| 1.1
| Cloud Computing Everywhere 5
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| 1.2
| A Facility For Flexible Computing 6
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| 1.3
| The Start Of Cloud: The Power Wall And Multiple Cores 7
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| 1.4
| From Multiple Cores To Multiple Machines 8
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| 1.5
| From Clusters To Web Sites And Load Balancing 8
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| 1.6
| Racks Of Server Computers 9
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| 1.7
| The Economic Motivation For A Centralized Data Center 10
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| 1.8
| Origin Of The Term ``In The Cloud'' 12
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| 1.9
| Centralization Once Again 12
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| 2.1
| Introduction 15
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| 2.2
| Multi-Tenant Clouds 15
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| 2.3
| The Concept Of Elastic Computing 16
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| 2.4
| Using Virtualized Servers For Rapid Change 16
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| 2.5
| How Virtualized Servers Aid Providers 17
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| 2.6
| How Virtualized Servers Help A Customer 18
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| 2.7
| Business Models For Cloud Providers 18
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| 2.8
| Intrastructure as a Service (IaaS) 19
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| 2.9
| Platform as a Service (PaaS) 19
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| 2.10
| Software as a Service (SaaS) 20
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| 2.11
| A Special Case: Desktop as a Service (DaaS) 21
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| 2.12
| Summary 22
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| 4.1
| Introduction 37
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| 4.2
| Racks, Aisles, And Pods 37
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| 4.3
| Pod Size 38
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| 4.4
| Power And Cooling For A Pod 38
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| 4.5
| Raised Floor Pathways And Air Cooling 39
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| 4.6
| Thermal Containment And Hot/Cold Aisles 40
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| 4.7
| Exhaust Ducts (Chimneys) 40
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| 4.8
| Lights-Out Data Centers 41
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| 4.9
| A Possible Future Of Liquid Cooling 42
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| 4.10
| Network Equipment And Multi-Port Server Interfaces 43
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| 4.11
| Smart Network Interfaces And Offload 43
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| 4.12
| North-South And East-West Network Traffic 44
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| 4.13
| Network Hierarchies, Capacity, And Fat Tree Designs 45
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| 4.14
| High Capacity And Link Aggregation 46
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| 4.15
| A Leaf-Spine Network Design For East-West Traffic 47
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| 4.16
| Scaling A Leaf-Spine Architecture With A Super Spine 49
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| 4.17
| External Internet Connections 49
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| 4.18
| Storage In A Data Center 50
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| 4.19
| Unified Data Center Networks 51
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| 4.20
| Summary 51
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| 5.1
| Introduction 55
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| 5.2
| Approaches To Virtualization 55
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| 5.3
| Properties Of Full Virtualization 57
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| 5.4
| Conceptual Organization Of VM Systems 58
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| 5.5
| Efficient Execution And Processor Privilege Levels 59
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| 5.6
| Extending Privilege To A Hypervisor 60
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| 5.7
| Levels Of Trust 60
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| 5.8
| Levels Of Trust And I/O Devices 61
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| 5.9
| Virtual I/O Devices 61
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| 5.10
| Virtual Device Details 62
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| 5.11
| An Example Virtual Device 63
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| 5.12
| A VM As A Digital Object 63
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| 5.13
| VM Migration 64
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| 5.14
| Live Migration Using Three Phases 65
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| 5.15
| Running Virtual Machines In An Application 66
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| 5.16
| Facilities That Make A Hosted Hypervisor Possible 67
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| 5.17
| How A User Benefits From A Hosted Hypervisor 68
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| 5.18
| Summary 68
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| 7.1
| Introduction 87
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| 7.2
| Conflicting Goals For A Data Center Network 87
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| 7.3
| Virtual Networks, Overlays, And Underlays 88
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| 7.4
| Virtual Local Area Networks (VLANs) 89
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| 7.5
| Scaling VLANs To A Data Center With VXLAN 90
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| 7.6
| A Virtual Network Switch Within A Server 91
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| 7.7
| Network Address Translation (NAT) 91
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| 7.8
| Managing Virtualization And Mobility 92
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| 7.9
| Automated Network Configuration And Operation 93
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| 7.10
| Software Defined Networking 94
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| 7.11
| The OpenFlow Protocol 95
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| 7.12
| Programmable Networks 96
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| 7.13
