This book explains why applications running on cloud might not deliver the same service reliability, availability, latency and overall quality to end users as they do when the applications are running on traditional (non-virtualized, non-cloud) configurations, and explains what can be done to mitigate that risk.

Figures xv Tables and Equations xxi 1 INTRODUCTION 1 1.1 Approach 1 1.2 Target Audience 3 1.3 Organization 3 I CONTEXT 7 2 APPLICATION SERVICE QUALITY 9 2.1 Simple Application Model 9 2.2 Service Boundaries 11 2.3 Key Quality and Performance Indicators 12 2.4 Key Application Characteristics 15 2.5 Application Service Quality Metrics 17 2.6 Technical Service versus Support Service 27 2.7 Security Considerations 28 3 CLOUD MODEL 29 3.1 Roles in Cloud Computing 30 3.2 Cloud Service Models 30 3.3 Cloud Essential Characteristics 31 3.4 Simplifi ed Cloud Architecture 33 3.5 Elasticity Measurements 36 3.6 Regions and Zones 44 3.7 Cloud Awareness 45 4 VIRTUALIZED INFRASTRUCTURE IMPAIRMENTS 49 4.1 Service Latency, Virtualization, and the Cloud 50 4.2 VM Failure 54 4.3 Nondelivery of Configured VM Capacity 54 4.4 Delivery of Degraded VM Capacity 57 4.5 Tail Latency 59 4.6 Clock Event Jitter 60 4.7 Clock Drift 61 4.8 Failed or Slow Allocation and Startup of VM Instance 62 4.9 Outlook for Virtualized Infrastructure Impairments 63 II ANALYSIS 65 5 APPLICATION REDUNDANCY AND CLOUD COMPUTING 67 5.1 Failures, Availability, and Simplex Architectures 68 5.2 Improving Software Repair Times via Virtualization 70 5.3 Improving Infrastructure Repair Times via Virtualization 72 5.4 Redundancy and Recoverability 75 5.5 Sequential Redundancy and Concurrent Redundancy 80 5.6 Application Service Impact of Virtualization Impairments 84 5.7 Data Redundancy 90 5.8 Discussion 92 6 LOAD DISTRIBUTION AND BALANCING 97 6.1 Load Distribution Mechanisms 97 6.2 Load Distribution Strategies 99 6.3 Proxy Load Balancers 99 6.4 Nonproxy Load Distribution 101 6.5 Hierarchy of Load Distribution 102 6.6 Cloud-Based Load Balancing Challenges 103 6.7 The Role of Load Balancing in Support of Redundancy 103 6.8 Load Balancing and Availability Zones 104 6.9 Workload Service Measurements 104 6.10 Operational Considerations 105 6.11 Load Balancing and Application Service Quality 107 7 FAILURE CONTAINMENT 111 7.1 Failure Containment 111 7.2 Points of Failure 116 7.3 Extreme Solution Coresidency 122 7.4 Multitenancy and Solution Containers 124 8 CAPACITY MANAGEMENT 127 8.1 Workload Variations 128 8.2 Traditional Capacity Management 129 8.3 Traditional Overload Control 129 8.4 Capacity Management and Virtualization 131 8.5 Capacity Management in Cloud 133 8.6 Storage Elasticity Considerations 135 8.7 Elasticity and Overload 136 8.8 Operational Considerations 137 8.9 Workload Whipsaw 138 8.10 General Elasticity Risks 140 8.11 Elasticity Failure Scenarios 141 9 RELEASE MANAGEMENT 145 9.1 Terminology 145 9.2 Traditional Software Upgrade Strategies 146 9.3 Cloud-Enabled Software Upgrade Strategies 153 9.4 Data Management 158 9.5 Role of Service Orchestration in Software Upgrade 159 9.6 Conclusion 161 10 END-TO-END CONSIDERATIONS 163 10.1 End-to-End Service Context 163 10.2 Three-Layer End-to-End Service Model 169 10.3 Distributed and Centralized Cloud Data Centers 177 10.4 Multitiered Solution Architectures 183 10.5 Disaster Recovery and Geographic Redundancy 184 III RECOMMENDATIONS 191 11 ACCOUNTABILITIES FOR SERVICE QUALITY 193 11.1 Traditional Accountability 193 11.2 The Cloud Service Delivery Path 194 11.3 Cloud Accountability 197 11.4 Accountability Case Studies 200 11.5 Service Quality Gap Model 205 11.6 Service Level Agreements 210 12 SERVICE AVAILABILITY MEASUREMENT 213 12.1 Parsimonious Service Measurements 214 12.2 Traditional Service Availability Measurement 215 12.3 Evolving