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ICC104 Introduction to Cloud Computing
Creation date：2024-06-01 14:30:47
Belonging category：计算机computer science
Tag ICC104
Introduction to Cloud Computing

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ASSESSMENT

ICC104 Introduction to Cloud Computing
Assessment Project + Report
Individual/Group Individual
Length 2500 words (+/-10%)
Learning Outcomes This assessment addresses the Subject Learning
Outcomes outlined at the bottom of this document.
Submission Due by 11:55 PM AEST Sunday of Module 12
For intensive class: By 11:55 PM AEST Sunday of Module
6.
Weighting 40%
Total Marks 100
Context:
This assessment is designed to acquaint the students to public cloud platforms, their products, and
experience the concepts of virtualisation and resource pooling in the Cloud Environment.
Project:
The project comprises of two tasks;
1. Explore Google Cloud Platform, setup a Virtual Machine in Google Cloud, deploy LAMP (Linux,
Apache, MySQL and PHP) Server on that server install WordPress, without using any “Click to
Deploy” Images.
2. Explore Amazon Web Services, setup an EC2 instance in AWS, deploy LAMP (Linux, Apache,
MySQL and PHP) Server and on that server install WordPress, again without using “Ready to Deploy
Images”
The deliverables of this project will be a report and a demonstration that can be carried out by the
instructor in person or can be shared as screencasts of student’s project showing GCP and AWS
dashboards, WordPress dashboard and all login credentials of AWS and GCP accounts and
WordPress administrator with Public IP addresses of the registered instances or Virtual machines.
Instructions:
For AWS and Google Cloud Platform, you will register for a free Virtual Machine and Free Tier EC2
server.
The assessment requires you to prepare a report based upon your project and to record a screencast
of your Project. To do this you will need to consider the following and specifically add in the body of
the report:
1. Key service offering from Amazon Web Services and Google Cloud Platform.
2. Comparison of cost model of AWS EC2 and GCP VM.
3. The procedure you followed from the registration of your account to the deployment of
WordPress with supporting evidence like screenshots and logs.
4. Possible improvement suggestion in the process while remaining within the Cloud domain.
5. Comparison of both the Platform EC2 and VM.
6. The concept of virtualization and elastic resources in AWS and GCP.
Writing the report
Start off with a short introduction (approximately 100 words) stating what the assessment is about
and some basic information relevant to the Project. This section is to be written in complete
sentences and paragraphs. It should not contain any dot point information or tables, graphs and
diagrams.
The introduction should be followed by some background information (approximately 200 words), in
which you can provide some context related to cloud computing and the deployment models.
Then structure the main body of the report (approximately 2000 words) using the above 6 points as
sub - section headings. These sections should be written in complete sentences and paragraphs.
However, you can include items such as graphs, diagrams and tables if appropriate. Ensure that you
title these clearly, in the correct way, and reference using the APA system. If placing any tables,
graphs and diagrams in an appendix at the end of your report, you need to clearly state where the
item can be located. Generally, the information presented in appendices does not count towards the
total word count.
Finally, write a conclusion (approximately 200 words) as a summary of your project. This section
brings together all of the information that you have presented in your report and should link to the
purpose of the assessment as mentioned in the introduction. You can also discuss any areas that
have been identified as requiring further investigation and how this will work to improve or change
our understanding of the topic. This section does not introduce or discuss any new information
specifically, and like the introduction, will be written in complete sentences and paragraphs. No
tables, graphs, diagrams or dot points should be included.
Report
If you would like some assistance on writing your report, please refer to the link below.
Laureate academic skills unit (n.d.). Report Writing. Retrieved from https://laureate-
au.blackboard.com/webapps/blackboard/content/listContent.jsp?course_id=_20163_1&content_id
=_2498855_1&mode=reset
Demonstration
Your demonstration should be a screencast of the project showing GCP and AWS dashboards,
WordPress dashboard along with all login credentials of AWS, GCP accounts and WordPress
administrator with Public IP addresses of the registered instances or Virtual machines.
• After uploading your video presentation, retain a copy in a safe place.
Referencing
It is essential that you use appropriate APA style for citing and referencing research. Please see more
information on referencing here
You should submit through the Assessment 3 submission link under Assessment found in the main
navigation menu of the subject Blackboard site. Your assessment will be formally graded via the
Grade Centre by your Learning Facilitator and feedback will be provided through My Grades.
Case category
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CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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