Introduction to Cloud Technologies and SecurityLaajuus (5 cr)
Code: MS00CN44
Credits
5 op
Objective
After completing the course, the student can:
- learn about the history and background of Cloud Computing
- discover Cloud Computing including examples of real-world problems
- understand the most commonly used platforms for cloud computing such as Amazon AWS and Microsoft Azure (and possibly CSC Finland).
- understand the various Service models on Cloud as IaaS, PaaS, and SaaS
- learn the basic network security techniques in the cloud environment
Content
- Cloud computing
- Software-as-a-Service (SaaS)
- Platform-as-a-Service (PaaS)
- Infrastructure-as-a-Service (IaaS)
- Cloud computing technologies and tools
- Security in the cloud environment
Enrollment
02.07.2024 - 07.10.2024
Timing
07.10.2024 - 31.12.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Engineering and Business
Teaching languages
- Finnish
- English
Degree programmes
- Master of Business Administration, Interactive Technologies
- Master of Engineering, Data Engineering and AI
- Master of Business Administration, Data Engineering and AI
Teachers
- Ali Khan
Groups
-
YINTBS24
-
YDATIS24
-
YDATTS24
Objective
After completing the course, the student can:
- learn about the history and background of Cloud Computing
- discover Cloud Computing including examples of real-world problems
- understand the most commonly used platforms for cloud computing such as Amazon AWS and Microsoft Azure (and possibly CSC Finland).
- understand the various Service models on Cloud as IaaS, PaaS, and SaaS
- learn the basic network security techniques in the cloud environment
Content
- Cloud computing
- Software-as-a-Service (SaaS)
- Platform-as-a-Service (PaaS)
- Infrastructure-as-a-Service (IaaS)
- Cloud computing technologies and tools
- Security in the cloud environment
Materials
Task-specific material to be announced separately in Its Learning
Teaching methods
- Self-paced learning and small group work
- Learning by doing and experimenting (exercise tasks, project work, information search)
- Small group work and peer learning
- Self-study material
- Teacher guidance and examples
Exam schedules
No exam, and retake not possible after evaluation grade is published.
International connections
Self paced, FLIP classrooms and learning by doing
Completion alternatives
Self-paced learning
Student workload
Contact hours
- Course introduction: 4 hours
- Introduction to AWS academy: 4 hours
- Group Project Presentations: 2 X 4 hours
- 16 times AWS Academy self paced sessions: 16 x 2h = 32 hours
- 12 times 2h theory self paced: 12 x 2h = 24 hours
Home work:
- Working with assignments: approximately 80 hours
Total: approximately 142 hours
Content scheduling
The course content is divided into four learning objectives(CLOs):
CLO1 Analyze classic data centers and cloud data center solutions.
Introduction to Cloud Computing
1.1 Understand the limitations of traditional computing and evolution of cloud computing
1.2 Understand the concepts of Cluster, Grid and Cloud Computing, its benefits and challenges
Cloud Computing Models and Services
1.3 Explore the standard cloud model, cloud deployment and service delivery models
1.4 Understand service abstraction
Resource Virtualization and Pooling
1.5 Implement physical computing resources virtualization
1.6 Implement machine, server level and operating system virtualization
1.7 Understand resource pooling, sharing and resource provisioning
CLO2 Design a cloud data center based on specific technical requirements.
Resource Virtualization and Pooling
2.1 Implement physical computing resources virtualization
2.2 Implement machine, server level and operating system virtualization
Scaling and Capacity Planning
2.3 Understand the foundation of cloud scaling
2.4 Explore scaling strategies and implement scalable applications
2.5 Explore approaches for capacity planning
Load Balancing
2.6 Explore the goals and categories of load balancing. Explore parameters for consideration.
File System and Storage
2.7 Understand the need for high performance processing and Big Data
2.8 Explore storage deployment models and differentiate various storage types
CLO3 Discuss the need for security, reliability and legal compliance of a cloud data center.
Database Technologies
3.1 Explore database models
3.2 Implement relational and non-relational database as a service
Cloud Computing Security
3.3 Understand the threats to cloud security
3.5 Explore and develop a cloud security model
3.6 Understand Trusted Cloud Computing
Privacy and Compliance
3.7 Explore key privacy concerns in the cloud
3.8 Differentiate security vs. privacy
3.9 Develop a privacy policy
CLO4 Design strategies for the implementation of effective cloud solutions to support business requirements.
Content Delivery Model
4.1 Understand and explore content delivery network models in the cloud
Portability and Interoperability
4.2 Explore portability and interoperability scenarios
4.3 Understand machine imaging
4.4 Differentiate virtual machine and virtual appliance
Cloud Management
4.5 Understand cloud service life cycle
4.6 Understand asset management in the cloud
4.7 Explore cloud service management
4.8 Develop disaster recovery strategies
SELF PACED / FLIP CLASSROOM
In addition to the above theoretical content the students will learn and practice the cloud concepts in AWS academy. The AWS academy online course covers the following modules.
