Module Specification

Advanced Cloud-Native Development

Module Specification

Advanced Cloud-Native Development: Modern, Resilient and Scalable Applications



Organisations today strive for elasticity and resilience in a landscape that demands constant innovation. This module provides you with an extensive foundation for mastering these demands. You'll delve into serverless architectures, multi-cloud strategies, and the intersection of security and scalability. By focusing on AWS and Azure, you'll understand how to create robust systems that adapt seamlessly to dynamic changes while maintaining top-tier security standards.

This module will explore key areas such as serverless computing, leveraging tools like AWS Lambda and Azure Functions to build responsive microservices. You'll gain insights into secure data management through AWS S3 and Azure Blob Storage, learning encryption, access control, and lifecycle management. The curriculum addresses cloud-native databases, offering knowledge on AWS DynamoDB and Azure Cosmos DB, embedding Infrastructure as Code principles for efficient resource provisioning on AWS and Azure. You'll also work with monitoring tools to ensure your applications maintain optimal performance and security.

With hands-on exposure, you'll learn to implement a multi-cloud architecture, using Terraform to manage resources effectively across platforms. This ensures not only flexibility and resilience but also helps you steer clear of vendor lock-in. As you progress, you'll cultivate skills that embed security holistically in your work, configuring IAM roles, policies, and access controls using real-world scenarios. By completing this module, you gain an advanced skillset that empowers you to enact transformative solutions in cloud-native development, equipping you to excel in an ever-competitive tech horizon.


Mode(s) of Study Code CATS Credits ECTS Credits Framework HECoS code
Full-time blended
Part-time blended
CD71 30 15 FHEQ - L7 programming (100956)

Prerequisites and Co-requisites

None

Learning Outcomes

Code Attributes developed Outcomes
LO1 Knowledge and Understanding Demonstrate an in-depth understanding of cloud-native application design principles, including serverless and event-driven architectures on AWS and Azure.
LO2 Intellectual Skills Critically evaluate multi-cloud strategies to optimise application latency, failover, and data sovereignty.
LO3 Technical/Practical Skills Deploy and manage cloud data solutions with robust security, using AWS and Azure.
LO4 Technical/Practical Skills Design and implement cloud-native applications using AWS Lambda and Azure Functions, focusing on scalability and response to events.
LO5 Professional/Transferable Skills Apply professional standards in configuring Identity and Access Management (IAM) to ensure secure cloud environments.

Content Structure

Week Topic
Week 1 Introductory lecture
Introduces the module, outlining its relevance to the field and connections to other topics. It provides an overview of the content structure, key references, and assessment details.
Week 2 Serverless Architecture
Discover how to build agile applications using serverless computing on AWS and Azure. Harness the power of AWS Lambda and Azure Functions to create microservices that respond to events like HTTP requests, file uploads, and message queues—all without managing servers. Understand why adopting serverless models enhances scalability, reduces operational overhead, and accelerates development cycles. By focusing on event-driven, responsive architectures, you'll learn how to deliver value rapidly while optimising resources and costs.
Week 3 Secure, Responsive Microservices
Learn to develop microservices that are both responsive and secure. Implement triggers for your services using events like HTTP requests, file uploads, and message queues. Apply role-based access controls to enforce least-privilege principles, ensuring users and services have only the permissions they need. Explore secure API management with AWS API Gateway and Azure API Management to protect and monitor your endpoints. Understand how combining microservices with robust security practices enhances scalability and safeguards your applications.
Week 4 File Storage and Management
Explore strategies to secure data in AWS S3 and Azure Blob Storage. Implement encryption, fine-grained access control, and lifecycle management to protect and optimise data storage. Understand the importance of access keys and bucket policies in maintaining data integrity and security. By mastering cloud storage security, you'll ensure that sensitive data remains protected while being accessible when and where it's needed.
Week 5 Cloud NoSql Databases
Utilise AWS DynamoDB and Azure Cosmos DB to manage dynamic workloads effectively. Learn how automated scaling, backup, and replication ensure your applications are resilient and highly available. Discover why choosing cloud-native databases supports scalability and performance for modern applications. By integrating these databases, you'll handle vast amounts of data with ease, providing users with fast and reliable services.
Week 6 Infrastructure as Code
Automate the provisioning of cloud resources using Infrastructure as Code principles with AWS CloudFormation and Azure Resource Manager. Discover how IaC promotes consistency, security, and efficiency, enabling rapid deployment and version control of infrastructure. Understand why automating infrastructure helps prevent configuration drift and allows for repeatable, auditable deployments. By mastering IaC, you'll streamline operations and enhance collaboration across teams.
Week 7 Application Monitoring for Optimisation
Set up robust monitoring with AWS CloudWatch and Azure Monitor to track application health, performance, and security. Learn to configure alerts and logs to proactively address issues, ensuring optimal performance and reliability of your applications. Understand why continuous monitoring is essential for maintaining service levels and responding swiftly to anomalies. By mastering these tools, you'll keep your applications running smoothly and meet user expectations.
Week 8 Multi-Cloud Strategies
Design and implement multi-cloud architectures using tools like Terraform. Optimise for factors like latency, failover, data sovereignty, and cost by managing resources across AWS and Azure. Understand how multi-cloud strategies enhance flexibility, resilience, and prevent vendor lock-in. By orchestrating resources in multiple clouds, you'll build applications that are robust, compliant, and cost-effective.
Week 9 Identity and Access Control
Gain hands-on experience with Identity and Access Management (IAM) in AWS and Azure. Configure roles, policies, and access controls to enforce security best practices. Understand why strong identity management is crucial for secure cloud applications. By fortifying IAM, you'll ensure that only authorised users and services can access your resources, protecting against unauthorised access and potential breaches.
Week 10 Integrated Security
Embed layered security models into your cloud-native applications. Implement encryption, access controls, and identity-based policies throughout your stack. Learn why integrating security at every layer is essential for protecting applications and data in the cloud. By adopting a defence-in-depth approach, you'll build robust applications that safeguard against a variety of threats, ensuring trust and compliance.

