Module Details

Module Code: COMP8062
Title: Cloud Automation&Orchestration
Long Title: Cloud Automation & Orchestration
NFQ Level: Advanced
Valid From: Semester 1 - 2020/21 ( September 2020 )
Duration: 1 Semester
Credits: 5
Field of Study: 4811 - Computer Science
Module Delivered in: 2 programme(s)
Module Description: Cloud automation enables the efficient automation, provisioning and management of cloud infrastructures and their associated workloads. In this module students will learn how scripting/programming languages and cloud automation tools can be leveraged to replace manual work with automated routines within a cloud environment. In addition, students will learn about cloud orchestration tools and techniques to effectively manage and automate tasks across an enterprise by scheduling and integrating automated tasks, facilitated by cloud automation tools, between different systems.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Critically assess the purpose, benefits and approaches of automation and orchestration as part of an overall infrastructure management solution.
LO2 Design and develop programs using Python as a programming language to automate and perform common tasks within a cloud computing infrastructure.
LO3 Identify the category of automation tool and select the optimal tool to automate a given task within a cloud infrastructure.
LO4 Design a solution to automate the development and operations for an organisation.
LO5 Orchestrate the automated provisioning and management of virtual infrastructure to provide services in a single or multi-cloud environment.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Introduction to Automation & Orchestration
History of automation in Information Technology - scripting languages, provisioning, management tools and the role of Infrastructure-as-Code (IaC). Cloud Automation - purpose and benefits. Suitability of automation to Cloud environments. Cloud Orchestration as a process control for managing automated activities across the Cloud.
Using Python for common IaaS tasks and cloud service deployment
Understanding how Python handles data: numbers, strings, lists, dictionaries and sets. Processing Python's data structures: control structures, loops and comprehensions. Structuring Python code: functions, modules, packages and files. Engineering Python code: objects, classes, and OOP (with Python). Scripting your cloud architecture using Python cloud libraries to deploy, manage and monitor cloud services (IaaS and PaaS) using Python libraries such as boto and Apache LibCloud.
Categories and characteristics of Cloud Automation tools
Main categories of Cloud Automation tools - Configuration Management, Configuration Provisioning, Continuous Integration and Orchestration and the most widely used tools in each category. The typical characteristics/capabilities of tools within a given category. The major differences between categories and the overlap between them. Identifying the category of tool and individual tool within a category to use based on requirements.
Implementation of Cloud Automation
Viewing and manipulating Infrastructure as Code (IaC) using tools such as fabric, salt, chef, puppet, ansible, vagrant, docker and kubernettes. Demonstrate automated configuration, deployment and management of infrastructure (including virtual machines, containers, network) within the Private Cloud (VMware vRealize) and Public Cloud (AWS OpWorks).
Orchestration of Single and Multi-Cloud Environments
Public and Private Cloud native orchestration tools to deploy and manage virtual infrastructure (AWS CloudFormation, Google Cloud – Cloud Composer, OpenStack HEAT). The integration of third-party Automation and Orchestration tools to manage the life-cycle of virtual infrastructure in single and multi-Cloud environments.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Project % of Total Mark 50
Timing Week 9 Learning Outcomes 1,2,3,4
Assessment Description
For a given cloud infrastructure, students will identify tasks that can be automated and then design and justify a solution.
Assessment Type Practical/Skills Evaluation % of Total Mark 50
Timing Week 13 Learning Outcomes 3,4,5
Assessment Description
The student, for example, will implement a set of automation tools to manage, coordinate and provision all components of a cloud platform that will run in a single or multi-cloud environment.
No End of Module Formal Examination
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lecture delivering theory underpinning learning outcomes. Every Week 2.00 2
Lab Contact Lab to support learning outcomes Every Week 2.00 2
Directed Learning Non Contact Independent Study Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lecture delivering theory underpinning learning outcomes. Every Week 2.00 2
Lab Contact Lab to support learning outcomes Every Week 2.00 2
Directed Learning Non Contact Independent study Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
 
Module Resources
Recommended Book Resources
  • Paul Barry. (2010), Head First Python, O'Reilly Media, [ISBN: 9781449382674].
  • Aditya Patawari, Vikas Aggarwal (Author). (2018), Ansible 2 Cloud Automation Cookbook: Write Ansible playbooks for AWS, Google Cloud, Microsoft Azure, and OpenStack, Packt Publishing, [ISBN: 9781788295826].
Supplementary Book Resources
  • John Arundel. (2017), Puppet 5 Beginner's Guide, 3rd Edition. Packt Publishing, [ISBN: 9781788472906].
  • Mitch Garnaat, O'Reilly. (2011), Python & AWS Cookbook, O'Reilly Media, [ISBN: 9781449305444].
  • Adnan Ahmed Siddiqui. (2015), OpenStack Orchestration, Packt Publishing, [ISBN: 9781783551651].
  • Kief Morris. (2016), Infrastructure as Code: Managing Servers in the Cloud, 1st Edition. O'Reilly Media, [ISBN: 9781491924358].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_KCLCO_8 Higher Diploma in Science in Cloud Computing 2 Mandatory
CR_KCLDC_9 Master of Science in Cloud Computing 1 Mandatory