Actionable KPIs + Analytics for Network Performance Visibility
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Transcript of Actionable KPIs + Analytics for Network Performance Visibility
2 ©2015ACCEDIANNETWORKSCompanyConfidential
“TheEvolutionofInsight”
INFORMATIONISPOWER
Newlevelsofvisibilityareemergingthatredefinewhatserviceproviderscansee,to…• DetectandisolateQoS&QoEissueswithexceptionalspeed• DiscoverunexpectedrelationshipsandtrendsbetweenKPIs• Uncover‘ghosts’inthenetwork:detect‘invisibile’QoEimpairments• Correlatemetricstoisolaterootcause;amplifywithBigData&Analytics
“Theevolutionofinsight”
Granular,precisevisibilitycombinedwithanalyticsdramaticallyincreasesresolvingpower
WhyNow?• Networksarebecomingexceptionallycomplex needbettertools
• Interdependenciesbetweenmetricscausesnewformsofinstability
needdeeperanalysis
• Shorttermeventsmakinglargerimpact needfasterdata
• Analytics&BigDatahitmainstream newlevelsofinsightnowaccessible
DelivertheBestUserExperience
3 ©2015ACCEDIANNETWORKSCompanyConfidential
Inaccurate,incomplete,
infrequentdataofferslittleinsight.
Analyticsamplifiesthelimitationsof
poordata.
BUILDINGANACTIONABLEINSIGHTDATASOURCE “Deepinsightisenabledbyhigh-qualitydata,anddiverseKPIs”
Percentiles
QoEScores
SampleMetrics
Min-Max-Mean&σ
OOO,Lost,LostBurst
KPISignificanceReportedPrecision,
SampleSize
VoIP/VoLTEMOS,R
Addressingoutliers
Define‘Normal’&CatchExceptions
Perspectives Statistics&KPIs
AnyFlow
Sub-SecondSampling
Measurements
Speed
Precision
Focus
µSecResolution
AnyLocation
AnySegment
1-WayMetrics
Granularity
APrecise,CompleteFoundationforInsight&Analytics
4 ©2015ACCEDIANNETWORKSCompanyConfidential
OptimizeQoE
“Instrumentingallkeypointsalongtheservicepath.”
IdentifyIssues
LocateSource
Standards-BasedNEPMReflectors
TestPoints
VirtualPMProbe(Actuator)
CSR
Access
AggregationTransport
Core
End-to-End
Virtual&Physical
PMAgent/VNF
NFVI
TakeAction
VIRTUALIZEDINSTRUMENTATION● COMPLETEVISIBILITY
5 ©2015ACCEDIANNETWORKSCompanyConfidential
EXAMPLE:LOCATION&VoLTEQoE
LosslessRelay
RAN /Backhaul
EPC
IAM_ __LEAVINGWITHOUTYOU!
IAMNOT LEAVINGWITHOUTYOU!
FlowBROKER™RemoteCapture
BrokeredFlows
DecodetheReal-UserExperienceUsingDPI
Simulate&MonitorNetworkQoS&TrendVoLTEQoE
CentralizedVantagePoint DistributedVantagePoint CallCanDegradeAlongtheTransmissionPath
S-GW
Analyzer
6 ©2015ACCEDIANNETWORKSCompanyConfidential
EXAMPLE:LOCATION&VIDEOQoE
HeadEnd
VideoAnalyzer
BasicQoS
SeetheCompletePicture● OptimizeQoE● AccelerateProblemResolution
VideoMOS
VideoPlayback
Central
QoELimitedtohead-endvisibility
CoarseQoSmetricsslowMTTR
Head-EndCapturedFlows
HeadEnd
Real-TimeQoS
Central Access
QoE&KPIs
VideoPlayback VideoPlayback
RealTimeQoS&QoE
CentralizedVideoAnalyzer
Central Remote
VisibilityExtendedtoanyLocation
Real-Time&1-WayMetrics
PerceptiveandNetwork-BasedQoE
End-to-End
SetTop
QoE&KPIs
15min
1sec
vs.
