Cloud App Development and Management
Code: 44735 ECTS Credits: 6| Degree | Type | Year | Semester |
|---|---|---|---|
| 4318303 Reseach and Innovation in Computer Based Science and Engineering | OT | 0 | 2 |
Contact
- Name:
- Antonio Miguel Espinosa Morales
- Email:
- antoniomiguel.espinosa@uab.cat
Teaching groups languages
You can check it through this link. To consult the language you will need to enter the CODE of the subject. Please note that this information is provisional until 30 November 2023.
Teachers
- Remo Lucio Suppi Boldrito
- Pedro Luis Pons Pons
Prerequisites
It is recommended to have a basic knowledge of programming languages like Python and basic skills of any Linux distribution.
Objectives and Contextualisation
The objectives of the module:
-Solve data analysis problems with open source tools
-Understand tool data management limitations and learn criteria to select suitable tools for a specific problem
-Learn data query methodologies related to each technology
-Use Cloud Computing providers to solve data analysis problems
-Apply a data analysis methodology to solve practical problems
By the end of the lectures and practical labs students should have enough knowledge to understand the requirements of typical large data analysis problems in industrial contexts. They should be able to pick some combination of tools and design a solution for a given large data analysis problem. This subject is oriented to develop data problem solving skills. Languages, tools and techniques are described in a data analysis context and students will solve a list of data problems applying the technology described at every chapter.
Learning Outcomes
- CA14 (Competence) Graduates will be able to design reliable, efficient and secure data processing and storage systems, using cloud computing.
- CA15 (Competence) Graduates will be able to develop innovative research projects in the face of new scientific and engineering challenges using cloud computing.
- KA19 (Knowledge) Describe architectural principles in order to explain cloud-based applications and organise their services.
- KA20 (Knowledge) Identify the main services offered by cloud computing.
- SA24 (Skill) Develop computing systems based on cloud resources.
- SA25 (Skill) Develop a cloud application architecture for private or public services whilst managing resources, costs and security requirements.
- SA26 (Skill) Evaluate a prototype cloud application including its cost, resources, security and maintenance requirements over time.
Content
1. Introduction to Cloud Computing: benefits, challenges and risks.
2. Cloud Computing Models: Infrastructure / Platform / Software as a Service.
3-Virtual private cloud and node network configuration
4-Basic computation services
5-Basic storage services
6-Elasticity and scalability
7-Cost evaluation: TCO
Methodology
The methodology will combine classroom work and problem solving in laboratory sessions.
Lab sessions will be scheduled at the beginning of the course and will use the same Teams space for the development of all practical labs. Students will use a local Linux environment: native, using local or remote Cloud Computing services.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Activities
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Lab | 26 | 1.04 | CA14, KA19, KA20, SA24, SA25, SA26, CA14 |
| Theory | 38 | 1.52 | CA14, CA15, KA19, KA20, CA14 |
| Type: Autonomous | |||
| Lab development | 62 | 2.48 | CA14, KA20, SA24, SA25, SA26, CA14 |
Assessment
Evaluation will come out from the combination of work developed in the lab sessions.
Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Computational lab | 40% | 6 | 0.24 | CA14, KA19, KA20, SA24, SA25 |
| Elasticity lab | 20% | 6 | 0.24 | CA14, CA15, KA19, SA26 |
| TCO lab | 20% | 6 | 0.24 | CA14, KA19, KA20, SA24, SA26 |
| VPC lab | 20% | 6 | 0.24 | CA14, KA20, SA24, SA25 |
Bibliography
A. Wittig, M. Wittig. "Amazon Web Services in Action", Manning, 2nd Edition, 2018.
G. Coulouris, J. Dollimore and T. Kinderg, "Distributed Systems. Concepts and design ", Addison-Wesley, 5th edition, 2012.
Bell, Charles; Kindahl, Mats; Thalmann, Lars. "MySQL High Availability". O'Reilly, 2010.
Chang, Fay, et al. "Bigtable: A Distributed Storage System for Structured Data." OSDI, 2006
Dewitt, David, and Jim Gray. "Parallel Database Systems: The Future of High Performance Database Processing." Communications of the ACM 35, no. 6 (1992): 85-98
Schwartz, Baron; Zaitsev, Peter; Tkachenko, Vadim; Zawodny, Jeremy D.; Lentz, Arjen; Balling, Derek J. "High Performance MySQL", O'Reilly, 2008.
Seyed M. M. "Saied" Tahaghoghi and Hugh E. Williams. Learning MySQL. O’Reilly, 2006
Nathan Haines. “Beginning Ubuntu for Windows and Mac Users”. Apress 2015. recurs electrònic a la biblioteca de la UAB
William E. Shotts. “The Linux Command Line”. Second Internet Edition. 2013. http://linuxcommand.org/tlcl.php
Dan C. Marinescu. “Cloud Computing. Theory and Practice”. Morgan-Kaufmann. 2018.
R. Buyya, R. N. Calheiros, A. V. Dastjerdi. “Big data. Principles and paradigms”. Morgan-Kaufmann. 2016.
Software
Students will use latest version of Ubuntu Linux. During the first lab sessions students who need it will receive a configuration tutorial of Windows 11 WSL