Eric Bauer - Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems
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- Book:Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems
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Beyond Redundancy: How Geographic Redundancy Can Improve Service Availability and Reliability of Computer-Based Systems: summary, description and annotation
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Enterprises make significant investments in geographically redundant systems to mitigate the very unlikely risk of a natural or man-made disaster rendering their primary site inaccessible or destroying it completely. While geographic redundancy has obvious benefits for disaster recovery, it is far less obvious what benefit georedundancy offers for more common hardware, software, and human failures. Beyond Redundancy provides both a theoretical and practical treatment of the feasible and likely benefits from geographic redundancy for both service availability and service reliability.
The book is organized into three sections:
Basics provides the necessary background on georedundancy and service availability
Modeling and Analysis of Redundancy gives the technical and mathematical details of service availability modeling of georedundant configurations
Recommendations offers specific recommendations on architecture, requirements, design, testing, and analysis of georedundant configurations
A complete georedundant case study is included to illustrate the recommendations. The book considers both georedundant systems and georedundant solutions. The text also provides a general discussion about the capital expense/operating expense tradeoff that frames system redundancy and georedundancy. These added features make Beyond Redundancy an invaluable resource for network/system planners, IS/IT personnel, system architects, system engineers, developers, testers, and disaster recovery/business continuity consultants and planners.
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Kenneth Moore, Director of IEEE Book and Information Services (BIS)
Technical Reviewers
Xuemei Zhang
Network Design and Performance Analysis Division, AT&T Labs
Kim W. Tracy
Northeastern Illinois University
Copyright 2012 by Institute of Electrical and Electronics Engineers. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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Library of Congress Cataloging-in-Publication Data
Bauer, Eric.
Beyond redundancy : how geographic redundancy can improve service availability and reliability of computer-based systems / Eric Bauer, Randee Adams, Daniel Eustace.
p. cm.
ISBN 978-1-118-03829-1 (hardback)
1. Computer input-output equipmentReliability. 2. Computer networksReliability. 3. Redundancy (Engineering) I. Adams, Randee. II. Eustace, Daniel. III. Title.
TK7887.5.B395 2011
004.6dc22
2011008324
oBook ISBN: 978-1-118-10491-0
ePDF ISBN: 978-1-118-10492-7
ePub ISBN: 978-1-118-10493-4
To our families for their encouragement and support:
Erics wife Sandy and children Lauren and Mark
Randees husband Scott and son Ryan
Dans wife Helen and daughters Christie and Chelsea
FIGURES
Figure 1.1. The Eight-Ingredient Model
Figure 1.2. Canonical Disaster Recovery Scenario
Figure 1.3. Recovery Time Objective and Recovery Point Objective
Figure 2.1. Canonical Service Impact Timeline
Figure 2.2. Reliability, Availability, and Quality of Service
Figure 2.3. Outage Downtime in Standalone NE Deployment
Figure 2.4. Outage Downtime with Redundant NE Deployment
Figure 3.1. Types of System Redundancy
Figure 3.2. State Transition Diagram of Simplex System
Figure 3.3. Availability Improvement Strategies for a Simplex System
Figure 3.4. Reliability Block Diagram of Redundant Pair
Figure 3.5. Service Availability of ActiveStandby Redundant Pair
Figure 3.6. Sample Reliability Block Diagram
Figure 3.7. Sample Standalone Redundant System
Figure 3.8. ActiveActive Markov Availability Model
Figure 3.9. ActiveActive Markov Availability Model with Formulas
Figure 3.10. ActiveStandby Markov Availability Model
Figure 3.11. Simplex Model with Mathematical Formulas
Figure 3.12. Outage Duration
Figure 3.13. Outage Duration for Disasters
Figure 4.1. Generic High Availability Model
Figure 4.2. Stable Service Delivery Path Across Generic Model
Figure 4.3. Degenerate Generic Model Without Element C
Figure 4.4. Failure Scenario in Generic Model
Figure 4.5. Recovery Scenario in Generic Model
Figure 4.6. Generic High Availability Model with Load Sharing
Figure 4.7. Georedundancy Using DNS SRV Records
Figure 5.1. Client-Initiated Recovery Scenario
Figure 5.2. Typical Client Processing Logic for Standalone Server
Figure 5.3. Generic Client-Initiated Recovery Logic with Redundant Servers
Figure 5.4. Session States Seen by a SIP Client A in Client-Initiated Recovery
Figure 5.5. Session States Seen by A in Client-Initiated Recovery Without Registration
Figure 5.6. Browser Query to Web Server
Figure 6.1. Generic High Availability Model
Figure 6.2. Sample Unavailability Contribution for ActiveStandby Redundancy
Figure 6.3. Simplified Standalone High-Availability Downtime Model
Figure 6.4. General Georedundant Manual Recovery Markov Transition Diagram
Figure 6.5. System-Driven Georedundant Recovery Markov Transition Diagram
Figure 6.6. Client-Initiated Georedundant Recovery Markov Transition Diagram
Figure 6.7. Client-Initiated and System-Driven Georedundant Recovery
Figure 6.8. Overlaying Generic Georedundancy Model Onto Simplistic Model
Figure 6.9. Outage Durations for Sample System with internal Redundancy
Figure 6.10. Simplified Client-Initiated Recovery Markov Model
Figure 6.11. Modified Client-Initiated Recovery Model
Figure 6.12. Estimating Service Unavailability During Manual Disaster Recovery
Figure 7.1. Standard Protocol Timeout
Figure 7.2. Adaptive Protocol Timeout
Figure 7.3. Timeout with Multiple Parallel Requests
Figure 7.4. Client/Server Keepalive
Figure 7.5. Manually Controlled Recovery Timeline
Figure 7.6. System-Driven Recovery Timeline
Figure 7.7. Client-Initiated Recovery Timeline
Figure 8.1. Generic Model of DNS
Figure 8.2. Practical Client-Initiated Model for DNS
Figure 8.3. Modeling Normal DNS Operation
Figure 8.4. Modeling Server Failure
Figure 8.5. Modeling Timeout Failure
Figure 8.6. Modeling Abnormal Server Failure
Figure 8.7. Modeling Multiple Server Failures
Figure 8.8. Simplified Client-Initiated Recovery Model with Formulas
Figure 8.9. Critical Failure Rate Parameter
Figure 8.10. Failure Rate as a Function of MTTR
Figure 8.11. F EXPLICIT Parameter
Figure 8.12. C CLIENT Parameter
Figure 8.13. TIMEOUT Parameter
Figure 8.14. CLIENTSFD Parameter
Figure 8.15. CLIENT Parameter
Figure 8.16. A CLUSTER1 Parameter
Figure 8.17. F CLIENT Parameter
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