T∕NIDA 004-2025 金融行业数据中心网络建网技术要求

NIDA-TS-004-2025

NIDA/TC/WG03/TF05Date:2025-07-17

TechnicalRequirementsforFinancialDataCenterNetworkConstruction

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Contents

Foreword iv

1Scope 1

2Normativereferences 1

3Termsanddefinitions 1

4Abbreviations 1

5BackgroundofFinancialdatacenternetworkStandards 3

5.1Serviceevolution 3

5.2Technologyevolution 4

5.2.1Automaticservicedeployment 4

5.2.2Intelligentcomputing 5

5.2.3Storage 5

5.2.4AIfornetwork 6

5.3NetworkingEvolution 6

5.3.1Multi-POD 7

5.3.2Multi-DC 7

5.4PolicyConstraints 8

6FinancialDataCenterNetworkConstructionRoadmap 8

6.1Subclausetitle(firstlevSingleDCandmultiplePODs 8

6.1.1Subclausetitle(secondlevel) 8

6.1.2SwitchingcorePOD 9

6.1.3IntelligentcomputingPOD 9

6.1.4BigdataPOD 11

6.1.5StoragePOD 12

6.2Multi-DCDeployment 14

7KeyTechnicalRequirementsforaSingleDCNetwork 16

7.1Networkautomation 16

7.1.1Automaticservicedeployment 16

7.1.2Servicefloworchestration 16

7.1.3ConfigurationSimulationVerification 17

7.2Openness 18

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7.2.1NorthboundOpenness 18

7.2.2SouthboundOpenness 18

7.3Highnetworkperformance 18

7.3.1Flowcontroltechnologies 19

7.3.2Congestiontechnologies 19

7.3.3Loadbalancing 21

7.4Highreliability 21

7.4.1Link-levelreliability 22

7.4.2Device-levelreliability 22

7.4.3Network-levelreliability 23

7.5IntelligentO&M 23

7.5.1Networkdigitalmap 23

7.5.2Networkfaultdemarcationandlocating 25

7.5.3Application-levelfaultdemarcationandlocating 27

7.5.4Full-flowanalysis 27

7.6Security 28

7.6.1DeviceLayerSecurity 28

7.6.2NetworkLayerSecurity 28

7.6.3Managementandcontrollayersecurity 29

8KeyTechnicalRequirementsforMulti DCDataCenterNetworks...................................29

8.1Multi-DCreliability 29

8.1.1Intra-cityactive-activeDCreliability 29

8.1.2Geo-RedundantDCReliability 30

8.2Multi-DCO&M 30

8.3Multi-DCsecurity 30

AnnexA 31

Bibliography 32

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Foreword

TheNetworkInnovationandDevelopmentAlliance(NIDA)isavoluntaryinternational,industry-specific,non-profitsocialorganizationcomprisedofindustryorganizations,universities,researchinstitutes,companies,andotherentitiesfromaroundtheworld,dedicatedtopromotingfixed

networktechnologyinnovationandindustrialupgrading.

TheworkofpreparingNIDAStandardsisnormallycarriedoutthroughtheNIDATechnical

Committee(TC),itsWorkingGroups(WGs),andTaskForces(TFs).TheproceduresusedtodevelopthisdocumentandthoseintendedforitsfurthermaintenancearedescribedintheNIDAStandardsDevelopmentGuidelines.

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ThisdocumentwaspreparedbytheTechnicalCommittee(TC),WorkingGroupWG03,DatacenterNetworkWorkGroup,TaskForceTF05.

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AnyfeedbackorquestionsonthisdocumentshouldbedirectedtotheNIDATCSecretariat.

Thisdocumentisdraftedby:HuaweiTechnologiesCo.,Ltd,IndustrialandCommercialBankofChina,PingAnTechnology(Shenzhen)Co.,Ltd,InternetAssociationofKazakhstan.

Maindraftersofthisdocument:LiZhang,JiuyongLi,XueshanYu,ZuruiMeng,ShavkatSabirov.

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TechnicalRequirementsforFinancialdatacenternetwork

1Scope

Thisdocumentspecifiesthetechnicalrequirementsforfinancialdatacenternetwork,includingthenetworkarchitecture,networkingscenarios,andkeytechnologiesofthedatacenternetwork.

