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Cloud Services
Major: IT Product Management
Code of subject: 6.124.04.E.058
Credits: 4.00
Department: Information Systems and Networks
Lecturer: Dmytro Dosyn
Semester: 6 семестр
Mode of study: денна
Завдання: As a result of studying the academic discipline, the student must be able to demonstrate the following learning outcomes:
The ability to use theoretical and fundamental knowledge, skills and abilities to successfully solve complex specialized tasks and practical problems during professional activities in the field of computer science and information technology, computer engineering and modern technologies for designing and programming information systems, mastering computer skills to solve problems in the specialty.
Studying the academic discipline involves the formation and development of students' competencies:
general:
1) the ability to communicate in a second language;
2) the ability to learn;
3) the ability to communicate orally and in writing in Ukrainian;
4) the ability to apply knowledge in practical situations;
5) the ability to make informed decisions;
6) the ability to conduct research at the appropriate level;
7) the ability to think abstractly, analyze and synthesize;
8) skills in using information and communication technologies;
professional:
1) the ability to apply basic knowledge of fundamental sciences: mathematics, physics, electronics to solve typical problems of the specialty;
2) the ability to apply basic knowledge of basic regulatory legal acts and reference materials, current standards and technical conditions, instructions and other regulatory documents in the field of information technologies;
3) the ability to use methodologies and technologies for designing, applying and maintaining software, supporting their life cycle;
4) the ability to develop software using methods and technologies of object-oriented programming;
5) the ability to apply knowledge of mathematical methods of analysis and synthesis of complex objects and systems using modern methods of information technology;
6) the ability to apply knowledge of methods of collecting, processing, analyzing, systematizing and storing scientific and technical information;
7) the ability to apply knowledge of modern methods and tools of distributed systems, parallel computing;
8) the ability to apply knowledge of the principles and methods of building and using computer networks;
9) the ability to apply knowledge of the principles of WEB technologies and methods and means of their use to solve problems in the specialty;
10) the ability to apply knowledge of the basics of labor protection, industrial sanitation and fire safety when working with equipment and equipment.
professional competencies of the professional direction:
1) the ability to formulate new hypotheses, search for and visualize hidden data dependencies using artificial intelligence methods;
2) the ability to effectively choose appropriate directions and appropriate methods for solving problems in the field of information technology and artificial intelligence;
3) the ability to analyze unstructured data, search for dependencies using artificial intelligence methods,
4) the ability to use knowledge of the basics of digital signal processing and the ability to use them in the design of vision systems, processing speech signals, analysis and synthesis of images.
5) the ability to effectively plan, implement project activities and manage project risks and quality based on regulatory and methodological provisions, standards and norms of a specific application area for IT project management, to formulate requirements for the information system to meet the technical task;
6) the ability to study and critically evaluate new methodologies for IT project management, based on professional scientific literature sources in these areas;
7) the ability to be a leader in the development and implementation of an information system project;
8) the ability to effectively select a conceptual model of the information system environment, based on the methodology of data and knowledge engineering.
