Reliability and availability of cloud computing

Reliability and Availability of Cloud Computing provides IS/IT system and solution architects, developers, and engineers with the knowledge needed to assess the impact of virtualization and cloud computing on service reliability and availability. It reveals how to select the most appropriate design for reliability diligence to assure that user expectations are met.

Organized in three parts (basics, risk analysis, and recommendations), this resource is accessible to readers of diverse backgrounds and experience levels. Numerous examples and more than 100 figures throughout the book help readers visualize problems to better understand the topic--and the authors present risks and options in bulleted lists that can be applied directly to specific applications/problems.

Special features of this book include:

Rigorous analysis of the reliability and availability risks that are inherent in cloud computing Simple formulas that explain the quantitative aspects of reliability and availability Enlightening discussions of the ways in which virtualized applications and cloud deployments differ from traditional system implementations and deployments Specific recommendations for developing reliable virtualized applications and cloud-based solutions

Reliability and Availability of Cloud Computing is the guide for IS/IT staff in business, government, academia, and non-governmental organizations who are moving their applications to the cloud. It is also an important reference for professionals in technical sales, product management, and quality management, as well as software and quality engineers looking to broaden their expertise.

Author Notes

ERIC BAUER is a reliability engineering manager in the Software, Solutions and Services Group of Alcatel-Lucent. The holder of more than a dozen U.S. patents, he is the author of Design for Reliability: Information and Computer-Based Systems, Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems, and Practical System Reliability, also available from Wiley-IEEE Press.

RANDEE ADAMS is a consulting member of technical staff in the Software, Solutions and Services Group of Alcatel-Lucent and the coauthor of Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems .

