1st Edition

The Cloud Computing Book The Future of Computing Explained

By Douglas Comer Copyright 2021
    288 Pages 82 B/W Illustrations
    by Chapman & Hall

    288 Pages 82 B/W Illustrations
    by Chapman & Hall

    288 Pages 82 B/W Illustrations
    by Chapman & Hall

    This latest textbook from bestselling author, Douglas E. Comer, is a class-tested book providing a comprehensive introduction to cloud computing. Focusing on concepts and principles, rather than commercial offerings by cloud providers and vendors, The Cloud Computing Book: The Future of Computing Explained gives readers a complete picture of the advantages and growth of cloud computing, cloud infrastructure, virtualization, automation and orchestration, and cloud-native software design.

    The book explains real and virtual data center facilities, including computation (e.g., servers, hypervisors, Virtual Machines, and containers), networks (e.g., leaf-spine architecture, VLANs, and VxLAN), and storage mechanisms (e.g., SAN, NAS, and object storage). Chapters on automation and orchestration cover the conceptual organization of systems that automate software deployment and scaling. Chapters on cloud-native software cover parallelism, microservices, MapReduce, controller-based designs, and serverless computing. Although it focuses on concepts and principles, the book uses popular technologies in examples, including Docker containers and Kubernetes. Final chapters explain security in a cloud environment and the use of models to help control the complexity involved in designing software for the cloud.

    The text is suitable for a one-semester course for software engineers who want to understand cloud, and for IT managers moving an organization’s computing to the cloud.


    PART I The Era Of Cloud Computing 

    The Motivations For Cloud 
    1.1 Cloud Computing Everywhere 
    1.2 A Facility For Flexible Computing 
    1.3 The Start Of Cloud: The Power Wall And Multiple Cores 
    1.4 From Multiple Cores To Multiple Machines 
    1.5 From Clusters To Web Sites And Load Balancing 
    1.6 Racks Of Server Computers 
    1.7 The Economic Motivation For A Centralized Data Center 
    1.8 Origin Of The Term “In The Cloud” 
    1.9 Centralization Once Again 

    Elastic Computing And Its Advantages 
    2.1 Introduction 
    2.2 Multi-Tenant Clouds 
    2.3 The Concept Of Elastic Computing 
    2.4 Using Virtualized Servers For Rapid Change 
    2.5 How Virtualized Servers Aid Providers 
    2.6 How Virtualized Servers Help A Customer 
    2.7 Business Models For Cloud Providers 
    2.8 Intrastructure as a Service (IaaS) 
    2.9 Platform as a Service (PaaS) 
    2.10 Software as a Service (SaaS) 
    2.11 A Special Case: Desktop as a Service (DaaS) 
    2.12 Summary 

    Type Of Clouds And Cloud Providers 
    3.1 Introduction 
    3.2 Private And Public Clouds 
    3.3 Private Cloud 
    3.4 Public Cloud 
    3.5 The Advantages Of Public Cloud 
    3.6 Provider Lock-In 
    3.7 The Advantages Of Private Cloud 
    3.8 Hybrid Cloud 
    3.9 Multi-Cloud 
    3.10 Hyperscalers 
    3.11 Summary 

    PART II Cloud Infrastructure And Virtualization 

    Data Center Infrastructure And Equipment 
    4.1 Introduction 
    4.2 Racks, Aisles, And Pods 
    4.3 Pod Size 
    4.4 Power And Cooling For A Pod 
    4.5 Raised Floor Pathways And Air Cooling 
    4.6 Thermal Containment And Hot/Cold Aisles 
    4.7 Exhaust Ducts (Chimneys) 
    4.8 Lights-Out Data Centers 
    4.9 A Possible Future Of Liquid Cooling 
    4.10 Network Equipment And Multi-Port Server Interfaces 
    4.11 Smart Network Interfaces And Offload 
    4.12 North-South And East-West Network Traffic 
    4.13 Network Hierarchies, Capacity, And Fat Tree Designs 
    4.14 High Capacity And Link Aggregation 
    4.15 A Leaf-Spine Network Design For East-West Traffic 
    4.16 Scaling A Leaf-Spine Architecture With A Super Spine 
    4.17 External Internet Connections 
    4.18 Storage In A Data Center 
    4.19 Unified Data Center Networks 
    4.20 Summary 

    Virtual Machines 
    5.1 Introduction 
    5.2 Approaches To Virtualization 
    5.3 Properties Of Full Virtualization 
    5.4 Conceptual Organization Of VM Systems 
    5.5 Efficient Execution And Processor Privilege Levels 
    5.6 Extending Privilege To A Hypervisor 
    5.7 Levels Of Trust 
    5.8 Levels Of Trust And I/O Devices 
    5.9 Virtual I/O Devices 
    5.10 Virtual Device Details 
    5.11 An Example Virtual Device 
    5.12 A VM As A Digital Object 
    5.13 VM Migration 
    5.14 Live Migration Using Three Phase
    5.15 Running Virtual Machines In An Application 
    5.16 Facilities That Make A Hosted Hypervisor Possible 
    5.17 How A User Benefits From A Hosted Hypervisor 
    5.18 Summary 