| Summary 96
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| 8.1
| Introduction 99
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| 8.2
| Persistent Storage: Disks And Files 99
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| 8.3
| The Disk Interface Abstraction 100
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| 8.4
| The File Interface Abstraction 101
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| 8.5
| Local And Remote Storage 101
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| 8.6
| Two Types Of Remote Storage Systems 102
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| 8.7
| Network Attached Storage (NAS) Technology 103
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| 8.8
| Storage Area Network (SAN) Technology 104
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| 8.9
| Mapping Virtual Disks To Physical Disks 105
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| 8.10
| Hyper-Converged Infrastructure 106
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| 8.11
| A Comparison Of NAS and SAN Technology 106
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|
| 8.11.1
| NAS Advantages And Disadvantages 106
|
|
| 8.11.2
| SAN Advantages And Disadvantages 107
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| 8.12
| Object Storage 107
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| 8.13
| Summary 108
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| 9.1
| Introduction 113
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| 9.2
| Groups That Use Automation 113
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| 9.3
| The Need For Automation In A Data Center 114
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| 9.4
| An Example Deployment 115
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| 9.5
| What Can Be Automated? 116
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| 9.6
| Levels Of Automation 117
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| 9.7
| AIops: Using Machine Learning And Artificial Intelligence 119
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| 9.8
| A Plethora Of Automation Tools 119
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| 9.9
| Automation Of Manual Data Center Practices 120
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| 9.10
| Zero Touch Provisioning And Infrastructure As Code 121
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| 9.11
| Declarative, Imperative, And Intent-Based Specifications 121
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| 9.12
| The Evolution Of Automation Tools 122
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| 9.13
| Summary 123
|
| 10.1
| Introduction 127
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| 10.2
| The Legacy Of Automating Manual Procedures 127
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| 10.3
| Orchestration: Automation With A Larger Scope 128
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| 10.4
| Kubernetes: An Example Container Orchestration System 129
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| 10.5
| Limits On Kubernetes Scope 130
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| 10.6
| The Kubernetes Cluster Model 131
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| 10.7
| Kubernetes Pods 132
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| 10.8
| Pod Creation, Templates, And Binding Times 133
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| 10.9
| Init Containers 134
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| 10.10
| Kubernetes Terminology: Nodes And Control Plane 135
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| 10.11
| Control Plane Software Components 135
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| 10.12
| Communication Among Control Plane Components 136
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| 10.13
| Worker Node Software Components 137
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| 10.14
| Kubernetes Features 138
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| 10.15
| Summary 140
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| 11.1
| Introduction 145
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| 11.2
| Software In A Cloud Environment 145
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| 11.3
| Cloud-Native Vs. Conventional Software 146
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| 11.4
| Using Data Center Servers For Parallel Processing 147
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| 11.5
| Tradeoffs And Limitations Of The Parallel Approach 148
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| 11.6
| The MapReduce Programming Paradigm 149
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| 11.7
| Mathematical Description Of MapReduce 152
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| 11.8
| Splitting Input 152
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| 11.9
| Parallelism And Data Size 153
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| 11.10
| Data Access And Data Transmission 153
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| 11.11
| Apache Hadoop 154
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| 11.12
| The Two Major Parts Of Hadoop 154
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| 11.13
| Hadoop Hardware Cluster Model 155
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| 11.14
| HDFS Components: DataNodes And A NameNode 156
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| 11.15
| Block Replication And Fault Tolerance 156
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| 11.16
| HDFS And MapReduce 157
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| 11.17
| Using Hadoop With Other File Systems 158
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| 11.18
| Using Hadoop For MapReduce Computations 158
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| 11.19
| Hadoop's Support For Programming Languages 159
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| 11.20
| Summary 160
|
| 12.1
| Introduction 163
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| 12.2
| Traditional Monolithic Applications 163
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| 12.3
| Monolithic Applications In A Data Center 164
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| 12.4
| The Microservices Approach 165
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| 12.5
| The Advantages Of Microservices 165
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|
| 12.5.1
| Advantages For Software Development 166
|
|
| 12.5.2
| Advantages For Operations And Maintenance 166
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| 12.6
| The Potential Disadvantages Of Microservices 167
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| 12.7
| Microservices Granularity 168
