Cloud Computing

Content

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.

Course 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.

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.

Weekly Contents

Assessment System

Relation of Proficiency

ECTS