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T I A D
Copyright©2016SplunkInc.
ContinuousIntegrationmeasured& controlledStéphaneLapiePresalesEngineer,Splunk Inc.
listentoyourdata®
T I A D
Presenters
2
StéphaneLapiePresalesEngineer– 2YearsatSplunkBasedinParis,FranceSpecializedinAppDelivery,ITOpsandCloudWentfromDev,toOpstoPresales(formercolleagueofAdegbenga atBNPParibas)
Adegbenga AmusaHPCDeveloper– BNPParibas,RiskSystemsBasedinLondon,UnitedKingdomWorkedonGridComputingforthepast10yearsHadafairshareofOpsinmycareer
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OnceUponaTimeinaFinancialInstitution…
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Service
AGroupofPeoplewasWorkingonEnhancingSome…
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• Requirements• ServiceDefinition
• Implementation• Validation&Testing
• ApplicationMonitoring• IncidentManagement
Business
Development
Operations Service
Customers
AndLikeManyServicesThereWere…
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Service
ThisGroupofPeopleWasBoundtoTransformtheService
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RiskCalculation
BusinessAnalysts
Java,C++,Cuda
Developers
ApplicationSupport
RiskSystems
StructurersRiskAnalystsQuantAnalystsDataAnalysts
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RiskCalculationCounterpartyRisk
A B
• ManySimulations• ManyParameters• ManyRegulations• …maybeslowtocalculate
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RiskCalculation
• Fresh information
• Accurateinformation
• CompliancewithMarketRegulations
• Fullyparametrizedon-demand simulations
• Longtermsimulations
• Quickresults(understandinstant)
• Easeofuse!!!
• Integratedwiththemanyothersystems
HighCustomerExpectationsStructurersRiskAnalystsQuantAnalystsDataAnalysts
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ANewProjectWasBorn
10
Goal:RebuildtheCalculationEnginetousehighlyparallelcomputingonGraphicalProcessingUnits
• MuchQuickerCalculations
• MuchMoreSimulationsCapabilities
• EasierModelsImplementation
• ReduceHardwareandMiddlewarecost
ProjectCodename:
HPCEHighPerformanceComputeEngine
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ANewProjectWasBorn
11
GPU/SIMTCPU/SMT
Complexanddifferenttasks
Notsocomplexscalabletasks
fewvery-smartcoresmanycheapercores
CPUvGPUinanutshell
T I A D12
CPUvGPUinanutshell
MonteCarloMethods
SimulationtocalculateValueatRisk
ParallelCalculatio
ns
ANewProjectWasBorn
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Project’sTimeline
13
FromZerotoHero…
Q2 Q2
Dev Production
2013 2014+
1. FullyIntegrated
2. FullyFunctional
3. IdenticalResultstoLegacy
T I A D
Project’s Timeline
14
FromZerotoHero…
Q2 Q2
Dev Production
2013 2014+
DevOps…totherescue!
FastForward◉
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Project’sTimeline
15
FromZerotoHero…
Q2 Q2
Dev Production
2013 2014+
FastForward◉
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Development AppSupport
16
DEV UAT STG PRDTEST TEST TEST
Automation
End-to-EndVisibility
VersionXYZ
VersionXYZ
Version1.0Version2.0
Version3.0.1
Version3.0.1.1
Version4.2.0.1
Business
TEST TEST TESTTEST TEST TESTTEST TEST TEST
DeliveryPipelineOverview
T I A D
Step#1
17
OpenAccesstoEnvironment’sData
T I A D
WhatisDelivered
18
High Performance Compute Engine
Non-persistent Data
PersistentData
Compute FarmREST
Services
GPUServers
CPUServers
ApacheCassandra
+SybaseIQ
+(FileSystem)
OracleCoherence
+DataServices
IBMPlatformSymphony
+CalculationServices
ApacheTomcat
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Step#2
19
Createindicatorsforeachsoftwarecomponents,oneafteranother…
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ConsistentandReusableAnalytics
20
Business AppSupport Development
HPCE
Non-persistent Data
PersistentData
Compute Farm
RESTServices
DEV/UATSTAGINGPRODUCTION
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Step#3
21
Makeitrepeatabletoimproveprogressively!
