top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
Beyond redundancy : how geographic redundancy can improve service availability and reliability of computer-based systems / / Eric Bauer, Randee Adams, Dan Eustace
Beyond redundancy : how geographic redundancy can improve service availability and reliability of computer-based systems / / Eric Bauer, Randee Adams, Dan Eustace
Autore Bauer Eric
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-IEEE Press, , 2011
Descrizione fisica 1 online resource (332 p.)
Disciplina 004.6
Altri autori (Persone) AdamsRandee
EustaceDan
Soggetto topico Computer input-output equipment - Reliability
Computer networks - Reliability
Redundancy (Engineering)
ISBN 1-118-10493-5
1-283-28274-7
9786613282743
1-118-10492-7
Classificazione COM051230
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Figures xv -- Tables xix -- Equations xxi -- Preface and Acknowledgments xxiii -- Audience xxiv -- Organization xxiv -- Acknowledgments xxvi -- PART 1 BASICS 1 -- 1 SERVICE, RISK, AND BUSINESS CONTINUITY 3 -- 1.1 Service Criticality and Availability Expectations 3 -- 1.2 The Eight-Ingredient Model 4 -- 1.3 Catastrophic Failures and Geographic Redundancy 7 -- 1.4 Geographically Separated Recovery Site 11 -- 1.5 Managing Risk 12 -- 1.6 Business Continuity Planning 14 -- 1.7 Disaster Recovery Planning 15 -- 1.8 Human Factors 17 -- 1.9 Recovery Objectives 17 -- 1.10 Disaster Recovery Strategies 18 -- 2 SERVICE AVAILABILITY AND SERVICE RELIABILITY 20 -- 2.1 Availability and Reliability 20 -- 2.2 Measuring Service Availability 25 -- 2.3 Measuring Service Reliability 33 -- PART 2 MODELING AND ANALYSIS OF REDUNDANCY 35 -- 3 UNDERSTANDING REDUNDANCY 37 -- 3.1 Types of Redundancy 37 -- 3.2 Modeling Availability of Internal Redundancy 44 -- 3.3 Evaluating High-Availability Mechanisms 52 -- 4 OVERVIEW OF EXTERNAL REDUNDANCY 59 -- 4.1 Generic External Redundancy Model 59 -- 4.2 Technical Distinctions between Georedundancy and Co-Located Redundancy 74 -- 4.3 Manual Graceful Switchover and Switchback 75 -- 5 EXTERNAL REDUNDANCY STRATEGY OPTIONS 77 -- 5.1 Redundancy Strategies 77 -- 5.2 Data Recovery Strategies 79 -- 5.3 External Recovery Strategies 80 -- 5.4 Manually Controlled Recovery 81 -- 5.5 System-Driven Recovery 83 -- 5.6 Client-Initiated Recovery 85 -- 6 MODELING SERVICE AVAILABILITY WITH EXTERNAL SYSTEM REDUNDANCY 98 -- 6.1 The Simplistic Answer 98 -- 6.2 Framing Service Availability of Standalone Systems 99 -- 6.3 Generic Markov Availability Model of Georedundant Recovery 103 -- 6.4 Solving the Generic Georedundancy Model 115 -- 6.5 Practical Modeling of Georedundancy 121 -- 6.6 Estimating Availability Benefit for Planned Activities 130 -- 6.7 Estimating Availability Benefit for Disasters 131 -- 7 UNDERSTANDING RECOVERY TIMING PARAMETERS 133 -- 7.1 Detecting Implicit Failures 134.
7.2 Understanding and Optimizing RTO 141 -- 8 CASE STUDY OF CLIENT-INITIATED RECOVERY 147 -- 8.1 Overview of DNS 147 -- 8.2 Mapping DNS onto Practical Client-Initiated Recovery Model 148 -- 8.3 Estimating Input Parameters 154 -- 8.4 Predicted Results 165 -- 8.5 Discussion of Predicted Results 172 -- 9 SOLUTION AND CLUSTER RECOVERY 174 -- 9.1 Understanding Solutions 174 -- 9.2 Estimating Solution Availability 177 -- 9.3 Cluster versus Element Recovery 179 -- 9.4 Element Failure and Cluster Recovery Case Study 182 -- 9.5 Comparing Element and Cluster Recovery 186 -- 9.6 Modeling Cluster Recovery 187 -- PART 3 RECOMMENDATIONS 201 -- 10 GEOREDUNDANCY STRATEGY 203 -- 10.1 Why Support Multiple Sites? 203 -- 10.2 Recovery Realms 204 -- 10.3 Recovery Strategies 206 -- 10.4 Limp-Along Architectures 207 -- 10.5 Site Redundancy Options 208 -- 10.6 Virtualization, Cloud Computing, and Standby Sites 216 -- 10.7 Recommended Design Methodology 217 -- 11 MAXIMIZING SERVICE AVAILABILITY VIA GEOREDUNDANCY 219 -- 11.1 Theoretically Optimal External Redundancy 219 -- 11.2 Practically Optimal Recovery Strategies 220 -- 11.3 Other Considerations 228 -- 12 GEOREDUNDANCY REQUIREMENTS 230 -- 12.1 Internal Redundancy Requirements 230 -- 12.2 External Redundancy Requirements 233 -- 12.3 Manually Controlled Redundancy Requirements 235 -- 12.4 Automatic External Recovery Requirements 237 -- 12.5 Operational Requirements 242 -- 13 GEOREDUNDANCY TESTING 243 -- 13.1 Georedundancy Testing Strategy 243 -- 13.2 Test Cases for External Redundancy 246 -- 13.3 Verifying Georedundancy Requirements 247 -- 13.4 Summary 254 -- 14 SOLUTION GEOREDUNDANCY CASE STUDY 256 -- 14.1 The Hypothetical Solution 256 -- 14.2 Standalone Solution Analysis 259 -- 14.3 Georedundant Solution Analysis 263 -- 14.4 Availability of the Georedundant Solution 269 -- 14.5 Requirements of Hypothetical Solution 269 -- 14.6 Testing of Hypothetical Solution 277 -- Summary 285 -- Appendix: Markov Modeling of Service Availability 292 -- Acronyms 296.
References 298 -- About the Authors 300 -- Index 302.
Record Nr. UNINA-9910139596903321
Bauer Eric  
Hoboken, New Jersey : , : Wiley-IEEE Press, , 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Beyond redundancy : how geographic redundancy can improve service availability and reliability of computer-based systems / / Eric Bauer, Randee Adams, Dan Eustace
Beyond redundancy : how geographic redundancy can improve service availability and reliability of computer-based systems / / Eric Bauer, Randee Adams, Dan Eustace
Autore Bauer Eric
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-IEEE Press, , 2011
Descrizione fisica 1 online resource (332 p.)