Learning outcomes: 1) the ability to demonstrate knowledge and understanding of the scientific and mathematical principles underlying information technologies;
2) the ability to demonstrate knowledge of the basics of professionally oriented disciplines of the specialty: methods and tools of modern information technologies, computer technology and modern technologies for designing and programming information systems, mathematical methods of analysis and synthesis of complex objects, methods of collecting, processing, analyzing, systematizing and storing scientific and technical information, methods and tools of distributed systems and parallel computing, principles and methods of building and applying computer networks, principles of web technologies and methods and tools of their use to solve problems of the specialty;
3) the ability to demonstrate in-depth knowledge in at least one of the areas of information technologies;
4) the ability to demonstrate knowledge and skills in conducting experiments, collecting data and modeling in the subject area;
5) the ability to demonstrate knowledge and understanding of methodologies for designing information systems;
6) ability to demonstrate knowledge of the current state of affairs and the latest technologies in the field of information technology;
7) ability to demonstrate understanding of the impact of technical solutions in a social, economic, social and environmental context;
8) ability to demonstrate knowledge of the basics of economics and project management;
Skills:
9) apply knowledge and understanding to identify, formulate and solve technical problems of the specialty, using known methods;
10) apply knowledge and understanding to solve problems of synthesis and analysis in systems that are characteristic of the chosen specialization;
11) think systematically and apply creative abilities to form fundamentally new ideas;
12) apply knowledge of technical characteristics, design features, purpose and rules of operation of equipment and equipment to solve technical problems of the specialty;
13) calculate, design, project, investigate, operate, adjust systems and objects for the chosen specialization;
14) search for information in various sources to solve problems of the specialty;
15) work effectively both individually and as part of a team;
16) identify, classify and describe the operation of systems and their components;
17) combine theory and practice, as well as make decisions and develop an activity strategy to solve the tasks of the specialty (specialization) taking into account universal human values, social, state and industrial interests;
18) perform relevant experimental research and apply research skills on professional topics;
19) evaluate the results obtained and defend the decisions made with arguments;
20) the ability to manage the development of software systems, use software tools and technologies for managing IT projects;
21) the ability to develop IT projects using case technologies;
22) the ability to evaluate the stage and final results of the implementation of IT project work and adjust the parameters of the IT project, determine actual risky events and potential risks of IT projects, take actions to respond to risks and external influences;
23) the ability to possess skills in the field of requirements management in IT projects, conducting strategic analysis, quality and cost management in IT projects, the ability to build information flow models using diagrammatic techniques and standards for developing information systems.
Required prior and related subjects: Previous:
Algorithmization and Programming
Information Systems Design
Information Security Technologies
Related:
Distributed Systems and Parallel Computing Technologies
Big Data Analysis Methods
Information Technologies for Data Processing
Summary of the subject: The academic discipline "Cloud Services" is an integral part of the cycle of computer disciplines necessary for analysts who, using modern computer and telecommunication technologies, collect, accumulate, process and analyze data. Modern information and communication technologies involve the use of virtualization technologies for server systems, communication tools for distributed computing and the development of software and hardware solutions for data centers. To manage heterogeneous computing resources remotely, software solutions are required for the implementation of virtualization systems, as well as remote service functions, which generally creates opportunities for the organization and application of cloud computing technologies.
The subject of the academic discipline is the principles and standards of technology operation and the development of solutions based on cloud computing. The object of the academic discipline is the processes of distributed computing. Studying the discipline allows students to master the knowledge and skills of analysis, modeling, optimization, generalization and dissemination of information using modern information technologies, in order to adapt and use modern software tools for processing ecological and economic information. The task is to form in students the competence in using standards and technologies for attracting and applying distributed computer resources provided on request for conducting scientific research and using the computing environment of organizations from the startup level to the corporation. Students should gain competence in choosing the architecture and building private and hybrid cloud computing systems, installing and configuring special software for working in the cloud environment.
Опис: • Introduction to cloud computing: concepts, development history, advantages and disadvantages.
• Cloud service delivery models: IaaS, PaaS, SaaS and their characteristics.
• Cloud systems architecture: components, principles of construction and operation. Microservices architecture in the cloud: principles of design, deployment and scaling of applications based on microservices.
• Virtualization technologies: the role of virtualization in cloud computing, types of hypervisors. Network services in the cloud: virtual networks, load balancing, auto-scaling and methods for ensuring high availability.
• Cloud platforms and providers: an overview of the main platforms (AWS, Azure, Google Cloud) and their services.
• Cloud security: threats, risks and methods for protecting data. Protecting access to objects in the cloud. Security, availability and disaster recovery strategies.
• Cloud data management: data storage, backup and recovery. Cloud storage solutions: Distributed file systems, NoSQL databases, object storage, and data consistency models.
• Distributed computing and cloud services: Principles of distributed systems and their integration with cloud technologies. Software-defined networking (SDN) and storage (SDS): Concepts and applications in cloud environments
• Cloud services for data analytics: Tools and platforms for processing big data in the cloud. Cloud machine learning services: An overview of cloud platforms and services for machine learning. Serverless computing and functions as a service (FaaS): Concepts, benefits, and use cases.
• Cloud migration: Strategies for moving existing systems and data to the cloud. Technical, economic, and organizational considerations. Rearchitecting applications for the cloud.
• Achieving transparency through platform virtualization.
