This module introduces the concept of virtualisation—one of the foundational technologies behind cloud computing. Learners will explore how virtualisation abstracts physical resources to create scalable and efficient computing environments. The module covers the basics of virtualisation, the purpose and function of hypervisors, and dives deeper into the virtualisation of key system components such as CPU, memory, and I/O. It also explains the different approaches to CPU virtualisation and categorises hypervisor types based on architecture and use case. Through interactive videos, quizzes, and readings, students will build a solid foundation in virtualisation technologies.

This module introduces the core concepts of containerisation and its critical role in modern software development and deployment. It begins by explaining what containers are, their evolution, and the different types used in the industry today. The module then explores Docker, a popular containerisation platform, including how to install, run, and manage containers using essential Docker commands. Finally, learners will gain hands-on insights into container networking (bridge, host, and overlay modes) and persistent storage techniques. Through structured video lessons, practice quizzes, and readings, learners will build the foundational skills needed to work with containerised applications.

This module introduces Infrastructure as a Service (IaaS), one of the core service models in cloud computing. Learners begin by exploring the foundational concepts of IaaS and its role in modern IT environments. The focus then shifts to Amazon Web Services (AWS), the leading IaaS provider, where learners will understand key services such as compute, networking, identity, and access management. Practical insights into launching and managing EC2 instances, AWS's shared responsibility model, IAM roles and policies, and compute pricing models will prepare learners for hands-on work with cloud infrastructure.

This module focuses on the storage and database services offered by AWS, along with an introduction to the Platform as a Service (PaaS) and Software as a Service (SaaS) models. Learners will explore various AWS storage options, including Amazon EBS, S3, and EFS, and understand when and how to use each. The module also covers AWS's managed database services such as Amazon RDS, DynamoDB, Aurora, and Redshift. In addition, learners will examine the principles of PaaS and SaaS, their architectures, business models, and user benefits, highlighting their applicability across different cloud solutions.

This module introduces learners to the foundational cloud service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)—with a focus on SaaS. It explores how SaaS applications are architected, delivered, and consumed over the internet without requiring users to manage infrastructure. Through real-world examples like Google Docs, Netflix, and Lideo, learners will understand the benefits of SaaS, including scalability, accessibility, and cost-efficiency. The module also demystifies multi-tenancy, a core concept in SaaS, using visual aids and hands-on deployment of a Java-based LMS on AWS EC2. By the end, learners will be able to explain SaaS architecture and deploy a basic SaaS application.

This module focuses on cloud storage types—object, block, and file—and how they are used in SaaS applications. Learners will explore AWS S3 storage classes such as Standard, Intelligent-Tiering, and Glacier, and understand how lifecycle policies help optimize storage costs. Using LMS content as a case study, the module demonstrates how different types of data map to different storage tiers. Learners will configure S3 buckets, set lifecycle rules, and estimate monthly costs using the AWS Pricing Calculator.

This module explores how cloud platforms manage fluctuating demand through elasticity, scalability, auto-scaling, and load balancing. Learners will understand the principles of capacity planning and how cloud services dynamically allocate resources to maintain performance and cost-efficiency. Using the LMS backend as a case study, learners will create AMIs, configure Auto Scaling Groups, and deploy Load Balancers to handle simulated traffic. CloudWatch metrics will be used to monitor performance and scaling behaviour.

This module introduces scheduling in cloud environments, emphasising its role in optimising resource usage and application performance. Learners will explore static and dynamic scheduling approaches, including Round Robin and priority-based algorithms. The module also covers Kubernetes pod scheduling using Amazon EKS, demonstrating how cloud-native applications manage workloads efficiently. Through a hands-on lab, learners will implement a Java-based scheduler in the LMS backend that adjusts task execution based on system load, using CloudWatch metrics.

This module addresses the critical challenges in cloud computing, including availability, fault tolerance, multi-tenancy risks, security, and compliance. Learners will explore how AWS services like IAM, CloudWatch, and encryption tools help mitigate these risks. The module includes a case study on cloud outages and SLA enforcement, guiding learners through the process of defining and monitoring service-level objectives. In the lab, learners will configure IAM roles, simulate failures, and analyse recovery metrics using CloudWatch.