Student Workload

The methods of teaching and learning for this module are based on the School's Technical 30 teaching system, consisting of the following activities.

Activity Total hours
Introductory lecture 1.50
Concept learning (knowledge graph) 36.00
AI formative assessment 18.00
Workshop/Lab Sessions 27.00
Independent reading, exploration and practice 153.50
Summative assessment 64.00
Total: 300.00

Teaching and Learning Methods

Activity Description
Introductory lecture

This is the first weekly session, dedicated to providing a comprehensive introduction to the module. The module leader will present an overview of the subject, elucidating its importance within various digital engineering professions and its interrelation with other modules. Students will need no preparation ahead of attending this session.

The module leader will provide a structured breakdown of the content to be covered in the subsequent 9 sessions. Students will also receive an outline of the essential reference materials, alongside suggestions for supplementary reading. The format and criteria for the summative assessment will be delineated, followed by a dedicated period for questions and answers.

A recording of the session will be available to facilitate async engagement for any other student who missed the class, also offering an opportunity to review the content again.

Concept learning (knowledge graph)

Our institution's approach to teaching is primarily based on flipped learning. Ahead of each weekly session (Workshop/Lab), students will be required to study the essential concepts that are used in the coming session so they are familiar with the theories and ideas related to that session. The study material will be in the form of written content, illustrations, pre-recorded lectures and tutorials, and other forms of content provided through the AGS.

This content is self-navigated by the students, accommodating different learning styles and schedules, allowing students to watch or listen to them at their own pace and review them as needed.

AI formative assessment

Once each concept of the theory is studied, students will be prompted to engage in formative assessment with instant AI feedback. They include multiple-choice questions, socratic questions and answers, written questions, role-play and other AI-assisted practice scenarios.

The purpose of this automated formative assessment is to provide students with immediate feedback on their understanding of module material and highlight any areas that need support or further study. They are also used to track student progress, boost motivation and promote accountability.

Workshop/Lab Sessions

Those studying in the blended learning mode will attend these 9 weekly classes (in person or remotely) during weeks 2 to 10. These sessions will complement the theory already studied during the preceding week (in our flipped-learning model), with discussions, analysis, practice or experience . They will be interactive and participatory, rather than one-way lectures. There will also be an opportunity for Q&A in every session. Depending on the nature of the content, challenges and learning activities will be pre-designed to apply flipped learning. They may include hands-on project work, group discussions or debates, roleplay, simulation, case studies, presentations, and other learning activities and opportunities. These workshops present an opportunity to apply critical thinking and problem-solving skills. They also encourage collaboration and foster a sense of community among students.

