The book leverages open-source technologies, Python frameworks, and standard cloud platforms to ensure that readers learn skills that are highly transferable across any cloud vendor. By writing code, deploying microservices, and setting up distributed clusters, readers develop a deeply intuitive understanding of how large-scale cloud systems operate. 🗂️ Detailed Structural Breakdown of the Book
The book is methodically organized to build a robust knowledge base. It begins with foundational concepts, offering a rigorous introduction to cloud computing architecture, virtualization technologies, and service-oriented architectures (SOA). Readers are introduced to the critical mechanisms that power the cloud, including:
Here’s a structure for a inspired by the book’s methodology:
Provides practical scenarios, including image processing and social network analytics. Why Choose "A Hands-On Approach" (Key Features) It begins with foundational concepts, offering a rigorous
The authors utilize an "immersive hands-on approach" that prioritizes developing working code for real-world scenarios over abstract theory. It is specifically tailored for senior undergraduate and graduate students in , as well as IT professionals seeking to modernize their skill sets. Book Structure and Key Topics
The foundation of cloud, covering server virtualization, storage virtualization, and network virtualization. 2. Cloud Platforms and Services
Execution environments where underlying infrastructure is managed (e.g., Heroku, AWS Elastic Beanstalk). It is specifically tailored for senior undergraduate and
This is the heart of the "hands-on" approach, focusing on the actual programming and deployment of scalable applications.
It covers the entire spectrum of cloud computing, from infrastructure-as-a-service (IaaS) to platform-as-a-service (PaaS) and software-as-a-service (SaaS).
This segment transitions from theoretical infrastructure to software architecture. covering server virtualization
Ideal for computer science and engineering students studying cloud computing.
: Handling massive traffic in real-time.
: Integrating traditional Relational Database Management Systems (RDBMS) alongside scalable NoSQL databases. Part III: Advanced Topics & Case Studies
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