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| 12.8
| Communication Protocols Used For Microservices 171
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| 12.9
| Communication Among Microservices 174
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| 12.10
| Using A Service Mesh Proxy 175
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| 12.11
| The Potential For Deadlock 176
|
| 12.12
| Microservices Technologies 178
|
| 12.13
| Summary 178
|
| 13.1
| Introduction 181
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| 13.2
| Traditional Distributed Application Management 181
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| 13.3
| Periodic Monitoring 182
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| 13.4
| Managing Cloud-Native Applications 183
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| 13.5
| Control Loop Concept 184
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| 13.6
| Control Loop Delay, Hysteresis, And Instability 185
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| 13.7
| The Kubernetes Controller Paradigm And Control Loop 186
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| 13.8
| An Event-Driven Implementation Of A Control Loop 187
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| 13.9
| Components Of A Kubernetes Controller 188
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| 13.10
| Custom Resources And Custom Controllers 189
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| 13.11
| Kubernetes Custom Resource Definition (CRD) 190
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| 13.12
| Service Mesh Management Tools 191
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| 13.13
| Reactive Or Dynamic Planning 191
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| 13.14
| A Goal: The Operator Pattern 192
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| 13.15
| Summary 192
|
| 14.1
| Introduction 195
|
| 14.2
| Traditional Client-Server Architecture 195
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| 14.3
| Scaling A Traditional Server To Handle Multiple Clients 196
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| 14.4
| Scaling A Server In A Cloud Environment 197
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| 14.5
| The Economics Of Servers In The Cloud 197
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| 14.6
| The Serverless Computing Approach 198
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| 14.7
| Stateless Servers And Containers 199
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| 14.8
| The Architecture Of A Serverless Infrastructure 201
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| 14.9
| An Example Of Serverless Processing 201
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| 14.10
| Potential Disadvantages Of Serverless Computing 202
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| 14.11
| Summary 204
|
| 15.1
| Introduction 207
|
| 15.2
| Software Creation And Deployment 207
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| 15.3
| The Realistic Software Development Cycle 208
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| 15.4
| Large Software Projects And Teams 208
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| 15.5
| Disadvantages Of Using Multiple Teams 209
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| 15.6
| The DevOps Approach 210
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| 15.7
| Continuous Integration (CI): A Short Change Cycle 211
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| 15.8
| Continuous Delivery (CD): Deploying Versions Rapidly 212
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| 15.9
| Cautious Deployment: Sandbox, Canary, And Blue/Green 212
|
| 15.10
| Difficult Aspects Of The DevOps Approach 213
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| 15.11
| Summary 214
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| 16.1
| Introduction 219
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| 16.2
| The Latency Disadvantage Of Cloud 219
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| 16.3
| Situations Where Latency Matters 220
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| 16.4
| Industries That Need Low Latency 220
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| 16.5
| Moving Computing To The Edge 221
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| 16.6
| Extending Edge Computing To A Fog Hierarchy 222
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| 16.7
| Caching At Multiple Levels Of A Hierarchy 223
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| 16.8
| An Automotive Example 224
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| 16.9
| Edge Computing And IIoT 225
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| 16.10
| Communication For IIoT 227
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| 16.11
| Decentralization Once Again 228
|
| 16.12
| Summary 229
|
| 17.1
| Introduction 233
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| 17.2
| Cloud-Specific Security Problems 233
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| 17.3
| Security In A Traditional Infrastructure 235
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| 17.4
| Why Traditional Methods Do Not Suffice For The Cloud 236
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| 17.5
| The Zero Trust Security Model 237
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| 17.6
| Identity Management 238
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| 17.7
| Privileged Access Management (PAM) 238
|
| 17.8
| AI Technologies And Their Effect On Security 239
|
| 17.9
| Protecting Remote Access 240
|
| 17.10
| Privacy In A Cloud Environment 241
|
| 17.11
| Back Doors, Side Channels, And Other Concerns 242
|
| 17.12
| Cloud Providers As Partners For Security And Privacy 242
|
| 17.13
| Summary 243
|
| 18.1
| Introduction 247
|
| 18.2
| Sources Of Complexity In Cloud Systems 247
|
| 18.3
| Inherent Complexity In Large Distributed Systems 248
|
| 18.4
| Designing A Flawless Distributed System 249
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| 18.5
| System Modeling 249
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| 18.6
| Mathematical Models 250
|
| 18.7
| An Example Graph Model To Help Avoid Deadlock 251
|
| 18.8
| A Graph Model For A Startup Sequence 252
|
| 18.9
| Modeling Using Mathematics 254
|
| 18.10
| An Example TLA\v'-.25m'\h'-4u'\s-1+\s+1\v'.25m'\h'4u' Specification 255
|
| 18.11
| System State And State Changes 256
|
| 18.12
| The Form Of A TLA\v'-.25m'\h'-4u'\s-1+\s+1\v'.25m'\h'4u' Specification 257
|
| 18.13
| Symbols In A TLA\v'-.25m'\h'-4u'\s-1+\s+1\v'.25m'\h'4u' Specification 259
|
| 18.14
| State Transitions For The Example 261
|
| 18.15
| Conclusions About Temporal Logic Models 263
|
| 18.16
| Summary 263
|