COMP4349: Semester 1, 2023

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Units COMP4349 Semester 1 2023 [Normal day]

Unit of study_

COMP4349: Cloud Computing

Semester 1, 2023 [Normal day] - Remote

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	COMP4349
Academic unit	Computer Science
Credit points	6
Prohibitions ?	COMP5349 OR OCMP5349
Prerequisites ?	INFO1110 or INFO1910 or ENGG1810 or DATA1002
Corequisites ?	Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103
Assumed knowledge ?	Knowledge of OS concepts as covered in INFO1112
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ying Zhou, ying.zhou@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Written examination Written examination	50%	Formal exam period	2 hours
Outcomes assessed:
Assignment	AWS Project Practical Assignment	20%	Week 12 Due date: 19 May 2023 at 23:59	10 hours
Outcomes assessed:
Small continuous assessment	AWS Lab Practice Weekly AWS Lab Practice	30%	Weekly	12 hours
Outcomes assessed:
= hurdle task ?

Assessment summary

AWS lab practice: Lab practices are worth 5 points each and the highest-scoring 6 will contribute to the final lab practice mark. There is no strict weekly deadline for submissions, but it is recommended to submit the labs during the corresponding week. The final lab practice mark will be determined on May 26, 2023 at 11:59 PM and any labs submitted after that time will not be considered.
AWS project: An application migration project involves a range of AWS services.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard. 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 sydney.edu.au/students/guide-to-grades.

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:

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

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Cloud computing overview	Lecture (2 hr)
Week 01	Introduction to AWS Academy	Computer laboratory (2 hr)
Week 02	Cloud compute service	Lecture (2 hr)
Week 02	Intro to Amazon EC2&S3	Computer laboratory (2 hr)
Week 03	AWS Compute Service	Lecture (2 hr)
Week 03	Amazon EC2	Computer laboratory (2 hr)
Week 04	Cloud Storage	Lecture (2 hr)
Week 04	Amazon S3	Computer laboratory (2 hr)
Week 05	Cloud Database	Lecture (2 hr)
Week 05	Amazon RDS	Computer laboratory (2 hr)
Week 06	Replication and Consensus	Lecture (2 hr)
Week 06	Paxos Tutorial	Tutorial (2 hr)
Week 07	Cloud Networking	Lecture (2 hr)
Week 07	Amazon VPC	Computer laboratory (2 hr)
Week 08	Cloud Security	Lecture (2 hr)
Week 08	Amazon IAM	Computer laboratory (2 hr)
Week 09	Cloud monitoring	Lecture (2 hr)
Week 09	Amazon autoscaling	Computer laboratory (2 hr)
Week 10	Cloud automation	Lecture (2 hr)
	Amazon CloudFormation	Computer laboratory (2 hr)
	Microservices architecture:container	Lecture (2 hr)
	Docker and Amazon ECS	Computer laboratory (2 hr)
Week 11	Microservices architecture: Serverless architecture	Lecture (2 hr)
Week 12	AWS Lambda	Computer laboratory (2 hr)
Week 13	Unit of study review	Computer laboratory (2 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 virtualisation and containerisation
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.

This a new code for undergraduate cohort

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

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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