Timeto
Insight“Slow”
7 ©2015ACCEDIANNETWORKSCompanyConfidential
0"
50"
100"
150"
200"
250"
300"
5" 10" 15" 20" 25" 30" 35" 40" 45" 50" 55" 60"
Mbp
s%
Transac+on%Group%Total%
CIR"
Total"5"s"Sampling"
5SEC
MeasureEvery
0"50"100"150"200"250"300"350"400"
1" 3" 5" 7" 9"11"13"15"17"19"21"23"25"27"29"31"33"35"37"39"41"43"45"47"49"51"53"55"57"59"
Mbp
s%
Transac+on%Group%Total%
CIR"
Total"1"s"Sampling"
1SEC
LossMeasureEvery
0"100"200"300"400"500"600"700"
1" 4" 7" 10"13"16"19"22"25"28"31"34"37"40"43"46"49"52"55"58"
Mbp
s%
Transac+on%Group%Total%CIR"
Total"Flowmeter"MIN"
Total"Flowmeter"MAX"
Total"Flowmeter"AVG"
0.1SEC
max
avgmin
MeasureEvery
0"
50"
100"
150"
200"
250"
300"
5" 10" 15" 20" 25" 30" 35" 40" 45" 50" 55" 60"
Mbp
s%Transac+on%Group%Total%
CIR"
Total"5"s"Sampling"
0"
50"
100"
150"
200"
250"
300"
0" 15" 30" 45" 60"
Axis%Title%
Transac.on%Group%Total%
CIR"
Total"15"s"Sampling"
15SEC
LinkCapacity
Utilization
MeasureEvery
ANEWLEVELOFINSIGHT● SAMPLINGSPEED “EffectsofSamplingFrequency• SameDataSet”
NoProblem
BigProblem
SmallProblem
NoProblem
IncreasingSamplingSpeed&AddingStatisticalPerspectivesChangesEverything
8 ©2015ACCEDIANNETWORKSCompanyConfidential
EXAMPLE:MICROBURSTSHITMOBILEBACKHAUL “Chattyapplications,inter-cellsignalingcreate‘loss-bursts’thatcanteardowncalls,anddisruptservice”
AverageUtilization
20%
CapacityLimit– anythingbeyond1GbE=lostpackets
“EverythingSeemsFine” Reality: PoorUserExperience
Granular,PreciseMonitoringisCrucialtoDeliveringExceptionalQoE
*theH.264ConstrainedBaselineProfile(CBP)performancetargetsincludeaPLRoflessthan0.1percent– correspondingtoavisibleerrornomorethanonceevery20seconds
Loss>0.1%addsnoticeabledistortiontovideo*
1-msMicro-Bursts:1packetlostoutof1,000=5%LessThroughputplusImpacttoQoE
9 ©2015ACCEDIANNETWORKSCompanyConfidential
250
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100
50 50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
ANEWLEVELOFINSIGHT● PRECISION “Tier-1NationalNetwork,Asia”
Time(sec)
UEThrou
ghpu
t(Mbp
s)
Delay(m
icrosecond
s)
PacketLossTHROUGHPUT
Precision&SamplingSpeedRevealMulti-MetricCorrelation
VSLATENCY*
*AsMeasuredfromEPCtoeNodeB
10 ©2015ACCEDIANNETWORKSCompanyConfidential
NEWINTERDEPENDENCIESEMERGE“LTE-Advanced,LTE-AdvancedPro,5GIntroduceGreaterNeedtoPreciselyMonitorQoS.”