Disciplina 004.6
Altri autori (Persone) AdamsRandee
EustaceDan
Soggetto topico Computer input-output equipment - Reliability
Computer networks - Reliability
Redundancy (Engineering)
ISBN 1-118-10493-5
1-283-28274-7
9786613282743
1-118-10492-7
Classificazione COM051230
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Figures xv -- Tables xix -- Equations xxi -- Preface and Acknowledgments xxiii -- Audience xxiv -- Organization xxiv -- Acknowledgments xxvi -- PART 1 BASICS 1 -- 1 SERVICE, RISK, AND BUSINESS CONTINUITY 3 -- 1.1 Service Criticality and Availability Expectations 3 -- 1.2 The Eight-Ingredient Model 4 -- 1.3 Catastrophic Failures and Geographic Redundancy 7 -- 1.4 Geographically Separated Recovery Site 11 -- 1.5 Managing Risk 12 -- 1.6 Business Continuity Planning 14 -- 1.7 Disaster Recovery Planning 15 -- 1.8 Human Factors 17 -- 1.9 Recovery Objectives 17 -- 1.10 Disaster Recovery Strategies 18 -- 2 SERVICE AVAILABILITY AND SERVICE RELIABILITY 20 -- 2.1 Availability and Reliability 20 -- 2.2 Measuring Service Availability 25 -- 2.3 Measuring Service Reliability 33 -- PART 2 MODELING AND ANALYSIS OF REDUNDANCY 35 -- 3 UNDERSTANDING REDUNDANCY 37 -- 3.1 Types of Redundancy 37 -- 3.2 Modeling Availability of Internal Redundancy 44 -- 3.3 Evaluating High-Availability Mechanisms 52 -- 4 OVERVIEW OF EXTERNAL REDUNDANCY 59 -- 4.1 Generic External Redundancy Model 59 -- 4.2 Technical Distinctions between Georedundancy and Co-Located Redundancy 74 -- 4.3 Manual Graceful Switchover and Switchback 75 -- 5 EXTERNAL REDUNDANCY STRATEGY OPTIONS 77 -- 5.1 Redundancy Strategies 77 -- 5.2 Data Recovery Strategies 79 -- 5.3 External Recovery Strategies 80 -- 5.4 Manually Controlled Recovery 81 -- 5.5 System-Driven Recovery 83 -- 5.6 Client-Initiated Recovery 85 -- 6 MODELING SERVICE AVAILABILITY WITH EXTERNAL SYSTEM REDUNDANCY 98 -- 6.1 The Simplistic Answer 98 -- 6.2 Framing Service Availability of Standalone Systems 99 -- 6.3 Generic Markov Availability Model of Georedundant Recovery 103 -- 6.4 Solving the Generic Georedundancy Model 115 -- 6.5 Practical Modeling of Georedundancy 121 -- 6.6 Estimating Availability Benefit for Planned Activities 130 -- 6.7 Estimating Availability Benefit for Disasters 131 -- 7 UNDERSTANDING RECOVERY TIMING PARAMETERS 133 -- 7.1 Detecting Implicit Failures 134.
7.2 Understanding and Optimizing RTO 141 -- 8 CASE STUDY OF CLIENT-INITIATED RECOVERY 147 -- 8.1 Overview of DNS 147 -- 8.2 Mapping DNS onto Practical Client-Initiated Recovery Model 148 -- 8.3 Estimating Input Parameters 154 -- 8.4 Predicted Results 165 -- 8.5 Discussion of Predicted Results 172 -- 9 SOLUTION AND CLUSTER RECOVERY 174 -- 9.1 Understanding Solutions 174 -- 9.2 Estimating Solution Availability 177 -- 9.3 Cluster versus Element Recovery 179 -- 9.4 Element Failure and Cluster Recovery Case Study 182 -- 9.5 Comparing Element and Cluster Recovery 186 -- 9.6 Modeling Cluster Recovery 187 -- PART 3 RECOMMENDATIONS 201 -- 10 GEOREDUNDANCY STRATEGY 203 -- 10.1 Why Support Multiple Sites? 203 -- 10.2 Recovery Realms 204 -- 10.3 Recovery Strategies 206 -- 10.4 Limp-Along Architectures 207 -- 10.5 Site Redundancy Options 208 -- 10.6 Virtualization, Cloud Computing, and Standby Sites 216 -- 10.7 Recommended Design Methodology 217 -- 11 MAXIMIZING SERVICE AVAILABILITY VIA GEOREDUNDANCY 219 -- 11.1 Theoretically Optimal External Redundancy 219 -- 11.2 Practically Optimal Recovery Strategies 220 -- 11.3 Other Considerations 228 -- 12 GEOREDUNDANCY REQUIREMENTS 230 -- 12.1 Internal Redundancy Requirements 230 -- 12.2 External Redundancy Requirements 233 -- 12.3 Manually Controlled Redundancy Requirements 235 -- 12.4 Automatic External Recovery Requirements 237 -- 12.5 Operational Requirements 242 -- 13 GEOREDUNDANCY TESTING 243 -- 13.1 Georedundancy Testing Strategy 243 -- 13.2 Test Cases for External Redundancy 246 -- 13.3 Verifying Georedundancy Requirements 247 -- 13.4 Summary 254 -- 14 SOLUTION GEOREDUNDANCY CASE STUDY 256 -- 14.1 The Hypothetical Solution 256 -- 14.2 Standalone Solution Analysis 259 -- 14.3 Georedundant Solution Analysis 263 -- 14.4 Availability of the Georedundant Solution 269 -- 14.5 Requirements of Hypothetical Solution 269 -- 14.6 Testing of Hypothetical Solution 277 -- Summary 285 -- Appendix: Markov Modeling of Service Availability 292 -- Acronyms 296.
References 298 -- About the Authors 300 -- Index 302.
Record Nr. UNINA-9910831180903321
Bauer Eric  
Hoboken, New Jersey : , : Wiley-IEEE Press, , 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Design for reliability : information and computer-based systems / / Eric Bauer
Design for reliability : information and computer-based systems / / Eric Bauer
Autore Bauer Eric
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-IEEE Press, , c2010
Descrizione fisica 1 online resource (349 p.)
Disciplina 620.00452
620/.00452
Soggetto topico Reliability (Engineering)
ISBN 1-283-03544-8
9786613035448
1-118-07508-0
1-118-07510-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Reliability Basics. Reliability and Availability Concepts -- System Basics -- What can go Wrong -- Reliability Concepts. Failure Containment and Redundancy -- Robust Design Principles -- Error Detection -- Analyzing and Modeling Reliability and Robustness -- Design for Reliability. Reliability Requirements -- Reliability Analysis -- Reliability Budgeting and Modeling -- Robustness and Stability Testing -- Closing the Loop -- Design for Reliability Case Study -- Conclusion -- Appendix: Assessing Design for Reliability Diligence -- Abbreviations -- References -- Photo Credits -- About the Author -- Index.
Record Nr. UNINA-9910133450803321
Bauer Eric  
Hoboken, New Jersey : , : Wiley-IEEE Press, , c2010
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Lean computing for the cloud / / Eric Bauer
Lean computing for the cloud / / Eric Bauer
Autore Bauer Eric
Pubbl/distr/stampa Piscataway, New Jersey : , : IEEE Press, 2016
Descrizione fisica 1 online resource (255 p.)
Disciplina 004.6782
Soggetto topico Cloud computing
ISBN 1-119-23232-5
1-119-23235-X
1-119-23230-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction xi -- Acknowledgments xv -- Abbreviations xvii -- 1. Basics 1 -- 1.1 Cloud Computing Fundamentals 1 -- 1.2 Roles in Cloud Computing 6 -- 1.3 Applications 9 -- 1.3.1 Application Service Quality 11 -- 1.4 Demand, Supply, Capacity, and Fungibility 13 -- 1.5 Demand Variability 16 -- 1.6 Chapter Review 18 -- 2. Rethinking Capacity Management 19 -- 2.1 Capacity Management 19 -- 2.2 Demand Management 21 -- 2.3 Performance Management 21 -- 2.4 Canonical Capacity Management 23 -- 2.4.1 Traditional Capacity Management 24 -- 2.4.2 ITIL Capacity Management 27 -- 2.4.3 eTOM Capacity Management 28 -- 2.4.4 Discussion 30 -- 2.5 Three Cloud Capacity Management Problems 30 -- 2.5.1 Physical Resource Capacity Management 31 -- 2.5.2 Virtual Resource Capacity Management 32 -- 2.5.3 Application Capacity Management 33 -- 2.6 Cloud Capacity Management as a Value Chain 36 -- 2.7 Chapter Review 39 -- 3. Lean Thinking on Cloud Capacity Management 41 -- 3.1 Lean Thinking Overview 41 -- 3.2 Goal 42 -- 3.3 Seeing Waste (Nonvalue-Adding Activities) 43 -- 3.3.1 Reserve Capacity 45 -- 3.3.2 Excess Application Capacity 46 -- 3.3.3 Excess Online Infrastructure Capacity 46 -- 3.3.4 Excess Physical Infrastructure Capacity 46 -- 3.3.5 Inadequate Capacity 47 -- 3.3.6 Infrastructure Overhead 48 -- 3.3.7 Capacity Management Overhead 48 -- 3.3.8 Resource Overhead 49 -- 3.3.9 Power Management Overhead 50 -- 3.3.10 Workload Migration 50 -- 3.3.11 Complexity Overhead 51 -- 3.3.12 Resource Allocation Failure 51 -- 3.3.13 Leaking and Lost Resources 53 -- 3.3.14 Waste Heat 53 -- 3.3.15 Carbon Footprint 54 -- 3.4 Key Principles 54 -- 3.4.1 Move toward Flow 55 -- 3.4.2 Pull versus Push 55 -- 3.4.3 Level the Workload 55 -- 3.4.4 Stop and Fix Problems 55 -- 3.4.5 Master Practices 56 -- 3.4.6 Visual Management 57 -- 3.4.7 Use Well-Tested Technology 57 -- 3.4.8 Take a Long-Term Perspective 58 -- 3.4.9 Grow, Learn, and Teach Others 58 -- 3.4.10 Develop Exceptional People 58 -- 3.4.11 Partners Help Each Other Improve 58.