    6.1 Introduction 
    6.2 The Advantages And Disadvantages Of VMs 
    6.3 Traditional Apps And Elasticity On Demand 
    6.4 Isolation Facilities In An Operating System 
    6.5 Linux Namespaces Used For Isolation 
    6.6 The Container Approach For Isolated Apps 
    6.7 Docker Containers
    6.8 Docker Terminology And Development Tools 
    6.9 Docker Software Components 
    6.10 Base Operating System And Files 
    6.11 Items In A Dockerfile 
    6.12 An Example Dockerfile 
    6.13 Summary 

    Virtual Networks 
    7.1 Introduction 
    7.2 Conflicting Goals For A Data Center Network 
    7.3 Virtual Networks, Overlays, And Underlays 
    7.4 Virtual Local Area Networks (VLANs) 
    7.5 Scaling VLANs To A Data Center With VXLAN 
    7.6 A Virtual Network Switch Within A Server 
    7.7 Network Address Translation (NAT) 
    7.8 Managing Virtualization And Mobility 
    7.9 Automated Network Configuration And Operation 
    7.10 Software Defined Networking 
    7.11 The OpenFlow Protocol 
    7.12 Programmable Networks 
    7.13 Summary 

    Virtual Storage 
    8.1 Introduction 
    8.2 Persistent Storage: Disks And Files 
    8.3 The Disk Interface Abstraction 
    8.4 The File Interface Abstraction 
    8.5 Local And Remote Storage 1
    8.6 Two Types Of Remote Storage Systems 
    8.7 Network Attached Storage (NAS) Technology 
    8.8 Storage Area Network (SAN) Technology 
    8.9 Mapping Virtual Disks To Physical Disks 
    8.10 Hyper-Converged Infrastructure 
    8.11 A Comparison Of NAS and SAN Technology 
    8.12 Object Storage 
    8.13 Summary 

    PART III Automation And Orchestration

    9.1 Introduction 
    9.2 Groups That Use Automation 
    9.3 The Need For Automation In A Data Center 
    9.4 An Example Deployment 
    9.5 What Can Be Automated? 
    9.6 Levels Of Automation 
    9.7 AIops: Using Machine Learning And Artificial Intelligence 
    9.8 A Plethora Of Automation Tools 
    9.9 Automation Of Manual Data Center Practices 
    9.10 Zero Touch Provisioning And Infrastructure As Code 
    9.11 Declarative, Imperative, And Intent-Based Specifications 
    9.12 The Evolution Of Automation Tools 
    9.13 Summary 

    Orchestration: Automated Replication And Parallelism 
    10.1 Introduction 
    10.2 The Legacy Of Automating Manual Procedures 
    10.3 Orchestration: Automation With A Larger Scope 
    10.4 Kubernetes: An Example Container Orchestration System 
    10.5 Limits On Kubernetes Scope 
    10.6 The Kubernetes Cluster Model 
    10.7 Kubernetes Pods 
    10.8 Pod Creation, Templates, And Binding Times 
    10.9 Init Containers 
    10.10 Kubernetes Terminology: Nodes And Control Plane 
    10.11 Control Plane Software Components 
    10.12 Communication Among Control Plane Components 
    10.13 Worker Node Software Components 
    10.14 Kubernetes Features 1
    10.15 Summary

    PART IV Cloud Programming Paradigms

    The MapReduce Paradigm 
    11.1 Introduction 
    11.2 Software In A Cloud Environment 
    11.3 Cloud-Native Vs. Conventional Software 
    11.4 Using Data Center Servers For Parallel Processing 
    11.5 Tradeoffs And Limitations Of The Parallel Approach 
    11.6 The MapReduce Programming Paradigm 
    11.7 Mathematical Description Of MapReduce 
    11.8 Splitting Input 
    11.9 Parallelism And Data Size 
    11.10 Data Access and Data Transmission 
    11.11 Apache Hadoop 
    11.12 The Two Major Parts Of Hadoop 
    11.13 Hadoop Hardware Cluster Model 
    11.14 HDFS Components: DataNodes And A NameNode 
    11.15 Block Replication And Fault Tolerance 
    11.16 HDFS And MapReduce 
    11.17 Using Hadoop With Other File Systems 
    11.18 Using Hadoop For MapReduce Computations 
    11.19 Hadoop’s Support For Programming Languages 
    11.20 Summary 