1
UserE
xperience
OntheLine
15ms
50%
Increased Delay DropInThroughput
2%
80%
Increased Loss DropInThroughput
0%
100%
Throughp
ut
2%1%0.5% 1½%
20%
PacketLoss
0.1%
Source:SKTelecom,LTE-ANetwork(production)Source:“CentralizedSchedulingforJoint-TransmissionCoordinatedMulti-PointinLTE-Advanced”,
S.Brueck,L.Zhao,J.Giese,M.A.Awais,proc.ITG/IEEWorkshoponSmartAntennas,Bremen(WSA'10)
80%↓50%↓40%↓5%↓
11 ©2015ACCEDIANNETWORKSCompanyConfidential
ANALYTICSAMPLIFYINGINSIGHT● CORRELATION
20billion
BigDataRecords
<2seconds
ComputeTime
“Mass”CallFailuresEvery14MinutesreflectedinQoEscore
“NetworkBehavingNormally”KPIswithinthreshold…inisolation
but
ApplyAnalytics Correlateswithrouter
firmwareversion
Correlations
ActionUpgradeRouter
MOS&PacketLoss• Loss&‘LostBurstMax’
Lossisoccurringin100msmicro-outages
MOS&MaxDelay: delayspikes
• Likely:RingSwitchIssue(>50ms)
TimetoRootCause
10min
Tier-1MobileNetworkExample
12 ©2015ACCEDIANNETWORKSCompanyConfidential
ANEWLEVELOFINSIGHT● CORRELATEDMETRICS
“Mass”CallFailuresEvery14MinutesreflectedinQoEscore
“Whatlooksinnocentmaybeonepartofabiggerproblem”20:10
20:20
20:30
20:40
20:50
21:00
21:10
21:20
21:30
21:40
21:50
22:00
22:00
22:10
22:20
22:30
VoLTEQoE(MOS)
4
5
3
2
1
0
“NetworkBehavingNormally”
Tier-1MobileNetworkExample
PacketLoss
0
Delay (ms)2502.5%
2.0%
1.5%
1.0%
0.5%
0
200
150
100
50
Threshold Threshold
but
atHighResolution,BothMetricsCorrelateWithFault
PacketLoss
0.20%
0.18%
Delay
0
[ms]
2
4
6
8
5testpacketslostconsecutively:100%lossin100ms– allcallsdropped
13 ©2015ACCEDIANNETWORKSCompanyConfidential
EPC VCXVCX
CSRBackhaulRings
VIRTUALPERFORMANCEASSURANCE&BIGDATAANALYTICSINTEGRATION “Tier-1Deployment:MaintainImpeccableQoS&QoEatCloud-Scale:100,000’sofeNodeBs,100M’sofmetrics/day”
Standards-BasedNEPMReflectors
PerformancePlatform
DC
Avirtualizedinstrumentationlayer formulti-vendor,multi-technologynetworks
SkyLIGHTDirector
Controller/Probe
BigDataDB(e.g. HDFS)
StreamingQueue
(e.g.Kafka)
InMemory(e.g.Spark)
Visualize
AGR
AggregationLevel3
AGR
AggregationLevel 2Rings
AGR
AGR
AggregationLevel 1Rings
AGR
AGRCSR
Real-TimeAnalytics
Correlate Predict
VCX
Multi-Service SegmentedEnd-to-End
TestPoints
VCX
VCX
EPC
EPC
EPC
…20+times
…Upto15xUpto10x ~5x
Tier-1LTENetwork:• 20+EPC• Eachserving~5,000
eNodeB• EacheNodeB&CSR
monitored:8.7MPMrecords/day(17.4Mtotal)
• 51KPIs/PMrecord• ~1BKPIs/day/EPC• ~20BKPIs/day
EPC
NationalTransport
SDNController&NFVO,NMS/OSS
14 ©2015ACCEDIANNETWORKSCompanyConfidential
INSIGHTIMPROVINGQoE● ACTIONSFROMANALYTICS “Tier-1LTEOperator:networkimprovementsresultingfrom1monthofmonitoring”
ActionstoimprovequalityofLTEbroadband&VoLTE
Type Impairments Action ResultSubscribersAffected
HardwareDefect
Delay,Jitter,Loss ↑ Replace SFP Improvedvoice quality,reducedcall
dropsinaffectedcell 100’s
SystemOverload
Delay,Jitter,Loss↑
Addsmallcellstomacro
ImprovedVoLTE connectivity,callsetuptime&QoE,broadband
throughputandlatency10,000’s
SoftwareDefect