3.4.12 Go See 59 -- 3.4.13 Implement Rapidly 59 -- 3.4.14 Become a Learning Organization 59 -- 3.5 Pillar: Respect 59 -- 3.6 Pillar: Continuous Improvement 61 -- 3.7 Foundation 62 -- 3.8 Cadence 62 -- 3.9 Lean Capacity Management Philosophy 63 -- 3.10 Chapter Review 64 -- 4. Lean Cloud Capacity Management Strategy 67 -- 4.1 Lean Application Service Provider Strategy 68 -- 4.1.1 User Workload Placement 71 -- 4.1.2 Application Performance Management 73 -- 4.2 Lean Infrastructure Service Provider Strategies 73 -- 4.2.1 Physical Resource Capacity Management 76 -- 4.3 Full Stream Optimization 77 -- 4.4 Chapter Review 79 -- 5. Electric Power Generation as Cloud Infrastructure Analog 81 -- 5.1 Power Generation as a Cloud Infrastructure Analog 81 -- 5.2 Business Context 83 -- 5.3 Business Structure 86 -- 5.4 Technical Similarities 88 -- 5.5 Impedance and Fungibility 91 -- 5.6 Capacity Ratings 94 -- 5.7 Bottled Capacity 95 -- 5.8 Location of Production Considerations 95 -- 5.9 Demand Management 97 -- 5.10 Demand and Reserves 98 -- 5.11 Service Curtailment 99 -- 5.12 Balance and Grid Operations 100 -- 5.13 Chapter Review 103 -- 6. Application Capacity Management as an Inventory Management Problem 105 -- 6.1 The Application Capacity Management Service Delivery Chain 105 -- 6.2 Traditional Application Service Production Chain 107 -- 6.3 Elasticity and Demand-Driven Capacity Management 108 -- 6.4 Application Service as Retail Analog 110 -- 6.4.1 Locational Consideration 112 -- 6.4.2 Inventory and Capacity 112 -- 6.4.3 Service Level 113 -- 6.4.4 Inventory Carrying Costs 114 -- 6.4.5 Inventory Decision, Planning, and Ordering 115 -- 6.4.6 Agility 118 -- 6.4.7 Changing Consumption Patterns 118 -- 6.5 Chapter Review 118 -- 7. Lean Demand Management 119 -- 7.1 Infrastructure Demand Management Techniques 120 -- 7.1.1 Resource Scheduling 121 -- 7.1.2 Resource Curtailment 121 -- 7.1.3 Mandatory Demand Shaping 122 -- 7.1.4 Voluntary Demand Shaping 123 -- 7.1.5 Scheduling Maintenance Actions 123.
7.1.6 Resource Pricing 123 -- 7.2 Application Demand Management Techniques 124 -- 7.2.1 Queues and Buffers 124 -- 7.2.2 Load Balancers 124 -- 7.2.3 Overload Controls 125 -- 7.2.4 Explicit Demand Management Actions 125 -- 7.2.5 Scheduling Maintenance Actions 125 -- 7.2.6 User Pricing Strategies 126 -- 7.3 Full Stream Analysis Methodology 126 -- 7.3.1 Analyze Applications' Natural Demand Patterns 127 -- 7.3.2 Analyze Applications' Tolerances 128 -- 7.3.3 Create Attractive Infrastructure Pricing Models 129 -- 7.3.4 Deploy Optimal Infrastructure Demand Management Models 130 -- 7.4 Chapter Review 131 -- 8. Lean Reserves 133 -- 8.1 What Is Reserve Capacity? 133 -- 8.2 Uses of Reserve Capacity 135 -- 8.2.1 Random Demand Peaks 135 -- 8.2.2 Component or Resource Failure 136 -- 8.2.3 Infrastructure Element Failure 136 -- 8.2.4 Infrastructure Resource Curtailment or Demand Management Action 137 -- 8.2.5 Demand Exceeding Forecast 137 -- 8.2.6 Lead Time Demand 137 -- 8.2.7 Catastrophic Failures and Force Majeure Events 139 -- 8.3 Reserve Capacity as a Feature 139 -- 8.4 Types of Reserve Capacity 140 -- 8.4.1 Automatic Infrastructure Power Management Controls 140 -- 8.4.2 Utilize Application Reserve Capacity 141 -- 8.4.3 Place/Migrate Demand into Underutilized Capacity 141 -- 8.4.4 Grow Online Capacity 141 -- 8.4.5 Service Curtailment/Degradation 141 -- 8.4.6 Mandatory Demand Shaping 141 -- 8.4.7 Voluntary Demand Shaping 142 -- 8.4.8 Emergency Reserves 142 -- 8.5 Limits of Reserve Capacity 144 -- 8.6 Ideal Reserve 144 -- 8.6.1 Normal (Co-located) Reserve 144 -- 8.6.2 Emergency (Geographically Distributed) Reserve 146 -- 8.7 Chapter Review 147 -- 9. Lean Infrastructure Commitment 149 -- 9.1 Unit Commitment and Infrastructure Commitment 150 -- 9.2 Framing the Unit Commitment Problem 151 -- 9.3 Framing the Infrastructure Commitment Problem 153 -- 9.4 Understanding Element Startup Time 155 -- 9.5 Understanding Element Shutdown Time 157 -- 9.6 Pulling It All Together 160 -- 9.7 Chapter Review 166.