Figures	p. xvii
Tables	p. xxi
Equations	p. xxiii
Introduction	p. xxv
I Basics	p. 1
1 Cloud Computing	p. 3
1.1 Essential Cloud Characteristics	p. 4
1.2 Common Cloud Characteristics	p. 6
1.3 But What, Exactly, Is Cloud Computing?	p. 7
1.4 Service Models	p. 9
1.5 Cloud Deployment Models	p. 11
1.6 Roles in Cloud Computing	p. 12
1.7 Benefi ts of Cloud Computing	p. 14
1.8 Risks of Cloud Computing	p. 15
2 Virtualization	p. 16
2.1 Background	p. 16
2.2 What Is Virtualization?	p. 17
2.3 Server Virtualization	p. 19
2.4 VM Lifecycle	p. 23
2.5 Reliability and Availability Risks of Virtualization	p. 28
3 Service Reliability and Service Availability	p. 29
3.1 Errors and Failures	p. 30
3.2 Eight-Ingredient Framework	p. 31
3.3 Service Availability	p. 34
3.4 Service Reliability	p. 43
3.5 Service Latency	p. 46
3.6 Redundancy and High Availability	p. 50
3.7 High Availability and Disaster Recovery	p. 56
3.8 Streaming Services	p. 58
3.9 Reliability and Availability Risks of Cloud Computing	p. 62
II Analysis	p. 63
4 Analyzing Cloud Reliability and Availability	p. 65
4.1 Expectations for Service Reliability and Availability	p. 65
4.2 Risks of Essential Cloud Characteristics	p. 66
4.3 Impacts of Common Cloud Characteristics	p. 70
4.4 Risks of Service Models	p. 72
4.5 IT Service Management and Availability Risks	p. 74
4.6 Outage Risks by Process Area	p. 80
4.7 Failure Detection Considerations	p. 83
4.8 Risks of Deployment Models	p. 87
4.9 Expectations of IaaS Data Centers	p. 87
5 Reliability Analysis of Virtualization	p. 90
5.1 Reliability Analysis Techniques	p. 90
5.2 Reliability Analysis of Virtualization Techniques	p. 95
5.3 Software Failure Rate Analysis	p. 100
5.4 Recovery Models	p. 101
5.5 Application Architecture Strategies	p. 108
5.6 Availability Modeling of Virtualized Recovery Options	p. 110
6 Hardware Reliability, Virtualization, and Service Availability	p. 116
6.1 Hardware Downtime Expectations	p. 116
6.2 Hardware Failures	p. 117
6.3 Hardware Failure Rate	p. 119
6.4 Hardware Failure Detection	p. 121
6.5 Hardware Failure Containment	p. 122
6.6 Hardware Failure Mitigation	p. 122
6.7 Mitigating Hardware Failures via Virtualization	p. 124
6.8 Virtualized Networks	p. 127
6.9 MTTR of Virtualized Hardware	p. 129
6.10 Discussion	p. 131
7 Capacity and Elasticity	p. 132
7.1 System Load Basics	p. 132
7.2 Overload, Service Reliability, and Service Availability	p. 135
7.3 Traditional Capacity Planning	p. 136
7.4 Cloud and Capacity	p. 137
7.5 Managing Online Capacity	p. 144
7.6 Capacity-Related Service Risks	p. 147
7.7 Capacity Management Risks	p. 153
7.8 Security and Service Availability	p. 157
7.9 Architecting for Elastic Growth and Degrowth	p. 162
8 Service Orchestration Analysis	p. 164
8.1 Service Orchestration Definition	p. 164
8.2 Policy-Based Management	p. 166
8.3 Cloud Management	p. 168
8.4 Service OrchestrationÆs Role in Risk Mitigation	p. 169
9 Geographic Distribution, Georedundancy, and Disaster Recovery	p. 174
9.1 Geographic Distribution versus Georedundancy	p. 175
9.2 Traditional Disaster Recovery	p. 175
9.3 Virtualization and Disaster Recovery	p. 177
9.4 Cloud Computing and Disaster Recovery	p. 178
9.5 Georedundancy Recovery Models	p. 180
9.6 Cloud and Traditional Collateral Benefits of Georedundancy	p. 180
9.7 Discussion	p. 182
III Recommendations	p. 183
10 Applications, Solutions, and Accountability	p. 185
10.1 Application Configuration Scenarios	p. 185
10.2 Application Deployment Scenario	p. 187
10.3 System Downtime Budgets	p. 188
10.4 End-to-End Solutions Considerations	p. 197
10.5 Attributability for Service Impairments	p. 201
10.6 Solution Service Measurement	p. 204
10.7 Managing Reliability and Service of Cloud Computing	p. 207
11 Recommendations for Architecting a Reliable System	p. 209
11.1 Architecting for Virtualization and Cloud	p. 209
11.2 Disaster Recovery	p. 216
11.3 IT Service Management Considerations	p. 217
11.4 Many Distributed Clouds versus Fewer Huge Clouds	p. 224
11.5 Minimizing Hardware-Attributed Downtime	p. 225
11.6 Architectural Optimizations	p. 231
12 Design for Reliability of Virtualized Applications	p. 244
12.1 Design for Reliability	p. 244
12.2 Tailoring DfR for Virtualized Applications	p. 246
12.3 Reliability Requirements	p. 248
12.4 Qualitative Reliability Analysis	p. 256
12.5 Quantitative Reliability Budgeting and Modeling	p. 259
12.6 Robustness Testing	p. 260
12.7 Stability Testing	p. 267
12.8 Field Performance Analysis	p. 268
12.9 Reliability Roadmap	p. 269
12.10 Hardware Reliability	p. 270
13 Design for Reliability of Cloud Solutions	p. 271
13.1 Solution Design for Reliability	p. 271
13.2 Solution Scope and Expectations	p. 273
13.3 Reliability Requirements	p. 275
13.4 Solution Modeling and Analysis	p. 279
13.5 Element Reliability Diligence	p. 285
13.6 Solution Testing and Validation	p. 285
13.7 Track and Analyze Field Performance	p. 288
13.8 Other Solution Reliability Diligence Topics	p. 292
14 Summary	p. 296
14.1 Service Reliability and Service Availability	p. 297
14.2 Failure Accountability and Cloud Computing	p. 299
14.3 Factoring Service Downtime	p. 301
14.4 Service Availability Measurement Points	p. 303
14.5 Cloud Capacity and Elasticity Considerations	p. 306
14.6 Maximizing Service Availability	p. 306
14.7 Reliability Diligence	p. 309
14.8 Concluding Remarks	p. 310
Abbreviations	p. 311
References	p. 314
About the authors	p. 318
Index	p. 319

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