Thisdocumentisapplicabletothenetworkconstructionplanningandtechnicalevaluationofthefinancialdatacenternetwork,andprovidestechnicalbasisforthenetworktest.

2Normativereferences

Therearenonormativereferencesinthisdocument.

3Termsanddefinitions

Forthepurposesofthisdocument,thefollowingtermsanddefinitionsapply.

ISOandIECmaintainterminologydatabasesforuseinstandardizationatthefollowingaddresses:

—ISOOnlinebrowsingplatform:availableat

/obp

—IECElectropedia:availableat

/

3.1

Dataplanefastrecovery

Dataplanefastrecoveryinthisdocumentreferstoasub-millisecondfaultrecoverytechnology.Itprovidesdata-planefastfaultdetectionandconvergencecapabilitiesforhardwarefaults,suchasopticalmodulefaultsandloosenessoftransmissionopticalcables,improvingdevice-levelreliability.

3.2

Dataplanecrossingfault

Dataplanecrossingfaultinthisdocumentreferstoanautomaticfaultrecoverytechnology.Itisusedtosolvesession-levelserviceexceptionscausedbysilentfaults,suchaslinkfaults,forwardingentryexceptions,forwardingcomponentexceptions,physicalportsthatareUpbutcannotforwardtraffic,andconfigurationerrors.Providesfastfaultdetectionandconvergencecapabilitiesbasedonthedataplane,achievingpathswitchoverwithinsecondsandimprovingnetworkreliability.

4Abbreviations

Thefollowingabbreviationsapplytothisdocument.

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BFD:BidirectionalForwardingDetectio

BGP:BorderGatewayProtocol

CI/CD:ContinuousIntegrationandContinuousDeliveryCLOS:ClosArchitecture

DC:DataCenter

DPCF:DataPlaneCrossingFault

DPFR:DataPlaneFastRecovery

ECMP:Equal-CostMulti-Path

ECN:ExplicitCongestionNotification

FC:FibreChannel

FCT:FlowCompletionTime

FET:FlowEfficientThroughput

FNR:FlowNAKRate

HDD:HardDiskDrive

IOPS:Input/outputOperationsPerSecond

LLM:LargeLanguageModel

MDC:Multi-Datacenter-Controller

M-LAG:Multi-chassislinkaggregationgroup

NOF:NVMeoverFabric

NVMe:Non-VolatileMemoryexpress

OSPF:OpenShortestPathFirst

PFC:Priority-basedFlowControl

POD:PointofDelivery

RDMA:RemoteDirectMemoryAccess

RoCE:RDMAoverConvergedEthernet

SLA:ServiceLevelAgreement

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SSD:Solid-StateDrive

SZTP:SecureZeroTouchProvisioning

5BackgroundofFinancialdatacenternetworkStandards

5.1Serviceevolution

Inthecontextofdigitaltransformation,digitalupgradesbasedontechnologiessuchas5G,bigdata,artificialintelligence,andtheInternetofThingshavecoveredallindustries.ThenewservicesofSmartConnectofEverythingposenewrequirementsonenterprisedatacenters.Takethefinancialindustryasanexample.DigitalfinancehasbeenanewbusinessformthatusesdigitaltechnologiesandInternetplatforms,aswellasthedigitalization,intelligence,andonlineofservicesandproductstoprovidecustomerswithmoreconvenient,efficient,secure,andpersonalizedfinancialservicesandproducts.WiththestrengtheningofAItechnologies,digitalfinancewillprovidemoreaccuratefinancialservices,improveoperationalefficiencyandchangebusinessmodels.