10. Lean Cloud Capacity Management Performance Indicators 167 -- 10.1 Perfect Capacity Metrics 168 -- 10.2 Capacity Management Metrics 172 -- 10.3 Infrastructure Commitment Metrics 173 -- 10.4 Waste Metrics 174 -- 10.4.1 Reserve Capacity Waste Metrics 174 -- 10.4.2 Excess Application Capacity Metrics 175 -- 10.4.3 Excess Online Infrastructure Capacity Metrics 175 -- 10.4.4 Excess Physical Infrastructure Capacity Metrics 175 -- 10.4.5 Inadequate Capacity Metrics 175 -- 10.4.6 Infrastructure Overhead Waste Metrics 176 -- 10.4.7 Capacity Management Overhead Waste Metrics 176 -- 10.4.8 Resource Overhead Waste Metrics 176 -- 10.4.9 Power Management Overhead Waste Metrics 177 -- 10.4.10 Workload Migration Metrics 177 -- 10.4.11 Complexity Overhead Metrics 178 -- 10.4.12 Resource Allocation Failure Metrics 178 -- 10.4.13 Leaking and Lost Resources 179 -- 10.4.14 Waste Heat Metrics 179 -- 10.4.15 Carbon Footprint Metrics 180 -- 10.5 Key Principle Indicators 180 -- 10.6 Cost of Poor Quality 181 -- 10.7 Metrics and Service Boundaries 182 -- 10.8 Measurements and Maturity 183 -- 10.9 Chapter Review 185 -- 11. Summary 187 -- 11.1 Cloud Computing as a Service Delivery Chain 187 -- 11.2 Lean Cloud Computing 190 -- 11.3 Reimagining Cloud Capacity 192 -- 11.4 Lean Demand Management 195 -- 11.5 Lean Reserves 197 -- 11.6 Lean Infrastructure Service Provider Considerations 198 -- 11.7 Lean Application Service Provider Considerations 198 -- 11.8 Lean Infrastructure Commitment 199 -- 11.9 Visualizing Perfect Capacity 201 -- 11.10 Lean Cloud Computing Metrics 203 -- 11.11 Concluding Remarks 204 -- References 207 -- About the Author 211 -- Index 213.
Record Nr. UNINA-9910136393403321
Bauer Eric  
Piscataway, New Jersey : , : IEEE Press, 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Lean computing for the cloud / / Eric Bauer
Lean computing for the cloud / / Eric Bauer
Autore Bauer Eric
Pubbl/distr/stampa Piscataway, New Jersey : , : IEEE Press, 2016
Descrizione fisica 1 online resource (255 p.)
Disciplina 004.6782
Soggetto topico Cloud computing
ISBN 1-119-23232-5
1-119-23235-X
1-119-23230-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction xi -- Acknowledgments xv -- Abbreviations xvii -- 1. Basics 1 -- 1.1 Cloud Computing Fundamentals 1 -- 1.2 Roles in Cloud Computing 6 -- 1.3 Applications 9 -- 1.3.1 Application Service Quality 11 -- 1.4 Demand, Supply, Capacity, and Fungibility 13 -- 1.5 Demand Variability 16 -- 1.6 Chapter Review 18 -- 2. Rethinking Capacity Management 19 -- 2.1 Capacity Management 19 -- 2.2 Demand Management 21 -- 2.3 Performance Management 21 -- 2.4 Canonical Capacity Management 23 -- 2.4.1 Traditional Capacity Management 24 -- 2.4.2 ITIL Capacity Management 27 -- 2.4.3 eTOM Capacity Management 28 -- 2.4.4 Discussion 30 -- 2.5 Three Cloud Capacity Management Problems 30 -- 2.5.1 Physical Resource Capacity Management 31 -- 2.5.2 Virtual Resource Capacity Management 32 -- 2.5.3 Application Capacity Management 33 -- 2.6 Cloud Capacity Management as a Value Chain 36 -- 2.7 Chapter Review 39 -- 3. Lean Thinking on Cloud Capacity Management 41 -- 3.1 Lean Thinking Overview 41 -- 3.2 Goal 42 -- 3.3 Seeing Waste (Nonvalue-Adding Activities) 43 -- 3.3.1 Reserve Capacity 45 -- 3.3.2 Excess Application Capacity 46 -- 3.3.3 Excess Online Infrastructure Capacity 46 -- 3.3.4 Excess Physical Infrastructure Capacity 46 -- 3.3.5 Inadequate Capacity 47 -- 3.3.6 Infrastructure Overhead 48 -- 3.3.7 Capacity Management Overhead 48 -- 3.3.8 Resource Overhead 49 -- 3.3.9 Power Management Overhead 50 -- 3.3.10 Workload Migration 50 -- 3.3.11 Complexity Overhead 51 -- 3.3.12 Resource Allocation Failure 51 -- 3.3.13 Leaking and Lost Resources 53 -- 3.3.14 Waste Heat 53 -- 3.3.15 Carbon Footprint 54 -- 3.4 Key Principles 54 -- 3.4.1 Move toward Flow 55 -- 3.4.2 Pull versus Push 55 -- 3.4.3 Level the Workload 55 -- 3.4.4 Stop and Fix Problems 55 -- 3.4.5 Master Practices 56 -- 3.4.6 Visual Management 57 -- 3.4.7 Use Well-Tested Technology 57 -- 3.4.8 Take a Long-Term Perspective 58 -- 3.4.9 Grow, Learn, and Teach Others 58 -- 3.4.10 Develop Exceptional People 58 -- 3.4.11 Partners Help Each Other Improve 58.
3.4.12 Go See 59 -- 3.4.13 Implement Rapidly 59 -- 3.4.14 Become a Learning Organization 59 -- 3.5 Pillar: Respect 59 -- 3.6 Pillar: Continuous Improvement 61 -- 3.7 Foundation 62 -- 3.8 Cadence 62 -- 3.9 Lean Capacity Management Philosophy 63 -- 3.10 Chapter Review 64 -- 4. Lean Cloud Capacity Management Strategy 67 -- 4.1 Lean Application Service Provider Strategy 68 -- 4.1.1 User Workload Placement 71 -- 4.1.2 Application Performance Management 73 -- 4.2 Lean Infrastructure Service Provider Strategies 73 -- 4.2.1 Physical Resource Capacity Management 76 -- 4.3 Full Stream Optimization 77 -- 4.4 Chapter Review 79 -- 5. Electric Power Generation as Cloud Infrastructure Analog 81 -- 5.1 Power Generation as a Cloud Infrastructure Analog 81 -- 5.2 Business Context 83 -- 5.3 Business Structure 86 -- 5.4 Technical Similarities 88 -- 5.5 Impedance and Fungibility 91 -- 5.6 Capacity Ratings 94 -- 5.7 Bottled Capacity 95 -- 5.8 Location of Production Considerations 95 -- 5.9 Demand Management 97 -- 5.10 Demand and Reserves 98 -- 5.11 Service Curtailment 99 -- 5.12 Balance and Grid Operations 100 -- 5.13 Chapter Review 103 -- 6. Application Capacity Management as an Inventory Management Problem 105 -- 6.1 The Application Capacity Management Service Delivery Chain 105 -- 6.2 Traditional Application Service Production Chain 107 -- 6.3 Elasticity and Demand-Driven Capacity Management 108 -- 6.4 Application Service as Retail Analog 110 -- 6.4.1 Locational Consideration 112 -- 6.4.2 Inventory and Capacity 112 -- 6.4.3 Service Level 113 -- 6.4.4 Inventory Carrying Costs 114 -- 6.4.5 Inventory Decision, Planning, and Ordering 115 -- 6.4.6 Agility 118 -- 6.4.7 Changing Consumption Patterns 118 -- 6.5 Chapter Review 118 -- 7. Lean Demand Management 119 -- 7.1 Infrastructure Demand Management Techniques 120 -- 7.1.1 Resource Scheduling 121 -- 7.1.2 Resource Curtailment 121 -- 7.1.3 Mandatory Demand Shaping 122 -- 7.1.4 Voluntary Demand Shaping 123 -- 7.1.5 Scheduling Maintenance Actions 123.
