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

<p><b>ERIC BAUER, MS,</b> is Reliability Engineering Manager in the IP Platforms CTO of Alcatel-Lucent. The holder of more than a dozen U.S. patents, Mr. Bauer is the author or coauthor of <i>Reliability and Availability of Cloud Computing, Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems, Design for Reliability: Information and Computer-Based Systems, and Practical System Reliability.</i></p> <p><b>RANDEE ADAMS, MS,</b> is a Consulting Member of the Technical Staff in the IP Platforms CTO of Alcatel-Lucent. She is the coauthor of <i>Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems and Reliability and Availability of Cloud Computing.</i> Ms. Adams has worked on many projects, including software development, delivery, engineering, architecture, and design.</p>

<p><b>Learn how to make the most of cloud computing infrastructures</b></p> <p>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.</p> <p><i>Service Quality of Cloud-Based Applications</i> 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.</p> <p>Expertly written and organized, this book is divided into three parts:</p> <ul> <li><b>Part I: Context</b> sets the foundation with discussion of application service quality, the cloud model, and virtualized infrastructure impairments.</li> <li><b>Part II: Analysis</b> methodically considers how application service is affected by infrastructure impairments.</li> <li><b>Part III: Recommendations</b> 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.</li> </ul> <p>An extensive list of references at the end of the book enables readers to explore individual topics in greater depth.</p> <p>With its expert advice on architecting and engineering cloud-based applications, <i>Service Quality of Cloud-Based Applications</i> makes it possible for application architects, developers, and testers to meet their customers’ and end users’ needs and expectations.</p>

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