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IntegrationwithinRiskSystems
22
Non-persistent Data
PersistentData
Compute Farm
HPCERESTServices
RiskData Bus
Upstream Systems
Downstream Systems
RiskNavigator
RiskData
Warehouse
DataIn/Out
SimulationsRequests
ResultsBrowsing
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IntegrationwithinRiskSystems
23
Non-persistent Data
PersistentData
Compute Farm
HPCERESTServices
RiskData Bus
Upstream Systems
Downstream Systems
RiskNavigator
RiskData
Warehouse
DataIn/Out
SimulationsRequests
ResultsBrowsing
End-to-EndVisibility
Business
AppSupport
Development
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Step#4
24
Increasethescopetogetclosertothe“fullpicture”
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DataSourcesOverview
VersionControl
QA/TestingTools
CM/DeploymentCI/BuildAutomation
23
Applications&Systemslogs
CUSTOMLOGGING
Business AppSupport Development
T I A D26
Visualize ShareAnalyzeExplore
Schema-Freedatacollection& storage
CodeRepository
QA/TestingTools
CM/DeploymentCI/BuildAutomation
ApplicationsMonitoring
Project&IssueTracking
SystemsMonitoring
DistributedStorage&Processing
ScalestoTBs/day
=DatageneratedbyITSystems
MachineData
DataSourcesOverview
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DashboardsWalkthrough
T I A D29
Compute Farm
CPUServers
GPUServers
Non-persistent Data
PersistentData
High Performance Compute Engine
RESTServices
ServiceRequestsDevelopment
Requests/Responses
T I A D30
Development
T I A D31
Development
T I A D32
Compute Farm
CPUServers
GPUServers
High Performance Compute Engine
RESTServices
Non-persistent Data
PersistentData
DataIn andOutBusiness
AppSupport
Development
RiskData Bus
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Business
AppSupport
T I A D35
Business
AppSupport
T I A D35
AppSupport
Development
T I A D36
AppSupport
Development
T I A D37
Business
AppSupport
Development
T I A D39
Business
AppSupport
Development
T I A D39
PersistentData
Non-persistent Data
High Performance Compute Engine
Compute Farm
CPUServers
GPUServers
RESTServices
CalculationsAnalysis Business
AppSupport
Development
T I A D40
AppSupport
Development
T I A D41
Business
AppSupport
Development
T I A D42
Development
T I A D43
AppSupport
Development
T I A D44
AppSupport
Development
T I A D45
Business
Development
T I A D46
Business
Development
T I A D47
High Performance Compute Engine
PersistentData
Non-persistent Data
Compute Farm
CPUServers
GPUServers
RESTServices
InfrastructureAppSupport
Development
T I A D48
AppSupport
Development
T I A D49
AppSupport
Development
T I A D50
AppSupport
Development
T I A D51
AppSupport
Development
T I A D52
AppSupport
Development
T I A D53
AppSupport
Development
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AppSupport
Development
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Wrap-up
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KeyTakeAway
56
1. Don’twithholdinformation,openaccesstoeveryone(%sensitiveness).Shareyourthoughtsandanalysiswiththeotherteams.
2. TaketimetodefineIndicatorsthatmatters.RepeattheoperationwithDev,OpsandBizpeople.
3. Mostanalysisshouldbeconsistentandrepeatable.EventuallyfromtheDevcomputer’tilProductionplatform(containerscanhelpnowadays).
4. Don’trushandtrydoeverythingatonce.You’llgettherequicklyenoughifyoustreamlineyourefforts.
T I A D
LessonsLearned
57
Ø Todaywemanagedtogetan“Holistic”viewofoursystemsandwecan’timagineworkingwithoutasolutionlikeSplunk.WedidallthisveryquicklywithSplunk andinmuchmoredepththanpreviouslydevelopingcustomtools.
Ø Inthepastmostlogswereconsidered“garbage”butmadeaccessibletheyrevealedmanyUserBehaviorswedidn’texpect.Itisoftremendousvaluetounderstandwhatcustomersdo,whichfeaturestheyuseandhow.Thiskindofanalysiscantriggerchangesinthesolution.WestartedtoputLoggingBestPracticesinplacetomakesurethe“garbage”canbe“recycled”;)
Ø EverybodywithinRiskSystemsisusingSplunk forad-hocsearchesandsharingsearchlinksbutveryfewpeopleshareDashboardsandReportstoday.Goingforwardwe’dliketoenablemorepeopleandmakesuretheycancollaborateonimprovingourinternalSplunk Apps.
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Merci!