7.1.6 Resource Pricing 123 -- 7.2 Application Demand Management Techniques 124 -- 7.2.1 Queues and Buffers 124 -- 7.2.2 Load Balancers 124 -- 7.2.3 Overload Controls 125 -- 7.2.4 Explicit Demand Management Actions 125 -- 7.2.5 Scheduling Maintenance Actions 125 -- 7.2.6 User Pricing Strategies 126 -- 7.3 Full Stream Analysis Methodology 126 -- 7.3.1 Analyze Applications' Natural Demand Patterns 127 -- 7.3.2 Analyze Applications' Tolerances 128 -- 7.3.3 Create Attractive Infrastructure Pricing Models 129 -- 7.3.4 Deploy Optimal Infrastructure Demand Management Models 130 -- 7.4 Chapter Review 131 -- 8. Lean Reserves 133 -- 8.1 What Is Reserve Capacity? 133 -- 8.2 Uses of Reserve Capacity 135 -- 8.2.1 Random Demand Peaks 135 -- 8.2.2 Component or Resource Failure 136 -- 8.2.3 Infrastructure Element Failure 136 -- 8.2.4 Infrastructure Resource Curtailment or Demand Management Action 137 -- 8.2.5 Demand Exceeding Forecast 137 -- 8.2.6 Lead Time Demand 137 -- 8.2.7 Catastrophic Failures and Force Majeure Events 139 -- 8.3 Reserve Capacity as a Feature 139 -- 8.4 Types of Reserve Capacity 140 -- 8.4.1 Automatic Infrastructure Power Management Controls 140 -- 8.4.2 Utilize Application Reserve Capacity 141 -- 8.4.3 Place/Migrate Demand into Underutilized Capacity 141 -- 8.4.4 Grow Online Capacity 141 -- 8.4.5 Service Curtailment/Degradation 141 -- 8.4.6 Mandatory Demand Shaping 141 -- 8.4.7 Voluntary Demand Shaping 142 -- 8.4.8 Emergency Reserves 142 -- 8.5 Limits of Reserve Capacity 144 -- 8.6 Ideal Reserve 144 -- 8.6.1 Normal (Co-located) Reserve 144 -- 8.6.2 Emergency (Geographically Distributed) Reserve 146 -- 8.7 Chapter Review 147 -- 9. Lean Infrastructure Commitment 149 -- 9.1 Unit Commitment and Infrastructure Commitment 150 -- 9.2 Framing the Unit Commitment Problem 151 -- 9.3 Framing the Infrastructure Commitment Problem 153 -- 9.4 Understanding Element Startup Time 155 -- 9.5 Understanding Element Shutdown Time 157 -- 9.6 Pulling It All Together 160 -- 9.7 Chapter Review 166.
10. Lean Cloud Capacity Management Performance Indicators 167 -- 10.1 Perfect Capacity Metrics 168 -- 10.2 Capacity Management Metrics 172 -- 10.3 Infrastructure Commitment Metrics 173 -- 10.4 Waste Metrics 174 -- 10.4.1 Reserve Capacity Waste Metrics 174 -- 10.4.2 Excess Application Capacity Metrics 175 -- 10.4.3 Excess Online Infrastructure Capacity Metrics 175 -- 10.4.4 Excess Physical Infrastructure Capacity Metrics 175 -- 10.4.5 Inadequate Capacity Metrics 175 -- 10.4.6 Infrastructure Overhead Waste Metrics 176 -- 10.4.7 Capacity Management Overhead Waste Metrics 176 -- 10.4.8 Resource Overhead Waste Metrics 176 -- 10.4.9 Power Management Overhead Waste Metrics 177 -- 10.4.10 Workload Migration Metrics 177 -- 10.4.11 Complexity Overhead Metrics 178 -- 10.4.12 Resource Allocation Failure Metrics 178 -- 10.4.13 Leaking and Lost Resources 179 -- 10.4.14 Waste Heat Metrics 179 -- 10.4.15 Carbon Footprint Metrics 180 -- 10.5 Key Principle Indicators 180 -- 10.6 Cost of Poor Quality 181 -- 10.7 Metrics and Service Boundaries 182 -- 10.8 Measurements and Maturity 183 -- 10.9 Chapter Review 185 -- 11. Summary 187 -- 11.1 Cloud Computing as a Service Delivery Chain 187 -- 11.2 Lean Cloud Computing 190 -- 11.3 Reimagining Cloud Capacity 192 -- 11.4 Lean Demand Management 195 -- 11.5 Lean Reserves 197 -- 11.6 Lean Infrastructure Service Provider Considerations 198 -- 11.7 Lean Application Service Provider Considerations 198 -- 11.8 Lean Infrastructure Commitment 199 -- 11.9 Visualizing Perfect Capacity 201 -- 11.10 Lean Cloud Computing Metrics 203 -- 11.11 Concluding Remarks 204 -- References 207 -- About the Author 211 -- Index 213.
Record Nr. UNINA-9910830141703321
Bauer Eric  
Piscataway, New Jersey : , : IEEE Press, 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Practical system reliability / / Eric Bauer, Xuemei Zhang, Douglas A. Kimber
Practical system reliability / / Eric Bauer, Xuemei Zhang, Douglas A. Kimber
Autore Bauer Eric
Pubbl/distr/stampa Piscataway, New Jersey : , : IEEE Press, , c2009
Descrizione fisica 1 online resource (303 p.)
Disciplina 620.00452
Soggetto topico Telecommunication systems - Reliability
Telecommunication
Soggetto non controllato high availability
ISBN 1-282-11379-8
9786612113796
0-470-45540-3
0-470-45538-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgments -- 1 Introduction -- 2 System Availability -- 2.1 Availability, Service and Elements -- 2.2 Classical View -- 2.3 Customers' View -- 2.4 Standards View -- 3 Conceptual Model of Reliability and Availability -- 3.1 Concept of Highly Available Systems -- 3.2 Conceptual Model of System Availability -- 3.3 Failures -- 3.4 Outage Resolution -- 3.5 Downtime Budgets -- 4 Why Availability Varies Between Customers -- 4.1 Causes of Variation in Outage Event Reporting -- 4.2 Causes of Variation in Outage Duration -- 5 Modeling Availability -- 5.1 Overview of Modeling Techniques -- 5.2 Modeling Definitions -- 5.3 Practical Modeling -- 5.4 Widget Example -- 5.5 Alignment with Industry Standards -- 6 Estimating Parameters and Availability from Field Data -- 6.1 Self-Maintaining Customers -- 6.2 Analyzing Field Outage Data -- 6.3 Analyzing Performance and Alarm Data -- 6.4 Coverage Factor and Failure Rate -- 6.5 Uncovered Failure Recovery Time -- 6.6 Covered Failure Detection and Recovery Time -- 7 Estimating Input Parameters from Lab Data -- 7.1 Hardware Failure Rate -- 7.2 Software Failure Rate -- 7.3 Coverage Factors -- 7.4 Timing Parameters -- 7.5 System-Level Parameters -- 8 Estimating Input Parameters in the Architecture/Design Stage -- 8.1 Hardware Parameters -- 8.2 System-Level Parameters -- 8.3 Sensitivity Analysis -- 9 Prediction Accuracy -- 9.1 How Much Field Data Is Enough? -- 9.2 How Does One Measure Sampling and Prediction Errors? -- 9.3 What Causes Prediction Errors? -- 10 Connecting the Dots -- 10.1 Set Availability Requirements -- 10.2 Incorporate Architectural and Design Techniques -- 10.3 Modeling to Verify Feasibility -- 10.4 Testing -- 10.5 Update Availability Prediction -- 10.6 Periodic Field Validation and Model Update -- 10.7 Building an Availability Roadmap -- 10.8 Reliability Report -- 11 Summary -- Appendix A System Reliability Report outline -- 1 Executive Summary -- 2 Reliability Requirements -- 3 Unplanned Downtime Model and Results.
Annex A Reliability Definitions -- Annex B References -- Annex C Markov Model State-Transition Diagrams -- Appendix B Reliability and Availability Theory -- 1 Reliability and Availability Definitions -- 2 Probability Distributions in Reliability Evaluation -- 3 Estimation of Confidence Intervals -- Appendix C Software Reliability Growth Models -- 1 Software Characteristic Models -- 2 Nonhomogeneous Poisson Process Models -- Appendix D Acronyms and Abbreviations -- Appendix E Bibliography -- Index -- About the Authors.
