Post

Cloud Operations and Management

Cloud Operations and Management

🎯 Module Overview

This module enabled me to:

  • Understand the architecture and framework for cloud computing and the fundamentals of cloud services.
  • Gain knowledge of various cloud computing technologies and practical sustainable implementation experience.
  • Learn about several cloud services, such as hybrid, edge, and fog computing.
  • Reflect on personal improvement and evaluate the ethical, social, and professional impact of Cloud principles and techniques.
  • Recognise current and future issues, restrictions, and prospects in the domain.
  • Develop competence in crafting persuasive arguments for specific actions or outcomes tailored to diverse audiences.
  • Understand how Cloud principles and techniques impact equality, diversity, and inclusion in the workplace.

📚 Table of Contents


Unit 1: Introduction to Cloud Fundamentals and Services

Key Concepts:

  • Cloud computing definition, history, and characteristics
  • Cloud service models (IaaS, PaaS, SaaS)
  • Benefits of cloud adoption (scalability, cost efficiency)
  • Challenges of cloud adoption (security risks, vendor lock-in)

Reflections:

This week introduced the fundamentals of cloud computing, including its definition, history, and key characteristics. I learned about the three main service models— IaaS, PaaS, and SaaS—along with real-world examples from AWS, Azure, and Google Cloud. Understanding these concepts has given me a strong foundation for the rest of the module.

Related Work: 📄 Forum post - Major CSP comparison


Unit 2: Understanding Cloud Architecture and Implementing Different Frameworks

Key Concepts:

  • Cloud architecture and frameworks
  • TOGAF, Software Development Life Cycle (SDLC)
  • Infrastructure as Code (IaC)
  • Scalability and consistency in cloud environments

Reflections:

This week focused on cloud architecture and the frameworks that support design and deployment. The introduction to TOGAF, SDLC, and IaC was insightful, especially in understanding how automation supports scalable cloud solutions.

Related Work: 📄 Forum post - ROCCA and ToGAF implementation in Government Agencies


Unit 3: Cloud Design Tools

Key Concepts:

  • Artificial Intelligence (AI) in cloud computing
  • AI for automation, optimisation, and performance
  • Machine learning and data analytics
  • Cloud management, security, and monitoring

Reflections:

This week explored AI’s role in cloud computing, particularly how it improves automation and optimisation. Use cases illustrated how ML and analytics strengthen cloud operations.

Related Work: 📄 Forum post - Cloud Design Tool


Unit 4: Cloud Native Technology Part 1


Unit 5: Cloud Native Technology Part 2


Unit 6: Hybrid Cloud Solutions (Hybrid, Fog, Edge Computing)


Unit 7: Cloud Security and Compliance


Unit 8: Disaster Recovery and Business Continuity


Unit 9: Cloud Migration and Integration Strategies


Unit 10: Advanced Cloud Technologies (Serverless Computing)


Unit 11: AI and Cloud Computing



This post is licensed under CC BY 4.0 by the author.