Figure1—Digitalfinancescenariosandrequirements

Thenewrequirementsofthefinancialindustrydatacenterinthedigitalfinanceeraincludeserviceautomationandefficientopenness,ultra-reliability,highperformance,intelligentO&M,andfull-lifecyclesecurity,whichhavethefollowingconnotations:

lThefinancialindustryprovidescustomerswithall-roundfinancialservicesbybuildingplatformsandAPPsindatacenter.Appsareupdatedfrequently,andservicesmustbedeployedassoonaspossible.Traditionalmanualconfigurationmodeistime-consuminganderror-prone.Servicedeploymentacrossmulti-vendordevicesandmulti-servicetechnologieshashighrequirementsonO&Mpersonnel.Thedatacenternetworkneedstoprovideefficientandopenautomaticservicedeploymentcapabilities,buildanE2EserviceautomationarchitecturethatincludestheO&Msystem,managementandcontrolsystem,and

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interconnectionofdevicesfrommultiplevendors,andrealizetheend-to-endservicedeploymentautomationinservicescenariossuchasunderlaynetworks,overlayservices,andnetwork-securityintegration.

lInthe5Gmobilepaymentera,thefinancialindustryfacescustomeraccessrequests24hoursaday.Thenumberofdailycustomervisitsandtheaveragedailytransactionservicecallsaremorethan100million.Thisrequiresdatacenternetworktoprovide7*24ultra-reliableserviceandultra-fastresponserate.

lThefinancialindustryhasawiderangeofrequirementsforbigdataandAItechnologies,whichareusedtoenablecustomerdigitalprofilingandcreditriskanalysis,financialfrauddetectionandmarketriskprediction,productandservicemodelinnovation,digitalservicesandoperations,etc.Financialdatacentersaregrowingincomputingpowerandstoragescale.Withtheevolutionoflargelanguagemodelsandstoragetechnologies,large-bandwidthandlosslessnetworksarerequiredfordatacenterstoensureno-packet-lossandlow-latencytransmissionofintelligentcomputing,modeltrainingandinference,andhigh-speedstorage.

lCustomersinthefinancialindustryhavehigherrequirementsonexperienceinthedigitalera.Continuousandrapidservicerequirementsposechallengestothetimelinessofnetworktroubleshooting.Inthefuture,withthefurtherexpansionoffinancialdatacenters,AI,digitaltwins,andexpertexperiencetechnologiesarerequiredtoimplementself-awareness,self-analysis,self-healing,andself-optimizationofnetworks,enablingintelligentcollaboration,dynamicoptimization,andinteractiveinnovationofdata,technologies,processes,andorganizations.

lAsfinancialservicesbecomeincreasinglycomplexinlifescenarios,thesecurityprotectionchainbecomesincreasinglycomplex.Atthesametime,theexternalinformationsecuritysituationisgrim,facingmoreandmorecomplexsecuritythreats.Financialbusinesshasnaturalhighsecurityrequirements.datacenternetworkshouldbuildacomprehensiveandmulti-dimensionalsecurityassurancesystemtopreventdataleakageandprotectcustomerassetsandprivacy.

5.2Technologyevolution

5.2.1Automaticservicedeployment

TheimprovementofservicedeploymentefficiencyandaccuracyinfinancialdatacentereffectivelyenhancescustomerexperienceandreducesnetworkO&MOPEX.BuildanautomaticinteractiveICTsystemthatintegratestheresourcesystem,serviceorchestrationsystem,workordersystem,servicecollaborationanddeploymentsystem,andservicedetectionsystemtoautomatetheentire

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processofserviceplanning,resourceallocation,configurationchangeapproval,servicedeployment,servicedetection,andservicevisualization.Ithasbecomeakeyrequirementforfinancialdatacenternetworkoperationandmanagement.

DatacenterservicesareusuallydeployedacrossPODsorevenacrossDCs,involvingdevicesfrommultiplevendorsandfrequentservicechanges.Serviceautomationmusthavethecapabilitiesofagiledevelopment,continuousevolution,opennessandprogrammability,andusability.WiththeevolutionofCI/CD-relatedtechnologies,suchasworkfloworchestrationandplug-and-play(PnP)ofmulti-vendordevices,itprovidestechnicalsupportfortheintegrationofmultiplesystemstobuildanautomaticICTsystem.