Record Nr. UNINA-9910145962103321
Bauer Eric  
Piscataway, New Jersey : , : IEEE Press, , c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Practical system reliability / / Eric Bauer, Xuemei Zhang, Douglas A. Kimber
Practical system reliability / / Eric Bauer, Xuemei Zhang, Douglas A. Kimber
Autore Bauer Eric
Pubbl/distr/stampa Piscataway, New Jersey : , : IEEE Press, , c2009
Descrizione fisica 1 online resource (303 p.)
Disciplina 620.00452
Soggetto topico Telecommunication systems - Reliability
Telecommunication
Soggetto non controllato high availability
ISBN 1-282-11379-8
9786612113796
0-470-45540-3
0-470-45538-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgments -- 1 Introduction -- 2 System Availability -- 2.1 Availability, Service and Elements -- 2.2 Classical View -- 2.3 Customers' View -- 2.4 Standards View -- 3 Conceptual Model of Reliability and Availability -- 3.1 Concept of Highly Available Systems -- 3.2 Conceptual Model of System Availability -- 3.3 Failures -- 3.4 Outage Resolution -- 3.5 Downtime Budgets -- 4 Why Availability Varies Between Customers -- 4.1 Causes of Variation in Outage Event Reporting -- 4.2 Causes of Variation in Outage Duration -- 5 Modeling Availability -- 5.1 Overview of Modeling Techniques -- 5.2 Modeling Definitions -- 5.3 Practical Modeling -- 5.4 Widget Example -- 5.5 Alignment with Industry Standards -- 6 Estimating Parameters and Availability from Field Data -- 6.1 Self-Maintaining Customers -- 6.2 Analyzing Field Outage Data -- 6.3 Analyzing Performance and Alarm Data -- 6.4 Coverage Factor and Failure Rate -- 6.5 Uncovered Failure Recovery Time -- 6.6 Covered Failure Detection and Recovery Time -- 7 Estimating Input Parameters from Lab Data -- 7.1 Hardware Failure Rate -- 7.2 Software Failure Rate -- 7.3 Coverage Factors -- 7.4 Timing Parameters -- 7.5 System-Level Parameters -- 8 Estimating Input Parameters in the Architecture/Design Stage -- 8.1 Hardware Parameters -- 8.2 System-Level Parameters -- 8.3 Sensitivity Analysis -- 9 Prediction Accuracy -- 9.1 How Much Field Data Is Enough? -- 9.2 How Does One Measure Sampling and Prediction Errors? -- 9.3 What Causes Prediction Errors? -- 10 Connecting the Dots -- 10.1 Set Availability Requirements -- 10.2 Incorporate Architectural and Design Techniques -- 10.3 Modeling to Verify Feasibility -- 10.4 Testing -- 10.5 Update Availability Prediction -- 10.6 Periodic Field Validation and Model Update -- 10.7 Building an Availability Roadmap -- 10.8 Reliability Report -- 11 Summary -- Appendix A System Reliability Report outline -- 1 Executive Summary -- 2 Reliability Requirements -- 3 Unplanned Downtime Model and Results.
Annex A Reliability Definitions -- Annex B References -- Annex C Markov Model State-Transition Diagrams -- Appendix B Reliability and Availability Theory -- 1 Reliability and Availability Definitions -- 2 Probability Distributions in Reliability Evaluation -- 3 Estimation of Confidence Intervals -- Appendix C Software Reliability Growth Models -- 1 Software Characteristic Models -- 2 Nonhomogeneous Poisson Process Models -- Appendix D Acronyms and Abbreviations -- Appendix E Bibliography -- Index -- About the Authors.
Record Nr. UNISA-996213051603316
Bauer Eric  
Piscataway, New Jersey : , : IEEE Press, , c2009
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Reliability and availability of cloud computing / / Eric Bauer, Randee Adams
Reliability and availability of cloud computing / / Eric Bauer, Randee Adams
Autore Bauer Eric
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-IEEE Press, , 2012
Descrizione fisica 1 online resource (353 p.)
Disciplina 004.6782
Altri autori (Persone) AdamsRandee
Soggetto topico Cloud computing
Computer software - Reliabillity
Computer software - Quality control
Computer security
ISBN 1-118-39400-3
1-282-16517-8
9786613808486
1-118-39398-8
1-118-39399-6
Classificazione TEC032000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Figures xvii -- Tables xxi -- Equations xxiii -- Introduction xxv -- I BASICS 1 -- 1 CLOUD COMPUTING 3 -- 1.1 Essential Cloud Characteristics 4 -- 1.2 Common Cloud Characteristics 6 -- 1.3 But What, Exactly, Is Cloud Computing? 7 -- 1.4 Service Models 9 -- 1.5 Cloud Deployment Models 11 -- 1.6 Roles in Cloud Computing 12 -- 1.7 Benefi ts of Cloud Computing 14 -- 1.8 Risks of Cloud Computing 15 -- 2 VIRTUALIZATION 16 -- 2.1 Background 16 -- 2.2 What Is Virtualization? 17 -- 2.3 Server Virtualization 19 -- 2.4 VM Lifecycle 23 -- 2.5 Reliability and Availability Risks of Virtualization 28 -- 3 SERVICE RELIABILITY AND SERVICE AVAILABILITY 29 -- 3.1 Errors and Failures 30 -- 3.2 Eight-Ingredient Framework 31 -- 3.3 Service Availability 34 -- 3.4 Service Reliability 43 -- 3.5 Service Latency 46 -- 3.6 Redundancy and High Availability 50 -- 3.7 High Availability and Disaster Recovery 56 -- 3.8 Streaming Services 58 -- 3.9 Reliability and Availability Risks of Cloud Computing 62 -- II ANALYSIS 63 -- 4 ANALYZING CLOUD RELIABILITY AND AVAILABILITY 65 -- 4.1 Expectations for Service Reliability and Availability 65 -- 4.2 Risks of Essential Cloud Characteristics 66 -- 4.3 Impacts of Common Cloud Characteristics 70 -- 4.4 Risks of Service Models 72 -- 4.5 IT Service Management and Availability Risks 74 -- 4.6 Outage Risks by Process Area 80 -- 4.7 Failure Detection Considerations 83 -- 4.8 Risks of Deployment Models 87 -- 4.9 Expectations of IaaS Data Centers 87 -- 5 RELIABILITY ANALYSIS OF VIRTUALIZATION 90 -- 5.1 Reliability Analysis Techniques 90 -- 5.2 Reliability Analysis of Virtualization Techniques 95 -- 5.3 Software Failure Rate Analysis 100 -- 5.4 Recovery Models 101 -- 5.5 Application Architecture Strategies 108 -- 5.6 Availability Modeling of Virtualized Recovery Options 110 -- 6 HARDWARE RELIABILITY, VIRTUALIZATION, AND SERVICE AVAILABILITY 116 -- 6.1 Hardware Downtime Expectations 116 -- 6.2 Hardware Failures 117 -- 6.3 Hardware Failure Rate 119 -- 6.4 Hardware Failure Detection 121.
