| Code |
16227
|
| Year |
3
|
| Semester |
S1
|
| ECTS Credits |
6
|
| Workload |
PL(30H)/T(30H)
|
| Scientific area |
Informatics
|
|
Entry requirements |
There are no prerequisites.
|
|
Learning outcomes |
The main objective of this curriculum unit is to provide a broad and detailed overview of the processes required to develop cloud applications capable of processing large volumes of data. Thus, it aims to give students a comprehensive and integrated perspective on the concepts and technologies necessary to build native cloud software.
|
|
Syllabus |
Introduction to cloud computing and emerging environments. Cloud infrastructures, middleware, and web services. Distributed processing of large volumes of data, the development of native cloud applications, and finally, concepts regarding scalability and performance optimizations.
|
|
Main Bibliography |
- Dan C. Marinescu, "Cloud Computing: Theory and Practice", 3.ª Edição, Morgan Kaufmann, 2022.
- Letha H. Etzkorn, "Introduction to Middleware: Web Services, Object Components, and Cloud Computing," 1.ª Edição, Chapman and Hall/CRC, 2017.
- V. Naresh Kumar, "Modern Big Data Processing with Hadoop," 1.ª Edição, Packt Publishing, 2018.
- Dean, Jeffrey, e Sanjay Ghemawat, "MapReduce: simplified data processing on large clusters," Communications of the ACM, 2018.
- Chang, Fay, et al. "Bigtable: A distributed storage system for structured data," ACM Transactions on Computer Systems, 2008.
|
|
Teaching Methodologies and Assessment Criteria |
Expository lectures for knowledge acquisition. Execution of two main projects, primarily focusing on i) analysis of a provided case study and ii) development of a native cloud application with the ability to process large volumes of data. At the end of the semester, the cloud application will be orally presented by the students using a slide set.
Theoretical and practical components are assessed using three main elements:
- One written tests for knowledge evaluation worth 40%.
- Synthesis project worth 20% on one of the following topics:
- Topic 1 - Distributed processing of large volumes of data.
- Topic 2 - Containerization and orchestration of services and applications.
- Laboratory project worth 40% on the following topic: Development of an original cloud application with the integration of large-scale data processing.
|
|
Language |
Portuguese. Tutorial support is available in English.
|