Independent reading, exploration and practice

This activity challenges students to engage with the reference material and independently explore and analyse academic literature related to the course topic. Students are expected to select relevant sources, practice critical reading skills, and where applicable technical skills, and synthesise information from multiple references. This is an opportunity to enhance research abilities, critical thinking, and self-directed learning skills while broadening and deepening subject knowledge.

Summative assessment

Summative assessments are used to evaluate student learning at the end of a module. These assessments can take many forms, including exams, papers, or presentations. Instructors can use summative assessments to measure whether students have achieved the learning outcomes for the module and provide them with a sense of their overall progress. Summative assessments can also be used to evaluate the effectiveness of the teaching methods used in the module.


Assessment Patterns

Weighting Format Outcomes assessed
60% Technical Analysis and Solution Assessment
This assessment requires students to develop a solution to a complex problem within a simulated domain, followed by a detailed analysis and reflection on their design and its theoretical underpinnings. The aim is to assess students' abilities to design practical solutions, critically analyse their work, and articulate their understanding of the technical and theoretical aspects of the module.
K LO1
I LO2
T LO3
T LO4
P LO5
40% Invigilated Exam
This is a time-limited and closed-book exam with a mix of multiple-choice and analytical written questions that students undertake during the summative assessment period as scheduled under the School’s remote invigilation conditions to ensure quality and academic integrity.

The exam enables the students to demonstrate their successful attainment of the module learning outcomes, primarily related to knowledge and understanding, and secondarily related to Professional/Transferable Skills.

The analytical written questions will consist of problem questions representing issues and dilemmas students are likely to encounter in professional life and students have to synthesise and apply what they have learnt on the module in order to produce sound and reasoned judgements with respect to the problem.

To enable the students to practice and prepare, various formative assessment activies, including quizzes and a AI-augmented assignments and mock exams are built into the module. Additionally, throughout the course, students will regularly receive feedback on their knowledge and assignments from AI as well as peers and staff to indicate how to improve future work and how to give constructive feedback to others.
K LO1
I LO2
P LO5

References/Indicative Reading List

Importance ISBN Description
Core Textbook 9781617294297 Davies, C. Cloud Native Patterns. Manning Publications. 2019
Core Textbook 9781484272268 Goniwada, S. Cloud Native Architecture and Design. Apress, 2021
Supplementary Reading 9781119814771 Raj, P. Vanga, S. Chaudharym A. Cloud-native Computing. Wiley-IEEE Press, 2022
Supplementary Reading 9781838643317 Arora, Kamal, Farr, Erik and Gilbert, John. Architecting Cloud Native Applications. Packt Publishing, 2019
Supplementary Reading 9781788473927 Gilbert, John Cloud Native Development Patterns and Best Practices
Supplementary Reading 9781804618707 Jacob, Jeveen, Natarajan, Subash. Multi-Cloud Handbook for Developers: Learn how to design and manage cloud-native applications in AWS, Azure, GCP, and more. Packt Publishing, 2024
Supplementary Reading 9781597497268 Sitaram, Dinkar, and Geetha Manjunath. Moving to the cloud: Developing apps in the new world of cloud computing. Elsevier, 2011.
Supplementary Reading 9781787280540 Laszewski, Tom, Arora, Kamal and Farr, Erik. Cloud Native Architectures. Packt Publishing, 2018
Supplementary Reading 9781492076339 Titmus, Matthew A. Cloud Native Go. O'Reilly Media, 2021
Supplementary Reading 9781492048909 Reznik, Pini. Cloud Native Transformation: Practical Patterns for Innovation. O'Reilly Media, 2020

Programmes Linked to This Module

Programme Term Type
1 MSc Software Technical Leadership 2 Optional

Module Approval

Stage Version Date of approval Authority Chair Revalidation
Compliance 1.0 Academic Board Dr Paresh Kathrani
Pre-Teaching 1.0 Director of Education Dr Paresh Kathrani
Note: The information detailed within this record is accurate at the time of publishing and may be subject to change.
Module Spec: Advanced Cloud-Native Development: Modern, Resilient and Scalable Applications (CD71)