5.2.2Intelligentcomputing

WiththebreakthroughdevelopmentofAIlargelanguagemodels,trainingandreinforcementtrainingoflarge-scalemodelsinthefinancialindustryarealsoevolving.High-performancecomputingisthecorerequirementofintelligentcomputingdatacenters.Professionalhigh-performancechipssuchasGPU,FPGA,andASICareusedtosupportalargenumberoffloating-pointandparallelcomputingrequirements.AlthoughtheimprovementofAItrainingalgorithmsreducesthedependenceonthescaleoftheintelligentcomputingclustertosomeextent,thecomputingpowerimprovementrateofsingle-chipstillcannotmeetthecomputingpowerrequirementsoftheincreasingnumberofparametersoflargemodeltraining.Thescaling-lawprincipleisstillapplicable,andthescaleoftheintelligentcomputingclusterisstillexpanding.

Atthesametime,theenhancementofmodelinferencecapabilitiesalsodrivesthedeploymentofinference-basedapplicationsinthefinancialindustry,andthedemandforcomputingresourcesinmodelinferenceisexpanding.Improvingcomputingefficiencyisthekeytointelligentcomputingclusterswithhighinvestment.

RoCEv2(RDMAoverConvergedEthernetVersion2)hasbecomethefirstchoiceforintelligentcomputingnetworks.Iteffectivelyreducesnetworkdelaybutissensitivetopacketloss,whichposeshigherrequirementsonintelligentcomputingnetworks,requiringlargebandwidth,lossless,stablelatency,andhighernetworkthroughputtoimprovecommunicationefficiency.

5.2.3Storage

Thedigitalizationofthefinancialindustrywillmakedatacentersfacehundredsofbillionsoftransactionsandpaymentoperationsperformedbytensofmillionsofusersthroughappseveryday.

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Thedigitalizationofthefinancialindustrywillmakedatacentersfacehundredsofbillionsoftransactionsandpaymentoperationsperformedbytensofmillionsofusersthroughappseveryday.Thisrequiresparallelandfastdataprocessingcapabilities.AstheinfrastructureofArtificialIntelligentapplicationsandservices,storagesystemsneedtoprovideover50GBbandwidthandover1millionIOPSperformance.Duetothematurityoftheflashtechnology,SDDsimprovestoragedensityandperformance,andgraduallyreducecosts.Therefore,SDDsgraduallyreplaceHDDsandgainwideapplication.TheNon-VolatileMemoryexpress(NVMe)providesanefficientcommunicationmechanismforSSDstofullyutilizetheperformanceadvantagesofSSDsandimproveread/writespeed,latency,andmore.

ThestoragenetworkthatworkswithSSDsandNVMealsoneedstosupporthigherperformanceandlosslessforwarding.TraditionalFCnetworksfacetechnicalbottlenecksofbandwidthgrowthandareseparatedfromotherareasofthedatacenter,whichcomplicatesO&M.Ethernethasagoodtechnicalaccumulationinlargebandwidthandlosslesstransmission,andhasacompletesupplychain.All-flashstorageandNoFstoragenetworkbasedonNVMeoverhigh-speedEthernetwillbethemaindevelopmentdirectionoffinancialdatacentersinthefuture.

5.2.4AIfornetwork

Themutualaccessrelationshipsbetweenonlinefinancialservicesarecomplex.Tocompleteaservice,multipleservicesystemmaybeinvolved.E2Ereal-timeawarenessofservicequalityandsegment-by-segmentdemarcationandvisualizationofdifferentservicesystemshavebeennewrequirementforvisualizedO&Moffinancialdatacenters.Withtheemergenceofdistributedandbigdataservices,theproportionofeast-westtrafficindatacentersincreases.Distributedtrafficispronetomicrobursts,whicharedifficulttodetectbytraditionalmonitoringmethods.Inaddition,thedistributedarchitectureandintelligentcomputingbringmultipledevices.Stableservicerunningrequiresthatpotentialnetworkriskscanbeidentifiedinadvanceandfaultscanbequicklylocated.ThisbringsnewchallengestonetworkO&M.

Toaddresstheprecedingchallenges,datacenterO&MisinurgentneedoftransformingfrommanualtraditionalO&MtointelligentnetworkO&M.Withthedevelopmentoftechnicalcapabilities,suchasTelemetrysecond-levelcollection,digitaltwin,knowledgegraph,AI,Co-pilot,andAgent,moreefficient,automated,andintelligentnetworkO&Mispossible.