6.5 Hardware Failure Containment 122 -- 6.6 Hardware Failure Mitigation 122 -- 6.7 Mitigating Hardware Failures via Virtualization 124 -- 6.8 Virtualized Networks 127 -- 6.9 MTTR of Virtualized Hardware 129 -- 6.10 Discussion 131 -- 7 CAPACITY AND ELASTICITY 132 -- 7.1 System Load Basics 132 -- 7.2 Overload, Service Reliability, and Service Availability 135 -- 7.3 Traditional Capacity Planning 136 -- 7.4 Cloud and Capacity 137 -- 7.5 Managing Online Capacity 144 -- 7.6 Capacity-Related Service Risks 147 -- 7.7 Capacity Management Risks 153 -- 7.8 Security and Service Availability 157 -- 7.9 Architecting for Elastic Growth and Degrowth 162 -- 8 SERVICE ORCHESTRATION ANALYSIS 164 -- 8.1 Service Orchestration Definition 164 -- 8.2 Policy-Based Management 166 -- 8.3 Cloud Management 168 -- 8.4 Service Orchestration's Role in Risk Mitigation 169 -- 9 GEOGRAPHIC DISTRIBUTION, GEOREDUNDANCY, AND DISASTER RECOVERY 174 -- 9.1 Geographic Distribution versus Georedundancy 175 -- 9.2 Traditional Disaster Recovery 175 -- 9.3 Virtualization and Disaster Recovery 177 -- 9.4 Cloud Computing and Disaster Recovery 178 -- 9.5 Georedundancy Recovery Models 180 -- 9.6 Cloud and Traditional Collateral Benefits of Georedundancy 180 -- 9.7 Discussion 182 -- III RECOMMENDATIONS 183 -- 10 APPLICATIONS, SOLUTIONS, AND ACCOUNTABILITY 185 -- 10.1 Application Configuration Scenarios 185 -- 10.2 Application Deployment Scenario 187 -- 10.3 System Downtime Budgets 188 -- 10.4 End-to-End Solutions Considerations 197 -- 10.5 Attributability for Service Impairments 201 -- 10.6 Solution Service Measurement 204 -- 10.7 Managing Reliability and Service of Cloud Computing 207 -- 11 RECOMMENDATIONS FOR ARCHITECTING A RELIABLE SYSTEM 209 -- 11.1 Architecting for Virtualization and Cloud 209 -- 11.2 Disaster Recovery 216 -- 11.3 IT Service Management Considerations 217 -- 11.4 Many Distributed Clouds versus Fewer Huge Clouds 224 -- 11.5 Minimizing Hardware-Attributed Downtime 225 -- 11.6 Architectural Optimizations 231.
12 DESIGN FOR RELIABILITY OF VIRTUALIZED APPLICATIONS 244 -- 12.1 Design for Reliability 244 -- 12.2 Tailoring DfR for Virtualized Applications 246 -- 12.3 Reliability Requirements 248 -- 12.4 Qualitative Reliability Analysis 256 -- 12.5 Quantitative Reliability Budgeting and Modeling 259 -- 12.6 Robustness Testing 260 -- 12.7 Stability Testing 267 -- 12.8 Field Performance Analysis 268 -- 12.9 Reliability Roadmap 269 -- 12.10 Hardware Reliability 270 -- 13 DESIGN FOR RELIABILITY OF CLOUD SOLUTIONS 271 -- 13.1 Solution Design for Reliability 271 -- 13.2 Solution Scope and Expectations 273 -- 13.3 Reliability Requirements 275 -- 13.4 Solution Modeling and Analysis 279 -- 13.5 Element Reliability Diligence 285 -- 13.6 Solution Testing and Validation 285 -- 13.7 Track and Analyze Field Performance 288 -- 13.8 Other Solution Reliability Diligence Topics 292 -- 14 SUMMARY 296 -- 14.1 Service Reliability and Service Availability 297 -- 14.2 Failure Accountability and Cloud Computing 299 -- 14.3 Factoring Service Downtime 301 -- 14.4 Service Availability Measurement Points 303 -- 14.5 Cloud Capacity and Elasticity Considerations 306 -- 14.6 Maximizing Service Availability 306 -- 14.7 Reliability Diligence 309 -- 14.8 Concluding Remarks 310 -- Abbreviations 311 -- References 314 -- About the Authors 318 -- Index 319.
Record Nr. UNINA-9910138870503321
Bauer Eric  
Hoboken, New Jersey : , : Wiley-IEEE Press, , 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Reliability and availability of cloud computing / / Eric Bauer, Randee Adams
Reliability and availability of cloud computing / / Eric Bauer, Randee Adams
Autore Bauer Eric
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-IEEE Press, , 2012
Descrizione fisica 1 online resource (353 p.)
Disciplina 004.6782
Altri autori (Persone) AdamsRandee
Soggetto topico Cloud computing
Computer software - Reliabillity
Computer software - Quality control
Computer security
ISBN 1-118-39400-3
1-282-16517-8
9786613808486
1-118-39398-8
1-118-39399-6
Classificazione TEC032000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Figures xvii -- Tables xxi -- Equations xxiii -- Introduction xxv -- I BASICS 1 -- 1 CLOUD COMPUTING 3 -- 1.1 Essential Cloud Characteristics 4 -- 1.2 Common Cloud Characteristics 6 -- 1.3 But What, Exactly, Is Cloud Computing? 7 -- 1.4 Service Models 9 -- 1.5 Cloud Deployment Models 11 -- 1.6 Roles in Cloud Computing 12 -- 1.7 Benefi ts of Cloud Computing 14 -- 1.8 Risks of Cloud Computing 15 -- 2 VIRTUALIZATION 16 -- 2.1 Background 16 -- 2.2 What Is Virtualization? 17 -- 2.3 Server Virtualization 19 -- 2.4 VM Lifecycle 23 -- 2.5 Reliability and Availability Risks of Virtualization 28 -- 3 SERVICE RELIABILITY AND SERVICE AVAILABILITY 29 -- 3.1 Errors and Failures 30 -- 3.2 Eight-Ingredient Framework 31 -- 3.3 Service Availability 34 -- 3.4 Service Reliability 43 -- 3.5 Service Latency 46 -- 3.6 Redundancy and High Availability 50 -- 3.7 High Availability and Disaster Recovery 56 -- 3.8 Streaming Services 58 -- 3.9 Reliability and Availability Risks of Cloud Computing 62 -- II ANALYSIS 63 -- 4 ANALYZING CLOUD RELIABILITY AND AVAILABILITY 65 -- 4.1 Expectations for Service Reliability and Availability 65 -- 4.2 Risks of Essential Cloud Characteristics 66 -- 4.3 Impacts of Common Cloud Characteristics 70 -- 4.4 Risks of Service Models 72 -- 4.5 IT Service Management and Availability Risks 74 -- 4.6 Outage Risks by Process Area 80 -- 4.7 Failure Detection Considerations 83 -- 4.8 Risks of Deployment Models 87 -- 4.9 Expectations of IaaS Data Centers 87 -- 5 RELIABILITY ANALYSIS OF VIRTUALIZATION 90 -- 5.1 Reliability Analysis Techniques 90 -- 5.2 Reliability Analysis of Virtualization Techniques 95 -- 5.3 Software Failure Rate Analysis 100 -- 5.4 Recovery Models 101 -- 5.5 Application Architecture Strategies 108 -- 5.6 Availability Modeling of Virtualized Recovery Options 110 -- 6 HARDWARE RELIABILITY, VIRTUALIZATION, AND SERVICE AVAILABILITY 116 -- 6.1 Hardware Downtime Expectations 116 -- 6.2 Hardware Failures 117 -- 6.3 Hardware Failure Rate 119 -- 6.4 Hardware Failure Detection 121.