• Elastic storage. Accessing IaaS. Provisioning servers on demand. Handling dynamic and static IP addresses. Management and monitoring tools and support.
• Economics of cloud computing: pricing models. Performance optimization and monitoring in the cloud: methods for improving application performance and resource utilization.
• Cloud services for software development: tools and platforms for DevOps in the cloud. Cloud application development and deployment: cloud service integration, DevOps practices, and CI/CD pipelines.
• Internet of Things (IoT) and cloud computing: IoT integration with cloud platforms. Edge and fog computing: integration with cloud services and applications in the Internet of Things.
• Cloud technology development prospects: trends, emerging technologies, and future challenges.
Assessment methods and criteria: Knowledge diagnostics takes place through the evaluation of completed laboratory work and passing an exam.
Критерії оцінювання результатів навчання: Laboratory work - max. 50 points
Documentation - max. 10 points.
Exam - max. 40 points.
Порядок та критерії виставляння балів та оцінок: 100-88 points - certified with an “excellent” grade - High level: the student demonstrates an in-depth mastery of the conceptual and categorical apparatus of the discipline, systematic knowledge, skills and abilities of their practical application. The mastered knowledge, skills and abilities provide the ability to independently formulate goals and organize learning activities, search and find solutions in non-standard, atypical educational and professional situations. The applicant demonstrates the ability to make generalizations based on critical analysis of factual material, ideas, theories and concepts, to formulate conclusions based on them. His/her activity is based on interest and motivation for self-development, continuous professional development, independent research activities, implemented with the support and guidance of the teacher. 87-71 points - certified with a grade of “good” - Sufficient level: involves mastery of the conceptual and categorical apparatus of the discipline at an advanced level, conscious use of knowledge, skills and abilities to reveal the essence of the issue. Possession of a partially structured set of knowledge provides the ability to apply it in familiar educational and professional situations. Aware of the specifics of tasks and learning situations, the student demonstrates the ability to search for and choose their solution according to the given sample, to argue for the use of a particular method of solving the problem. Their activities are based on interest and motivation for self-development and continuous professional development. 70-50 points - certified with a grade of “satisfactory” - Satisfactory level: outlines the mastery of the conceptual and categorical apparatus of the discipline at the average level, partial awareness of educational and professional tasks, problems and situations, knowledge of ways to solve typical problems and tasks. The applicant demonstrates an average level of skills and abilities to apply knowledge in practice, and solving problems requires assistance, support from a model. The basis of learning activities is situational and heuristic, dominated by motives of duty, unconscious use of opportunities for self-development. 49-00 points - certified with a grade of “unsatisfactory” - Unsatisfactory level: indicates an elementary mastery of the conceptual and categorical apparatus of the discipline, a general understanding of the content of the educational material, partial use of knowledge, skills and abilities. The basis of learning activities is situational and pragmatic interest.
Recommended books: Lecture notes, methodological instructions for laboratory work, methodological instructions for didactic support of independent work.
Main:
1. T. Erl, Cloud Computing: Concepts, Technology & Architecture. Upper Saddle River, NJ: Prentice Hall, 2013.
2. Antonopoulos, N., Gillam, L.: Cloud Computing: Principles, Systems and Applications" London: Springer, 2010.
3. "Distributed Computing and Cloud Services" Textbook. Kharkiv: NTU "KhPI", 2023.
4. "Cloud Technologies. Google Services" Methodological recommendations. Zaporizhzhia: ZDMU, 2020.
5. Petrenko A.I., Application of GRID technologies in science and education: handout for the course for students of the specialty "Information technologies of design". ? Kyiv: NTUU "KPI", 2008.
6. Zinchenko O.V. Cloud technologies: a manual / O.V. Zinchenko, S.M. Ishcheryakov, S.V. Prokopov, S.O. Serikh, V.V. Vasylenko. – Kyiv: FOP Gulyaeva V.M., 2020.
Recommended:
Basic
1. O. V. Zinchenko, S.M. Ishcheryakov, S.V. Prokopov, S.O. Serikh, V.V. Vasylenko, "Cloud technologies," Kyiv: FOP Gulyaeva V.M., 2020.