5.3NetworkingEvolution

Tomeettheservicedevelopmentrequirementsbroughtbythedigitaltransformationofthefinancialindustry,multipledatacentersarerequiredtodeployservices.Inaddition,datasecurity

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andservicereliabilityandcontinuityareincreasinglyvalued.Backupanddisasterrecoveryarebecomingacommonrequirement.Multipledatacentersmustbeconstructedtosolvethedisasterrecoveryandbackupproblem.

Withthedevelopmentof5G,cloudcomputing,andbigdata,virtualizationandresourcepoolingbecomethemainstreamrequirements.Cross-regionandcross-DCresourcesneedtobeintegratedtoformaunifiedresourcepool.Inaddition,servicesystemsaredeployedinmultipleDCsinadistributedmannertoprovideservicesnearbytoimproveuserexperience.Distributedmultipledatacentersarethemainstreamsolutionnow.

Tomeetthecontinuousinnovationrequirementsoffinancialdatacenters,thedatacenterarchitecturemustbeflexible,scalable,andevolvable.Thedesignofthedatacenternetworkmustmeetthedevelopmentrequirementsofcomputing,storage,andlargedatacenters,takeintoaccountthetechnologyevolutioninacertainperiod,andsupporttheevolutionofdistributedandcloud-baseddatacenters.

5.3.1Multi-POD

MultiplePODsaredeployedinasingleDC.ProperservicePODdivisionimprovesthecomputingandstorageresourcepoolingandsharingcapabilities,andensuresthescalabilityoftheDCandtheelasticscalingcapabilityofeachPOD.DeploysecuritypoliciesbetweenPODstoimplementsecurityprotectionandfaultisolationatdifferentlayers.ServicescanbeflexiblybackedupandmigratedbetweenPODstoachieveloadbalancingandhighreliability.Tomeetthecontinuousimprovementofservicecapacityandperformanceinthefuture,thedatacentermustreserveappropriatebandwidthcapacityandreliableaccesssettings.

5.3.2Multi-DC

Withtheincreasingdigitalizationoffinancialservices,datacentershavehighsecurityandreliabilityrequirements.Datacentersmustcontinuouslyensurereliability,meettherequirementsfor7x24networkoperation,andmeettherequirementsforhighreliabilityofsystemsandapplicationsdeployedinthesameoracrossdatacenters.Therefore,datacenterconstructionmustsupportmulti-DCscenarios,including:

lIntra-cityactive-activeDCs

TwoservicesystemsrunningatthesametimearedeployedintwoDCsinthesamecity.Thesecuritypoliciesofthesamesubsystemarethesameandthesameservicesareprovided.Thisscenarioprovidesdoubleservicecapabilitiesandsupportsreal-timeDRandtakeoverofeach

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other.Fullredundancyisimplementedattheapplicationprocessinglayer,greatlyimprovingservicecontinuityandreliabilityandpreventingusersfromsensingfaults.

lGeo-RedundantDCs

TheremoteDRcenteristhebackupdatacenterofthetwoactivedatacentersinthesame-cityactive-activesolution.Itisusedtobackupdata,configurations,andservicesoftheactivedatacenter.Whenthemasteractive-activedatacentersarefaultyduetonaturaldisasters,theremotedisasterrecoverydatacentercanquicklyrecoverdataandapplicationstoensurenormalservicerunningandminimizelossescausedbydisasters.

5.4PolicyConstraints

Thefinancialindustryisofgreatsignificancetothecountryandplaysanimportantroleinpromotingeconomicdevelopment,optimizingresourceallocation,stabilizingtheeconomy,andpromotinginnovationandcooperation.Countrieshavealsoissuedcorrespondingpoliciestoensuretheconstructionofdatacentersinthefinancialindustry.Forexample,theintelligentO&Mmechanismforfinancialdatacentersshouldbeestablishedandimproved,andmulti-scenariocollaborationandmulti-sitesintegratedmanagementandcontrolshouldbestrengthenedtoimprovesiteawareness,exceptiondetection,andfaultpredictioncapabilitiesandreducemanualoperationrisks.