Service Availability Measurements 217 12.4 Evolving Hardware Reliability Measurement 226 12.5 Evolving Elasticity Service Availability Measurements 228 12.6 Evolving Release Management Service Availability Measurement 229 12.7 Service Measurement Outlook 231 13 APPLICATION SERVICE QUALITY REQUIREMENTS 233 13.1 Service Availability Requirements 234 13.2 Service Latency Requirements 237 13.3 Service Reliability Requirements 237 13.4 Service Accessibility Requirements 238 13.5 Service Retainability Requirements 239 13.6 Service Throughput Requirements 239 13.7 Timestamp Accuracy Requirements 240 13.8 Elasticity Requirements 240 13.9 Release Management Requirements 241 13.10 Disaster Recovery Requirements 241 14 VIRTUALIZED INFRASTRUCTURE MEASUREMENT AND MANAGEMENT 243 14.1 Business Context for Infrastructure Service Quality Measurements 244 14.2 Cloud Consumer Measurement Options 245 14.3 Impairment Measurement Strategies 247 14.4 Managing Virtualized Infrastructure Impairments 252 15 ANALYSIS OF CLOUD-BASED APPLICATIONS 255 15.1 Reliability Block Diagrams and Side-by-Side Analysis 256 15.2 IaaS Impairment Effects Analysis 257 15.3 PaaS Failure Effects Analysis 259 15.4 Workload Distribution Analysis 260 15.5 Anti-Affi nity Analysis 262 15.6 Elasticity Analysis 263 15.7 Release Management Impact Effects Analysis 267 15.8 Recovery Point Objective Analysis 268 15.9 Recovery Time Objective Analysis 270 16 TESTING CONSIDERATIONS 273 16.1 Context for Testing 273 16.2 Test Strategy 274 16.3 Simulating Infrastructure Impairments 277 16.4 Test Planning 278 17 CONNECTING THE DOTS 287 17.1 The Application Service Quality Challenge 287 17.2 Redundancy and Robustness 289 17.3 Design for Scalability 292 17.4 Design for Extensibility 292 17.5 Design for Failure 293 17.6 Planning Considerations 294 17.7 Evolving Traditional Applications 296 17.8 Concluding Remarks 301 Abbreviations 303 References 307 About the Authors 311 Index 313

Learn how to make the most of cloud computing infrastructures We expect that software applications and services delivered via cloud computing infrastructures will deliver the same level of service quality, reliability, and availability as they do when running on traditional native hardware configurations. Cloud computing infrastructures, however, introduce many potential service impairment risks based on their virtualized computing, memory, storage, and networking resources. As a result, cloud-based application developers must learn to mitigate these impairments to ensure acceptable service delivered to end users. Service Quality of Cloud-Based Applications methodically analyzes the effect of cloud infrastructure impairments on services delivered to end users as well as the opportunities to improve service afforded by the cloud. The book recommends cloud architectures, policies, and techniques to maximize the ability of providing superior service. Expertly written and organized, this book is divided into three parts: Part I: Context sets the foundation with discussion of application service quality, the cloud model, and virtualized infrastructure impairments.Part II: Analysis methodically considers how application service is affected by infrastructure impairments.Part III: Recommendations sets forth strategies and techniques to mitigate or eliminate the service quality risks and impairments of both current cloud-based applications and those in development. An extensive list of references at the end of the book enables readers to explore individual topics in greater depth. With its expert advice on architecting and engineering cloud-based applications, Service Quality of Cloud-Based Applications makes it possible for application architects, developers, and testers to meet their customers’ and end users’ needs and expectations.