Module Specification

Advanced Cloud-Native Development

London school of INNOVATION

Module Specification

Advanced Cloud-Native Development: Mastering Scalable, Secure, Cloud Applications


Modern cloud applications must balance scalability, security, and dynamic responsiveness. This module delves into the specifics of cloud-native design, offering a rich understanding of serverless architectures, secure storage practices, and managed databases across AWS and Azure.

In this module, you will build and deploy serverless functions, master secure access controls, and establish robust cloud storage solutions. You will explore NoSQL and relational databases, implement event-driven architectures, and design secure APIs. Through hands-on practice, you will gain proficiency in Infrastructure as Code, centralised logging and monitoring, and multi-cloud strategies.

By completing this module, you will be well-prepared to manage complex cloud environments, ensure the security of your applications, and handle real-world challenges with confidence. You'll gain invaluable experience with cloud platforms, making you a sought-after expert in the field.


Code Number of Credits ECTS Credits Framework HECoS code
CD71 30 15 FHEQ - L7 programming (100956)

Learning outcomes

Code Attributes developed Outcomes
LO1 Knowledge and Understanding Demonstrate comprehensive knowledge of modern serverless application implementation using dominant cloud computing platforms.
LO2 Intellectual Skills Systematically analyse the complexities of multi-cloud strategies to identify optimal solutions for latency, data sovereignty, and cost optimisation.
LO3 Technical/Practical Skills Automate infrastructure provisioning and configuration using Infrastructure as Code (IaC) principles on AWS and Azure platforms.
LO4 Technical/Practical Skills Develop and deploy secure, event-driven microservices, integrating with cloud storage and database services in AWS and Azure.
LO5 Professional/Transferable Skills Strategically evaluate and advocate ethical and professional practices in the development and deployment of cloud-native applications.

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

Student workload

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
300.00

Content Structure

Week Chapter Name Chapter Description
Week 1 Serverless Function Development Embrace the flexibility and scalability of serverless computing to build efficient, cost-effective applications. Understand how event-driven microservices respond to various triggers such as HTTP requests and message queues, reducing infrastructure management and enhancing agility. Master AWS Lambda and Azure Functions to rapidly deploy on-demand functions that meet dynamic user needs, enabling quicker time to market and improved user experiences.
Week 2 Implementing Secure Access Protect your applications by enforcing strict access controls. Learn to apply role-based access mechanisms like AWS IAM and Azure RBAC to ensure only authorised users and services can access resources. By embracing the principle of least privilege, safeguard your systems against unauthorised access and potential breaches. Understand the importance of identity and access management in maintaining a secure cloud environment and complying with regulatory requirements.
Week 3 Leveraging Cloud Storage Optimise data management by utilising scalable cloud storage solutions. Understand the importance of securing unstructured data with encryption and access controls in services like AWS S3 and Azure Blob Storage. By managing data lifecycle effectively, reduce costs and maintain data integrity. Learn to implement fine-grained security controls such as bucket policies and shared access signatures to protect data and manage permissions efficiently.
Week 4 Managing Cloud Databases Address diverse data requirements with managed databases that scale effortlessly. Explore how to leverage services like AWS DynamoDB, Amazon RDS, Azure Cosmos DB, and Azure SQL Database while implementing robust security measures. Protect sensitive data with encryption at rest and in transit, and secure credential management using AWS Secrets Manager and Azure Key Vault to maintain compliance and trust. Understand automated scaling, backups, and replication features for high availability.
Week 5 Designing Event-Driven Systems Create responsive applications that adapt to real-time events and user interactions. By designing event-driven architectures with AWS EventBridge and Azure Event Hubs, achieve scalability and resilience. Embrace patterns such as event filtering, routing, and fan-out mechanisms that enable decoupled services, reducing complexity and improving fault tolerance. Build systems that can dynamically adjust to changing workloads and market demands.
Week 6 Securing and Managing APIs Build secure, well-managed API layers that are essential for modern applications. Understand how to protect APIs using AWS API Gateway and Azure API Management with features like API keys, OAuth 2.0, and custom authorisers. By monitoring and securing APIs, enhance user trust and system reliability. Learn to integrate APIs with serverless functions to create robust, scalable microservices architectures that support your application ecosystem.
Week 7 Automating Infrastructure Ensure consistent and repeatable deployments by automating infrastructure provisioning. Leverage Infrastructure as Code with AWS CloudFormation and Azure Resource Manager to define and manage cloud resources. Embed security policies and access controls directly into your infrastructure definitions. By automating, reduce errors, streamline updates across environments, and maintain compliance through consistent configurations.
Week 8 Enhancing Observability Gain deep insights into application performance and health through robust monitoring. Implement comprehensive observability practices using AWS CloudWatch, Azure Monitor, and integrating with third-party tools like the ELK Stack for enhanced log analysis and data visualisation. By proactively identifying and resolving issues, improve system reliability and user satisfaction. Configure alerts, dashboards, and metrics to track key performance indicators effectively.
Week 9 Building Multi-Cloud Solutions Avoid vendor lock-in and increase resilience by developing applications across multiple clouds. Learn strategies to manage resources in AWS and Azure using tools like Terraform, Kubernetes, and Crossplane. Address challenges related to latency, data sovereignty, failover mechanisms, and cost optimisation. By leveraging the strengths of each platform, optimise performance, ensure business continuity, and meet global compliance standards.

Module References

Type Description
Book Gilbert, J. (2018). Cloud Native Development Patterns and Best Practices: Practical architectural patterns for building modern, distributed cloud-native systems. Packt Publishing Ltd.
Website Link GitHub- Cloud Native Development Patterns and Best Practices

Methods of teaching/learning


Introductory lecture (1.50 hours)

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) (36.00 hours)

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 (18.00 hours)

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 (27.00 hours)

The 9 weekly sessions following the introduction (weeks 2 to 10) will be dedicated to teaching the contents of the module during interactive workshops. These sessions will complement the theory with practice, experience or analysis. Their purpose is to advance the student's cognition from 'knowledge' to 'understand' and 'apply'.

Depending on the nature of the content, challenges and learning activities will be pre-designed to apply flipped learning, and may include hands-on project work, group discussions or debates, roleplay, simulation, case study or other presentation, 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. There will be an opportunity also for Q&A in every session.


Independent reading, exploration and practice (153.50 hours)

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 (64.00 hours)

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.

Programmes this module appears on

Programme Term Type
1 Software Technical Leadership (MSc) 2 Optional
Please note that 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: Mastering Scalable, Secure, Cloud Applications (CD71)