Skip to main content

Cloud ServicesLaajuus (5 cr)

Code: TT00CN73

Credits

5 op

Objective

After completing the course, the student can:
- Describe what Cloud Services are, how they affect business and which new opportunities it may enable.
- Describe use cases and benefits of cloud services,
- Describe SAAS, PAAS, IAAS.
- Develop a solution that utilizes cloud services.

Content

Introduction to cloud services
Software as a service (SAAS)
Platform as a service (PAAS)
Infrastructure as a service (IAAS)
Virtual machines and containers
Security of cloud services
Project work

Enrollment

04.12.2024 - 13.01.2025

Timing

13.01.2025 - 30.04.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Engineering and Business

Campus

Kupittaa Campus

Teaching languages
  • English
Seats

0 - 40

Degree programmes
  • Degree Programme in Information and Communication Technology
  • Degree Programme in Business Information Technology
Teachers
  • Ali Khan
Groups
  • VAVA2425

Objective

After completing the course, the student can:
- Describe what Cloud Services are, how they affect business and which new opportunities it may enable.
- Describe use cases and benefits of cloud services,
- Describe SAAS, PAAS, IAAS.
- Develop a solution that utilizes cloud services.

Content

Introduction to cloud services
Software as a service (SAAS)
Platform as a service (PAAS)
Infrastructure as a service (IAAS)
Virtual machines and containers
Security of cloud services
Project work

Materials

Task-specific material to be announced separately in Its Learning and in AWS academy.

Teaching methods

- Weekly face-to-face meetings with lecture teaching 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

FLIP classrooms and learning by doing

Completion alternatives

Not possible

Student workload

Contact hours
- Course introduction: 3 hours
- 12 times 2h theory: 12 x 2h = 24 hours
- 12 times 1h AWS Support: 12 x 1h = 12 hours
- 16 times AWS Academy self paced sessions: 16 x 1h = 16 hours

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 135 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.

Introduction
Module 1 - Cloud Concepts Overview
Module 2 - Cloud Economics and Billing
Module 3 - AWS Global Infrastructure Overview
Module 4 - AWS Cloud Security
Module 5 - Networking and Content Delivery
Module 6 - Compute
Module 7 - Storage
Module 8 - Databases
Module 9 - Cloud Architecture
Module 10 - Auto Scaling and Monitoring

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.
Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

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

24.07.2024 - 09.09.2024

Timing

02.09.2024 - 15.12.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Engineering and Business

Campus

Kupittaa Campus

Teaching languages
  • English
Seats

10 - 40

Degree programmes
  • Degree Programme in Information and Communication Technology
  • Degree Programme in Business Information Technology
Teachers
  • Ali Khan
Teacher in charge

Ali Khan

Groups
  • PTIETS22deai
    PTIETS22 Data Engineering and Artificial Intelligence
  • PTIVIS22I
    Data Engineering and AI

Objective

After completing the course, the student can:
- Describe what Cloud Services are, how they affect business and which new opportunities it may enable.
- Describe use cases and benefits of cloud services,
- Describe SAAS, PAAS, IAAS.
- Develop a solution that utilizes cloud services.

Content

Introduction to cloud services
Software as a service (SAAS)
Platform as a service (PAAS)
Infrastructure as a service (IAAS)
Virtual machines and containers
Security of cloud services
Project work

Materials

Task-specific material to be announced separately in Its Learning and in AWS academy.

Teaching methods

- Weekly face-to-face meetings with lecture teaching 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

FLIP classrooms and learning by doing

Completion alternatives

Not possible

Student workload

Contact hours
- Course introduction: 3 hours
- 12 times 3h theory and AWS support: 12 x 3h = 36 hours
- 16 times AWS Academy self paced sessions: 16 x 1h = 16 hours

Home work:
- Working with assignments: approximately 80 hours

Total: approximately 135 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.
Demonstrations of exercises during the contact session is mandatory without demonstration you will lose 50% of your marks.

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