Computer Engineering Department

Cloud Computing(INF472)

Course Code Course Name Semester Theory Practice Lab Credit ECTS
INF472 Cloud Computing 8 3 0 0 3 5
Prerequisites
Admission Requirements
Language of Instruction French
Course Type Elective
Course Level Bachelor Degree
Course Instructor(s) Özgün PINARER opinarer@gsu.edu.tr (Email)
Assistant
Objective The aim of this course is to study cloud computing as a distributed systems paradigm and to provide both theoretical and practical knowledge on virtualization, containerization, microservices architectures, Kubernetes, scalability engineering, observability, DevOps, cloud security, and cost optimization. The course equips students with the ability to design, deploy, and manage scalable, reliable, secure, and cost-efficient cloud-native systems.
Content • Cloud as a Distributed Systems Paradigm
• Virtualization and Containerization
• Cloud Networking Architecture
• Cloud Storage Systems
• Scalability Engineering
• Distributed Systems Deep Dive
• Microservices Architecture
• Kubernetes Architecture
• Autoscaling & Scheduling
• Observability & Reliability Engineering
• DevOps & Infrastructure as Code
• Cloud Security Architecture
• Cloud Economics & Cost Engineering
• Serverless & Edge Computing
Course Learning Outcomes Upon successful completion of the course, students will be able to:
1. Analyze cloud computing within the context of distributed systems.
2. Explain and implement virtualization and container technologies.
3. Design cloud networking and storage architectures.
4. Develop scalable and highly available systems.
5. Deploy and manage microservices architectures and Kubernetes-based systems.
6. Configure autoscaling and scheduling mechanisms.
7. Apply observability and reliability engineering principles.
8. Implement DevOps practices and Infrastructure as Code for CI/CD pipelines.
9. Design secure cloud architectures and perform risk assessments.
10. Conduct cloud cost analysis and optimization.
11. Evaluate serverless and edge computing paradigms.
Teaching and Learning Methods
References 1. Patni, Sakshi, Deepika Saxena, and Ashutosh Kumar Singh. Resource Management in Cloud Computing. 2025.
2. Ferreira, Haroldo. Cloud computing. Editora Senac São Paulo, 2025.
Print the course contents
Theory Topics
Week Weekly Contents
1 Cloud as a Distributed Systems Paradigm
2 Virtualization and Containerization
3 Cloud Networking Architecture
4 Cloud Storage Systems
5 Scalability Engineering
6 Distributed Systems
7 Microservices Architecture
8 Kubernetes Architecture
9 Autoscaling & Scheduling
10 Observability & Reliability Engineering
11 DevOps & Infrastructure as Code
12 Cloud Security Architecture
13 Cloud Economics & Cost Engineering
14 Serverless & Edge Computing
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 2 60
Contribution of final exam to overall grade 1 40
Toplam 3 100
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 1 30
Project 0 0
Laboratory 1 30
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Make-up 0 0
Toplam 2 60
No Program Learning Outcomes Contribution
1 2 3 4 5
Activities Number Period Total Workload
Total Workload 0
Total Workload / 25 0.00
Credits ECTS 0
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