Module 1 - Global Infrastructure
Module 2 - Structures of the Cloud
Module 3 - AWS Console
Module 4 - Virtual Servers
Module 5 - Content Delivery
Module 6 - Virtual Storage
Module 7 - Security 1
Module 8 - Security 2
Module 9 - Monitoring the Cloud
Module 10: Databases
Module 11 - Load Balancers and Caching
Module 12 - Elastic Beanstalk and Cloud Formation
Module 13 - Emerging Technologies in the Cloud
Module 14 - Billing and Support
Module 15 - Other Cloud Features
Module 16 - Optimizing the Cloud with the AWS CDK
Further information
Course material and assignments in Its Learning and AWS academy.
Evaluation scale
H-5
Assessment methods and criteria
Personal assignments: 50 points
AWS Academy Course labs: 30 points
Project: 20 points
The assignments must be returned by the deadline to get the points. The assignments returned after the deadline will give you only half of the points.
The grading scale (points -> grade):
50 points -> 1
60 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5
Assessment criteria, fail (0)
Fail < 50 points
Assessment criteria, satisfactory (1-2)
50 points -> 1
60 points -> 2
Assessment criteria, good (3-4)
70 points -> 3
80 points -> 4
Assessment criteria, excellent (5)
90 points -> 5
Enrollment
17.05.2023 - 16.10.2023
Timing
09.10.2023 - 15.12.2023
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Engineering and Business
Teaching languages
- English
Seats
10 - 35
Degree programmes
- Master of Engineering, Data Engineering and AI
- Master of Business Administration, Data Engineering and AI
Teachers
- Ali Khan
Groups
-
YDATIS23
-
YDATTS23
Objective
After completing the course, the student can:
- learn about the history and background of Cloud Computing
- discover Cloud Computing including examples of real-world problems
- understand the most commonly used platforms for cloud computing such as Amazon AWS and Microsoft Azure (and possibly CSC Finland).
- understand the various Service models on Cloud as IaaS, PaaS, and SaaS
- learn the basic network security techniques in the cloud environment
Content
- Cloud computing
- Software-as-a-Service (SaaS)
- Platform-as-a-Service (PaaS)
- Infrastructure-as-a-Service (IaaS)
- Cloud computing technologies and tools
- Security in the cloud environment
Materials
Task-specific material to be announced separately in Its Learning
Teaching methods
- Self-paced learning and small group work
- Learning by doing and experimenting (exercise tasks, project work, information search)
- Small group work and peer learning
- Self-study material
- Teacher guidance and examples
Exam schedules
No exam.
International connections
FLIP classrooms and learning by doing
Completion alternatives
Self-paced learning
Student workload
135h
Content scheduling
The course content is divided into four learning objectives(CLOs):
CLO1 Analyze classic data centers and cloud data center solutions.
Introduction to Cloud Computing
1.1 Understand the limitations of traditional computing and evolution of cloud computing
1.2 Understand the concepts of Cluster, Grid and Cloud Computing, its benefits and challenges
Cloud Computing Models and Services
1.3 Explore the standard cloud model, cloud deployment and service delivery models
1.4 Understand service abstraction
Resource Virtualization and Pooling
1.5 Implement physical computing resources virtualization
1.6 Implement machine, server level and operating system virtualization
1.7 Understand resource pooling, sharing and resource provisioning
CLO2 Design a cloud data center based on specific technical requirements.
Resource Virtualization and Pooling
2.1 Implement physical computing resources virtualization
2.2 Implement machine, server level and operating system virtualization
Scaling and Capacity Planning
2.3 Understand the foundation of cloud scaling
2.4 Explore scaling strategies and implement scalable applications
2.5 Explore approaches for capacity planning
Load Balancing
2.6 Explore the goals and categories of load balancing. Explore parameters for consideration.
File System and Storage
2.7 Understand the need for high performance processing and Big Data
2.8 Explore storage deployment models and differentiate various storage types
CLO3 Discuss the need for security, reliability and legal compliance of a cloud data center.
Database Technologies
3.1 Explore database models
3.2 Implement relational and non-relational database as a service
Cloud Computing Security
3.3 Understand the threats to cloud security
3.5 Explore and develop a cloud security model
3.6 Understand Trusted Cloud Computing
Privacy and Compliance
3.7 Explore key privacy concerns in the cloud
3.8 Differentiate security vs. privacy
3.9 Develop a privacy policy
CLO4 Design strategies for the implementation of effective cloud solutions to support business requirements.
Content Delivery Model
4.1 Understand and explore content delivery network models in the cloud
Portability and Interoperability
4.2 Explore portability and interoperability scenarios
4.3 Understand machine imaging
4.4 Differentiate virtual machine and virtual appliance
Cloud Management
4.5 Understand cloud service life cycle
4.6 Understand asset management in the cloud
4.7 Explore cloud service management
4.8 Develop disaster recovery strategies
Further information
Course material and assignments in Its Learning.
Evaluation scale
H-5
Assessment methods and criteria
9 personal assignments/Labs: 90 points
Presentation demonstration of assignments: 10 points.
The assignments must be returned by the deadline to get the points. The assignments returned after the deadline will give you only half of the points.
The student must be present in the demos (on the lectures where the personal assignments are checked and presented).
The grading scale (points -> grade):
40 points -> 1
55 points -> 2
70 points -> 3
80 points -> 4
90 points -> 5