Jiang. H. (2014) The Basics of Cloud Computing. Waltham- USA: Elsevier.
Ecourse Review. (6 4, 2017). Cloud Computing Services Models – IaaS PaaS SaaS Explained. Retrieved from:Youtube: https://www.youtube.com/watch?v=36zducUX16w
Jarrahi, M.H. (2018) Artificial Intelligence and the Future of Work. Business Horizons، 4.
Wikipedia. (, 2021). Cloud_computing. Retrieved from: Wikipedia: https://en.wikipedia.org/wiki/Cloud_computing