Excessive DelayWithoutAlarm
Replace 10GRouter
Improved throughput inurbanareaservedbymultipleeNodeBsby35% 100,000’s
NetworkCongestion
Loss↑,Throughput↓
Change queuesize(routerCBS) Improvedcarrier aggregation
efficiency:improvedmetroregionthroughputby25%
100,000’sLoss↑ Increasebackhaul
capacity
TopologyDefect Delay>10ms Divide bigring
intosmallerrings 30%+improvementinthroughput 1,000,000’s
FullyVirtualisedEPCwithCloudRAN
VirtualisedInstrumentation
500thousand
1Trillion
NetworkWideAnalytics
DIRECTIMPACT
MoreNetwork
$0 CapEx30 Days
15 ©2015ACCEDIANNETWORKSCompanyConfidential
THEVALUEOFANALYTICS CorrelatingKPIs
• Acceleratetroubleshootingwithguidedinsight• IdentifycombinationsofvariablesthatdirectlyaffectQoE uncovernetworkspecificbehavior— sometimescounterintuitive• Buildawatchlistofmostimpactingconditions reducealarmfatigue:focusonknown‘repeatoffenders’
PredictiveAnalytics• Trend&interpolatecorrelatedKPIstotriggerproactiveaction• Anticipatefailure:identify‘most-likely’impairments&estimatesubscriberimpact
• Useinsighttofocusonbuildingabetteruserexperience networkupgrades,optimization,prevention
MachineLearning• Recordthesuccessrateandresultofanyservicechange,networkreconfigurationorcorrectiveaction
• Learnwhichactionsleadtodesiredresults,overtime• Automatecorrectiveactions,insurewithimmediatefeedback
“Learnhowyournetworkreallyworks.”
StrengthofCorrelation
Time
PacketLoss
Time
Loss&Throughput
Latency&Throughput
Latency
FOCUS
16 ©2015ACCEDIANNETWORKSCompanyConfidential
Correlate Predict
Analytics Significance
Perspectives DiversityofMetrics:Viewpoints
ACHIEVINGANEWLEVELOFINSIGHT● ASOLIDFOUNDATION
Deepinsightisn’tpossiblewithbesteffort,‘goodenough’data.
“InformationisPower”
AnyFlow
Sub-SecondSampling
Accuracy,Granularity,Recency
Speed
Precision
Focus
µSecResolution
AnyLocation
AnySegment
1-WayMetrics
Measurements
Eachincreaseinvisibilityisbuiltontheprevious.
Highresolutionmonitoringformsafoundationforexceptionalinsight.
“Theintegrationofthebestmetrics,broadstatisticsandreal-timebig-dataanalyticsistheultimatetoolforoperators”
17 ©2015ACCEDIANNETWORKSCompanyConfidential
“Bringingintelligencetonetworks”
ACCEDIAN’SACTIONABLEINSIGHTARCHITECTURE
VCX
VCXVCX
VCX
“Fromthemostprecisemetrics,tothemostversatileservicedelivery,toanalyticsintegration”
BigDataDB(e.g. HDFS)
StreamingQueue
(e.g.Flume/Kafka)
InMemoryProcessingVisualize Real-Time
Analytics
Correlate Predict
SDNController&NFVO,NMS/OSS
CollectEnforceCondition
MeasureCreateKPIs
OpenInterfaces
ProviderSystems CompleteCoverage
• UbiquitousInstrumentationLayer• PhysicalandVirtualEndpoints• Alllayers:QoS&QoE
SeamlessIntegration• Openinterfacesto… B/OSS/NMS/SDNControl/NFVO Big&In-MemoryDataStructures AnalyticsEngines
UltimateVisibility• ActionableMetricsinReal-Time• Mostgranular&precise• Segmented&end-to-end
RAMCloud
(e.g.Spark)
18 ©2015ACCEDIANNETWORKSCompanyConfidential
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