6.5 Hardware Failure Containment 122 -- 6.6 Hardware Failure Mitigation 122 -- 6.7 Mitigating Hardware Failures via Virtualization 124 -- 6.8 Virtualized Networks 127 -- 6.9 MTTR of Virtualized Hardware 129 -- 6.10 Discussion 131 -- 7 CAPACITY AND ELASTICITY 132 -- 7.1 System Load Basics 132 -- 7.2 Overload, Service Reliability, and Service Availability 135 -- 7.3 Traditional Capacity Planning 136 -- 7.4 Cloud and Capacity 137 -- 7.5 Managing Online Capacity 144 -- 7.6 Capacity-Related Service Risks 147 -- 7.7 Capacity Management Risks 153 -- 7.8 Security and Service Availability 157 -- 7.9 Architecting for Elastic Growth and Degrowth 162 -- 8 SERVICE ORCHESTRATION ANALYSIS 164 -- 8.1 Service Orchestration Definition 164 -- 8.2 Policy-Based Management 166 -- 8.3 Cloud Management 168 -- 8.4 Service Orchestration's Role in Risk Mitigation 169 -- 9 GEOGRAPHIC DISTRIBUTION, GEOREDUNDANCY, AND DISASTER RECOVERY 174 -- 9.1 Geographic Distribution versus Georedundancy 175 -- 9.2 Traditional Disaster Recovery 175 -- 9.3 Virtualization and Disaster Recovery 177 -- 9.4 Cloud Computing and Disaster Recovery 178 -- 9.5 Georedundancy Recovery Models 180 -- 9.6 Cloud and Traditional Collateral Benefits of Georedundancy 180 -- 9.7 Discussion 182 -- III RECOMMENDATIONS 183 -- 10 APPLICATIONS, SOLUTIONS, AND ACCOUNTABILITY 185 -- 10.1 Application Configuration Scenarios 185 -- 10.2 Application Deployment Scenario 187 -- 10.3 System Downtime Budgets 188 -- 10.4 End-to-End Solutions Considerations 197 -- 10.5 Attributability for Service Impairments 201 -- 10.6 Solution Service Measurement 204 -- 10.7 Managing Reliability and Service of Cloud Computing 207 -- 11 RECOMMENDATIONS FOR ARCHITECTING A RELIABLE SYSTEM 209 -- 11.1 Architecting for Virtualization and Cloud 209 -- 11.2 Disaster Recovery 216 -- 11.3 IT Service Management Considerations 217 -- 11.4 Many Distributed Clouds versus Fewer Huge Clouds 224 -- 11.5 Minimizing Hardware-Attributed Downtime 225 -- 11.6 Architectural Optimizations 231.
12 DESIGN FOR RELIABILITY OF VIRTUALIZED APPLICATIONS 244 -- 12.1 Design for Reliability 244 -- 12.2 Tailoring DfR for Virtualized Applications 246 -- 12.3 Reliability Requirements 248 -- 12.4 Qualitative Reliability Analysis 256 -- 12.5 Quantitative Reliability Budgeting and Modeling 259 -- 12.6 Robustness Testing 260 -- 12.7 Stability Testing 267 -- 12.8 Field Performance Analysis 268 -- 12.9 Reliability Roadmap 269 -- 12.10 Hardware Reliability 270 -- 13 DESIGN FOR RELIABILITY OF CLOUD SOLUTIONS 271 -- 13.1 Solution Design for Reliability 271 -- 13.2 Solution Scope and Expectations 273 -- 13.3 Reliability Requirements 275 -- 13.4 Solution Modeling and Analysis 279 -- 13.5 Element Reliability Diligence 285 -- 13.6 Solution Testing and Validation 285 -- 13.7 Track and Analyze Field Performance 288 -- 13.8 Other Solution Reliability Diligence Topics 292 -- 14 SUMMARY 296 -- 14.1 Service Reliability and Service Availability 297 -- 14.2 Failure Accountability and Cloud Computing 299 -- 14.3 Factoring Service Downtime 301 -- 14.4 Service Availability Measurement Points 303 -- 14.5 Cloud Capacity and Elasticity Considerations 306 -- 14.6 Maximizing Service Availability 306 -- 14.7 Reliability Diligence 309 -- 14.8 Concluding Remarks 310 -- Abbreviations 311 -- References 314 -- About the Authors 318 -- Index 319.
Record Nr. UNINA-9910831097803321
Bauer Eric  
Hoboken, New Jersey : , : Wiley-IEEE Press, , 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Service quality of cloud-based applications / / Eric Bauer, Randee Adams
Service quality of cloud-based applications / / Eric Bauer, Randee Adams
Autore Bauer Eric
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2014]
Descrizione fisica 1 online resource (340 p.)
Disciplina 004.6782
Soggetto topico Cloud computing
Application software - Reliability
Quality of service (Computer networks)
ISBN 1-118-76328-9
1-118-76340-8
1-118-76339-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; IEEE Press; Title page; Copyright page; Contents; Figures; Tables and Equations; Tables; Equations; 1: Introduction; 1.1 Approach; 1.2 Target Audience; 1.3 Organization; Acknowledgments; I: Context; 2: Application Service Quality; 2.1 Simple Application Model; 2.2 Service Boundaries; 2.3 Key Quality and Performance Indicators; 2.4 Key Application Characteristics; 2.4.1 Service Criticality; 2.4.2 Application Interactivity; 2.4.3 Tolerance to Network Traffic Impairments; 2.5 Application Service Quality Metrics; 2.5.1 Service Availability; 2.5.2 Service Latency; 2.5.3 Service Reliability
2.5.4 Service Accessibility2.5.5 Service Retainability; 2.5.6 Service Throughput; 2.5.7 Service Timestamp Accuracy; 2.5.8 Application-Specific Service Quality Measurements; 2.6 Technical Service versus Support Service; 2.6.1 Technical Service Quality; 2.6.2 Support Service Quality; 2.7 Security Considerations; 3: Cloud Model; 3.1 Roles in Cloud Computing; 3.2 Cloud Service Models; 3.3 Cloud Essential Characteristics; 3.3.1 On-Demand Self-Service; 3.3.2 Broad Network Access; 3.3.3 Resource Pooling; 3.3.4 Rapid Elasticity; 3.3.5 Measured Service; 3.4 Simplified Cloud Architecture
3.4.1 Application Software3.4.2 Virtual Machine Servers; 3.4.3 Virtual Machine Server Controllers; 3.4.4 Cloud Operations Support Systems; 3.4.5 Cloud Technology Components Offered "as-a-Service"; 3.5 Elasticity Measurements; 3.5.1 Density; 3.5.2 Provisioning Interval; 3.5.3 Release Interval; 3.5.4 Scaling In and Out; 3.5.5 Scaling Up and Down; 3.5.6 Agility; 3.5.7 Slew Rate and Linearity; 3.5.8 Elasticity Speedup; 3.6 Regions and Zones; 3.7 Cloud Awareness; 4: Virtualized Infrastructure Impairments; 4.1 Service Latency, Virtualization, and the Cloud
4.1.1 Virtualization and Cloud Causes of Latency Variation4.1.2 Virtualization Overhead; 4.1.3 Increased Variability of Infrastructure Performance; 4.2 VM Failure; 4.3 Nondelivery of Configured VM Capacity; 4.4 Delivery of Degraded VM Capacity; 4.5 Tail Latency; 4.6 Clock Event Jitter; 4.7 Clock Drift; 4.8 Failed or Slow Allocation and Startup of VM Instance; 4.9 Outlook for Virtualized Infrastructure Impairments; II: Analysis; 5: Application Redundancy and Cloud Computing; 5.1 Failures, Availability, and Simplex Architectures; 5.2 Improving Software Repair Times via Virtualization
5.3 Improving Infrastructure Repair Times via Virtualization5.3.1 Understanding Hardware Repair; 5.3.2 VM Repair-as-a-Service; 5.3.3 Discussion; 5.4 Redundancy and Recoverability; 5.4.1 Improving Recovery Times via Virtualization; 5.5 Sequential Redundancy and Concurrent Redundancy; 5.5.1 Hybrid Concurrent Strategy; 5.6 Application Service Impact of Virtualization Impairments; 5.6.1 Service Impact for Simplex Architectures; 5.6.2 Service Impact for Sequential Redundancy Architectures; 5.6.3 Service Impact for Concurrent Redundancy Architectures
5.6.4 Service Impact for Hybrid Concurrent Architectures
Record Nr. UNINA-9910138991203321
Bauer Eric  
Hoboken, New Jersey : , : Wiley, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui