A d ddblAutomating data dependabilityDr. Kimberly KeetonISM 158: Business Information StrategygyApril 20, [email protected]© 2006 Hewlett-Packard Development Company, L.P.The information contained herein is subject to change without noticeProblems happen…ppHighNatural disaster — fire, flood, adverse weatherntSecurity breach — hackerMan made disaster — terrorism, malicious damageDenial of service attackHardware failureper incidenVirus attackUser/administrator error Software failurePower failureImpact pNetwork failureApplication failurePower failureLowPlanned downtime2 20 April 2010LowHighLowRelative frequencyImpact of problemspp• Data unavailability is expensive – downtime costs/hr:− Brokerage operations $6,450,000g− Credit card authorization $2,600,000− Ebay (1 outage 22 hours) $ 225,000Amazon com$ 180 000−Amazon.com$ 180,000− Package shipping services $ 150,000− Home shopping channel $ 113,000− Catalog sales center $ 90,000− Airline reservation center $ 89,000−Cellular service activation$ 41 000Cellular service activation$ 41,000Source: InternetWeek 4/3/2000 + Fibre Channel: A Comprehensive Introduction, R. Kembel 2000, p.8. ”...based on a survey done by Contingency Planning Research.“•Data loss is expensive100 MB $1Mll ll3 20 April 2010•Data loss is expensive–100 MB == $1M(source: Gallup poll)Impact of data unavailabilitypyExponential onsRevenue:Direct loss, compensatory increase$ BilliDirect loss, compensatory payment, lost future revenues, billing losses and investment lossesDamaged reputationFinancial performanceProductivity/ employeesProductivity:Number employee x impacted x hours out = ?$ Impactreputation$ MillionsConstant increaseTiDirect financial/ customerDamaged reputation:Customers, competitors gain advantage, suppliers, financial markets, business MinutesDaysTimepartnersFinancial performance:Revenue recognition, cash flow credit rating stock Downtime5 20 April 2010Indirect impact of downtime can be far more severe and unpredictableflow, credit rating, stock price, regulatory finesAnatomy of a failureRecovery metricsRecovery metricsupdatesRecovery Time(duration of outage)updatesnormal operation operationcrash!Recovery Pointoperation continues (e.g., at 2ndsite) Recovery Point(go back to when?)timeRPO = max allowedit ti 100%availabilityrecovery-point time (data loss)RTO = max outage timeallowed6 20 April 2010time0%outageallowedNot all applications are created equalNot all applications are created equalRequirements CategoryBusiness ProcessTypical Data FormRTO: min-1 hrRPO: < 30 minRTO: < 8 hrRPO: < 4 hrRTO, RPO: < 24 hrBusiness ProcessinggData BaseDecision SupportCollaborative EmailIT InfrastructureFileWeb InfrastructureScientific/EngineeringVaries by applicationApplication Development10 20 April 2010otherData protection techniquesData protection techniqueslocal copy (mirror)nearby remote copyprimarycopypartial copy (snapshot)tape-librarybackup copydistantremote continuous data (CDP)vault: offsite11 20 April 2010remote copyprotection (CDP)tape storageDetermining the right solutionOutlay costs Penalty costsOverall costs = outlays + penaltiesMinimize llCostSpend more, Spend less, overall costsSpend more, lose lessp,lose moreReco er time Reco er point12 20 April 2010Recovery time, Recovery pointToday’s approachypp• Best practices− Manual, ad hoc design techniquesTl f dd l−Templates for standard solutions•Insufficient tools for Insufficient tools for − Evaluating dependability provided by a candidate solution− Examining wide range of candidate designsTranslating b siness req irements into design recommendations−Translating business requirements into design recommendations• Result− Current solutions are likely conservative (and hence too costly)− Only qualitative understanding of solution dependability13 20 April 2010Data dependability overviewData dependability overviewCharacterize goals and failure consequences in financial termsFormulate data dependability questions as optimization problemsProblem inputs1. Business objectivespenalty rates2. Threatsdependability assessmentsfailure typesdependability designsOptimization engineModelsrecoveryschedules• workloads• disk arrays• mirroring• tape backupModel cost and dependability 15 20 April 2010• spare resourcesModel cost and dependability properties of common data protection and recovery techniquesTopics to coverTopics to cover• Problem and motivation• Data protection techniques refresher− Backup− Online point-in-time copies− Continuous data protection/− Remote replication/mirroring• Research in automating data dependability• Summary16 20 April 2010BackupBackup• What?Rdl d −Read-only copy on separate media, representing recovery point in past• Why?y− To permit time-travel recovery (e.g., before mistake or virus infection)− To create archival copyo c ea e a c va copy− To enable cheap disaster recovery from offsite vault• How?− Full vs. partial backups− File vs. block-level backup−Tape-based vs. disk-based architectures17 20 April 2010Tapebased vs. diskbased architecturesFull vs partial backupsFull vs. partial backups• Full backup−Copy everything backup−Copy everything backup− Restoration is straightforward− Large resource requirements (server, network, tapes)•Incremental backup•Incremental backup− Cumulative incremental: copy data that’s changed since last full backup− Differential incremental: copy data that’s changed since last f ll/ l b kpy gfull/incremental backup− Massive reduction in data moved/copied− Requires more complicated restoration Fll bk h li i l h diff il •Full backup, then cumulative incremental, then one or more differential incrementals• Most backup schedules employ a combination−Full backup over weekend daily cumulative incrementals during 18 20 April 2010−Full backup over weekend, daily cumulative incrementals during weekWhat gets backed upWhat gets backed up• File-level backupA h fl fl b b k d −Any change to file causes entire file to be backed up− Open files often require special handling software− Pro: simplifies backup and recoverypp y− Con: small changes to large files result in large backups• Block-level backupf− Only back up blocks that change in a file− Requires additional client-side processing to discover changed blocks− Pro:
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