6FinancialDataCenterNetworkConstructionRoadmap

6.1SingleDCandmultiplePODs

6.1.1OverallArchitecture

AsingleDCisdividedintomultiplePODstocarrydifferentservices.PODsareconnectedbytheswitchingcorePOD,asshowninFigure2.

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Figure2—Single-DCnetworkconstructionarchitecture

6.1.2SwitchingcorePOD

TheswitchingcorePODisthecoreofthefinancialdatacenternetwork.ItconnectsallthefunctionalPODsinthedatacenterandworksastheswitchingbusofthedatacenter.

lCoredevicesaredeployedintheswitchingcorePODindependently.Thespine-leafarchitectureensuresthescalabilityoftheswitchingcorePODandallowsflexibleadditionordeletionoffunctionalPODs.

lThebandwidthoftheswitchingcorePODmustbescalableandreservedforfutureservicedevelopment.Currently,200G/400Gisthemainstream,and800Gisanewtrendinlargefinancialdatacenters.

lTheswitchingcorePODmustsupporttheestablishmentofaLayer3routingcontrolplanetoensurenetworkreliabilitythroughfastconvergenceofstandardroutingprotocols.

6.1.3IntelligentcomputingPOD

AnintelligentcomputingPODisapartitionthatperformsAImodeltraining.Itisusuallydividedintothreeplanes:serviceplane,parameterplane,andmanagementplane,asshowninFigure3.

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Figure3—IntelligentcomputingPODnetworkconstructionarchitecture

InintelligentcomputingPOD,thecommunicationefficiencybetweenGPUsiscritical.RDMAiswidelyusedfordatatransmissionandmemoryaccess,andtheIntelligentcomputingnetworksareusuallyconstructedbasedontheRoCEv2protocol.RoCEv2-basedAItrainingissensitivetonetworktransmissionindicatorssuchasnetworkdelay,packetloss,andjitter.Thepacketlossrateof1per10,000decreasesthetrainingefficiencyby50%.RoCEv2doesnotprovideacomprehensivepacketlossprotectionmechanism.Toimprovethecomputingpoweravailabilityofintelligentcomputingclusters,high-performance,large-bandwidth,andlosslessnetworkarerequired.TherequirementsforbuildinganintelligentcomputingPODareasfollows:

lThescaleofintelligentcomputingPODscanbeflexiblyadjustedbasedonservicerequirements.Highnetworkavailabilityandscalabilityarerequired.TheCLOSspine-leafarchitectureisused.

lThenetworkbandwidthofintelligentcomputingPODsisincreasingdrivenbytheincreasingofAImodelscalesandGPUbandwidth.Currently,200G/400Gisthemainstream,and800GisanewtrendinordertosupportlargescaleAItraining.

lAnon-blockingnetworkinintelligentcomputingPODsisneeded.TraditionalECMPisinsufficienttosupportlosslessnetworktransmission.Moreefficientloadbalancingisrequiredtosteeringasmallnumberofhigh-bandwidthAIflows.Additionally,moreefficientflowcontrolandcongresscontrolareneeded.

lThecomplexityofnetworkoperationandmanagementintheintelligentcomputingPODiscreasingwiththenetworkscale.It’srequiredtoprovideRDMA-basedvisualizationinordertosimplifyandshortenthefaultdetectionandanalysistime.

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Thekeytechnologiesofintelligentcomputingnetworksareasfollows:

PFCPriorityFlowControl

PFCdeadlockmonitoring

PFCDeadlockPrevention

ECN

Networkscaleloadbalancing

RDMA-BasedVisualizedO&M

6.1.4BigdataPOD

ThebigdataPODisusedtoprocesslarge-scaledistributeddatacomputingtasks.ThebigdataPODinthefinancialindustrydatacenterisusedtocalculateandanalyzecustomerinformation,includingfinancialbehavior,preference,andriskanalysisforaccountopening,transaction,andtransfer.Itcanalsobeusedtocalculateandanalyzefinancialorganizationinformation,suchasbusinessprocessingprocessimprovementpoints,resourceallocationoptimization,andfinancialdata.Figure4s