OCMP5349: Semester 1b, 2024

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Units OCMP5349 Semester 1b 2024 [Online]

Unit of study_

OCMP5349: Cloud Computing

Semester 1b, 2024 [Online] - Online Program

Overview

This unit covers topics of active and cutting-edge research within IT in the area of 'Cloud Computing'. Cloud Computing is an emerging paradigm of utilising large-scale computing services over the Internet that will affect individual and organization's computing needs from small to large. Over the last decade, many cloud computing platforms have been set up by companies like Google, Yahoo!, Amazon, Microsoft, Salesforce, Ebay and Facebook. Some of the platforms are open to public via various pricing models. They operate at different levels and enable business to harness different computing power from the cloud. In this course, we will describe the important enabling technologies of cloud computing, explore the state-of-the art platforms and the existing services, and examine the challenges and opportunities of adopting cloud computing. The unit will be organized as a series of presentations and discussions of seminal and timely research papers and articles. Students are expected to read all papers, to lead discussions on some of the papers and to complete a hands-on cloud-programming project.

Unit details and rules

Unit code	OCMP5349
Academic unit	Computer Science
Credit points	6
Prohibitions ?	COMP5349 or COMP4349
Prerequisites ?	None
Corequisites ?	None
Assumed knowledge ?	Basic knowledge of computer networks as covered in INFO1112 or COMP9201 or COMP9601 (or equivalent UoS from different institutions)
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Ali Anaissi, ali.anaissi@sydney.edu.au
Tutor(s)	James Phung, james.phung@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Project A term long project	20%	Week 06 Due date: 24 May 2024 at 23:59	6 weeks
Outcomes assessed:
Supervised exam ?	Final Exam Final Exam taken in Week 8	50%	Week 08	2 hours
Outcomes assessed:
Small continuous assessment	AWS Challenge Labs Challenge Labs taken in the AWS Instance of Canvas.	30%	Weekly Due date: 24 May 2024 at 23:59	60 to 90 minutes per week
Outcomes assessed:
= hurdle task ?

Assessment summary

Challenge Labs: Each week, you will complete a Challenge Lab using AWS Academy's Canvas platform where you will demonstrate practical skills in a particular area of Cloud Architecting.
Project: You will design and implement a Cloud solution to solve a set problem using AWS Academy's Canvas platform.
Final Exam: You will answer a series of questions that test your understanding of Cloud Computing concepts that you have studied in this unit under examination conditions.

The final exam is a hurdle task. You must score at least 40% in the final exam in order to pass this unit.

Detailed information for each assessment can be found on Canvas. Assessment rubrics and submission instructions are published on Canvas.

Assessment criteria

Result name	Mark range	Description
High Distinction	85 - 100	Excellent course work
Distinction	75 - 84	Very good course work
Credit	65 - 74	Good course work
Pass	50 - 64	Fair course work
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Challenge Labs that are submitted late will be awarded zero marks. Standard late penalties apply for the Project.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Cloud Computing Overview	Lecture (4.18 hr)
Week 01	Cloud Computing Overview	Workshop (1.5 hr)
Week 02	Cloud Computing Services	Lecture (3.5 hr)
Week 02	Cloud Computing Services	Workshop (1.5 hr)
Week 03	Cloud Database Services	Lecture (4.75 hr)
Week 03	Cloud Database Services	Workshop (1.5 hr)
Week 04	Cloud Networking and Security	Lecture (4.45 hr)
Week 04	Cloud Networking and Security	Workshop (1.5 hr)
Week 05	Cloud Scalability and Automation	Lecture (4.02 hr)
Week 05	Cloud Scalability and Automation	Workshop (1.5 hr)
Week 06	Micro Services Architecture	Lecture (2.97 hr)
Week 06	Micro Services Architecture	Workshop (1.5 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. develop a comprehensive understanding of cloud computing concepts, architecture, and design principles.
LO2. explain cloud-enabling technologies, including virtualization and containerization
LO3. gain proficiency in using cloud-based tools and technologies, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
LO4. acquire expertise in different cloud storage and databases
LO5. gain expertise in securing cloud-based solutions, including data protection and network security.
LO6. acquire an understanding of emerging cloud technologies and trends, such as microservices architecture and serverless computing.
LO7. create a solution architecture for transitioning to the cloud

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Some learning activities and the project have been modified.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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