2. S. G. Litvinova, O. M. Spirin, L. P. Anikina, "Office 365 Cloud Services: A Tutorial," Kyiv: Komprint, 2015, 170 p.
3. M. S. Kingsley, Cloud Technologies and Services: Theoretical Concepts and Practical Applications, 1st ed., Cham, Switzerland: Springer, 2023.
4. L. H. Etzkorn, Introduction to Middleware: Web Services, Object Components, and Cloud Computing. Boca Raton, FL: CRC Press, 2017.
5. B. Furht and A. Escalante, Eds., Handbook of Cloud Computing, 1st ed. New York, NY, USA: Springer, 2010. [Online]. Available: https://www.amazon.com/Handbook-Cloud-Computing-Borko-Furht-ebook/dp/B008BBTD94/
6. Antonopoulos N. Cloud Computing. Principles. Systems and Applications / N. Antonopoulos, L. Gillam. —London; New York: Springer-Verlag, 2010.
7. Apache CloudStack Documentation: open source cloud computing[Electronic resource]. —Access mode: http://cloudstack.apache.org/docs/en-US/Apache_CloudStack/4.2.0/html/Installation_Guide/cloud-infrastructure-concepts.html
8. Cloud computing. Principles and Paradigms. / Edited by Rajkumar Buyya, James Broberg, Andrzej Goscinski. —New Jersey: John Wiley & Sons, Inc., 2011.
9. Oleksiuk V. P. Experience of integrating Google Apps cloud services into the information and educational space of a higher education institution. [Electronic resource]/ V. P. Oleksiuk // Information technologies and learning tools. —2013. —No. 3. —Access mode: http://journal.iitta.gov.ua/index.php/itlt/article/view/824/631
Ancillary:
1. V. P. Oleksiuk, "Fundamentals of cloud technologies," Kyiv: UMO, 2016.
2. Cloud computing. Principles and Paradigms. / Edited by Rajkumar Buyya, James Broberg, Andrzej Goscinski. —New Jersey: John Wiley & Sons, Inc., 2011.
3. Pepple K. Deploying OpenStack/ K. Pepple . - O'Reilly Media, 2011.
4. Thomas Erl, Zaigham Mahmood, and Ricardo Puttini, "Cloud Computing: Concepts, Technology & Architecture," Prentice Hall, 2013.
5. M. J. Kavis, Architecting the Cloud: Design Decisions for Cloud Computing Service Models. Hoboken, NJ: Wiley, 2014.
6. Shor R.M. Cloud computing for learning and performance professionals. – American Society for Training & Development, 2011.
7. Warschauer M. Learning in the Cloud: How (and Why) to Transform Schools with Digital Media. -New York: Teachers College, 2011.
8. M. Abdula, I. Averdunk, et al., The Cloud Adoption Playbook: Proven Strategies for Transforming Your Organization with the Cloud. Hoboken, NJ: Wiley, 2018.
9. H. Shah, Cloud Computing: A Hands-On Approach, 2nd ed. CreateSpace Independent Publishing, 2020.
Online Information Resources:
1. Public Cloud Services Comparison [Access Mode: http://comparecloud.in/]
2. Install OpenStack [Access Mode: http://docs.openstack.org/]
3. Deploying OpenStack: Virtual Infrastructure or Dedicated Hardware [Access Mode: https://www.researchgate.net/publication/263765728_Deploying_OpenStack_Virtual_Infrastructure_or_Dedicated_Hardware#read]
4. Alibaba Cloud Computing [Access Mode: https://www.alibabacloud.com/campaign/free-trial?spm=a3c0i.272861.9482640970.1.c43324afqAhueD]
5. An Introduction to Data Science (Jeffrey Stanton, 2013) [Access Mode: https://docs.google.com/file/d/0B6iefdnF22XQeVZDSkxjZ0Z5VUE/edit?pli=1]
6. School of Data Handbook (2015) [Access mode: http://schoolofdata.org/handbook/]
7. Data Jujitsu: The Art of Turning Data into Product (DJ Patil, 2012) [Access mode: http://www.oreilly.com/data/free/data-jujitsu.csp]
8. Art of Data Science (Roger D. Peng & Elizabeth Matsui, 2015) [Access mode: https://leanpub.com/artofdatascience]
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