    12.1 Introduction 
    12.2 Traditional Monolithic Applications 
    12.3 Monolithic Applications In A Data Center 
    12.4 The Microservices Approach 
    12.5 The Advantages Of Microservices 
    12.6 The Potential Disadvantages of Microservices 
    12.7 Microservices Granularity 
    12.8 Communication Protocols Used For Microservices 
    12.9 Communication Among Microservices 
    12.10 Using A Service Mesh Proxy 
    12.11 The Potential For Deadlock 
    12.12 Microservices Technologies 
    12.13 Summary 

    Controller-Based Management Software
    13.1 Introduction 
    13.2 Traditional Distributed Application Management 
    13.3 Periodic Monitoring 
    13.4 Managing Cloud-Native Applications 
    13.5 Control Loop Concept 
    13.6 Control Loop Delay, Hysteresis, And Instability 
    13.7 The Kubernetes Controller Paradigm And Control Loop 
    13.8 An Event-Driven Implementation Of A Control Loop 
    13.9 Components Of A Kubernetes Controller 
    13.10 Custom Resources And Custom Controllers 
    13.11 Kubernetes Custom Resource Definition (CRD) 
    13.12 Service Mesh Management Tools 
    13.13 Reactive Or Dynamic Planning 
    13.14 A Goal: The Operator Pattern 
    13.15 Summary 

    Serverless Computing And Event Processing 
    14.1 Introduction 
    14.2 Traditional Client-Server Architecture 1
    14.3 Scaling A Traditional Server To Handle Multiple Clients 
    14.4 Scaling A Server In A Cloud Environment 
    14.5 The Economics Of Servers In The Cloud 
    14.6 The Serverless Computing Approach 
    14.7 Stateless Servers And Containers 
    14.8 The Architecture Of A Serverless Infrastructure 
    14.9 An Example Of Serverless Processing 
    14.10 Potential Disadvantages Of Serverless Computing 
    14.11 Summary 

    15.1 Introduction 
    15.2 Software Creation And Deployment
    15.3 The Realistic Software Development Cycle 
    15.4 Large Software Projects And Teams 
    15.5 Disadvantages Of Using Multiple Teams 
    15.6 The DevOps Approach 
    15.7 Continuous Integration (CI): A Short Change Cycle 
    15.8 Continuous Delivery (CD): Deploying Versions Rapidly 
    15.9 Cautious Deployment: Sandbox, Canary, And Blue/Green 
    15.10 Difficult Aspects Of The DevOps Approach 
    15.11 Summary 

    PART V Other Aspects Of Cloud 

    Edge Computing And IIoT 
    16.1 Introduction 
    16.2 The Latency Disadvantage Of Cloud 
    16.3 Situations Where Latency Matters 
    16.4 Industries That Need Low Latency 
    16.5 Moving Computing To The Edge 
    16.6 Extending Edge Computing To A Fog Hierarchy 
    16.7 Caching At Multiple Levels Of A Hierarchy 
    16.8 An Automotive Example 
    16.9 Edge Computing And IIoT 
    16.10 Communication For IIoT 
    16.11 Decentralization Once Again 
    16.12 Summary 

    Cloud Security And Privacy
    17.1 Introduction 
    17.2 Cloud-Specific Security Problems 
    17.3 Security In A Traditional Infrastructure 
    17.4 Why Traditional Methods Do Not Suffice For The Cloud 
    17.5 The Zero Trust Security Model 
    17.6 Identity Management 
    17.7 Privileged Access Management (PAM) 
    17.8 AI Technologies And Their Effect On Security

    17.9 Protecting Remote Access 
    17.10 Privacy In A Cloud Environment 
    17.11 Back Doors, Side Channels, And Other Concerns 
    17.12 Cloud Providers As Partners For Security And Privacy 
    17.13 Summary 

    Controlling The Complexity Of Cloud-Native Systems 
    18.1 Introduction 
    18.2 Sources Of Complexity In Cloud Systems 
    18.3 Inherent Complexity In Large Distributed Systems 
    18.4 Designing A Flawless Distributed System 
    18.5 System Modeling 
    18.6 Mathematical Models 
    18.7 An Example Graph Model To Help Avoid Deadlock 
    18.8 A Graph Model For A Startup Sequence 
    18.9 Modeling Using Mathematics 
    18.10 An Example TLA+ Specification 
    18.11 System State And State Changes 
    18.12 The Form Of A TLA+ Specification 
    18.13 Symbols In A TLA+ Specification 
    18.14 State Transitions For The Example 
    18.15 Conclusions About Temporal Logic Models 
    18.16 Summary 



    Dr. Douglas Comer is a Distinguished Professor at Purdue University, an industry consultant, and internationally-acclaimed author. He served as the inaugural VP of Research at Cisco Systems, and maintains ties with industry. His books are used in industry and academia around the world. Comer is a Fellow of the ACM, a member of the Internet Hall of Fame, and the recipient of numerous teaching awards. His ability to make complex topics understandable gives his books broad appeal for a wide variety of audiences.