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The Languages of Capacity Planning:Business, Infrastructure & FacilitiesAmy Spellmann; St. Louis CMG 4/19/16

The Languages of Capacity Planning:Business, Infrastructure & FacilitiesAmy SpellmannRichard Gimarc- amy.spellmann@451research.com- richard.gimarc@ca.com 2015 The 451 Group and CA Technologies. All rights reserved.November 5, 2015CMG 2015Session 511

The Languages of Capacity PlanningThe ChallengeCapacity Planning Stack Multi-level hierarchy Demand ( ) Feedback ( ) Efficiency Metrics ( ) Supports all elements of today's DigitalInfrastructure Implementation is straightforward &transparentBusiness Transactions per DI DollarCloud Migration7 ,0006 ,0005 ,0004 ,0003 ,0002 ,0001 ,0000123456789 1 0 11 1 2 13 1 4 15 16 17 18 19 20 21 22 23 24MonthBiz Trans per Month per DI Do llarApp & SS Transactions per CPU FootprintOn Premise201816141210864201234567891 0 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Tra nsaction s pe r CPU Footprin tShare d Services Transactio ns per CPU Footp rintApp & SS Transactions per CPU FootprintOn Premise201816141210864201234567891 0 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Tra nsaction s pe r CPU Footprin tShare d Services Transactio ns per CPU Footp rintCPU Footprint: Available vs. UsedOn Premise3 ,0002 ,5002 ,0001 ,5001 ,0005000123456789 1 0 11 1 2 13 1 4 15 16 17 18 19 20 21 22 23 24MonthTo tal CPU Foot print UsedTotal CPU Foot print Availa bleEstimated Power Usage per Month (kWh)On Premise8,0 007,0 006,0 005,0 004,0 003,0 002,0 001,0 000123456789 1 0 11 1 2 13 14 15 16 17 18 19 20 21 22 23 24MonthDat abasePowe r Used (kWh)Web AppPower Used (kWh )Power LimitChallenge: Formulate & communicate demand How does Application talk to Business? How do Infrastructure planners talk to Facilities planners?3

The Languages of Capacity PlanningOur ApproachBusiness Transactions per DI DollarCloud Migration7 ,0006 ,0005 ,0004 ,0003 ,0002 ,0001 ,00001 Understand demandRevive the notion of NaturalForecasting Units (NFU)Use NFUs to express demandApply this approach to a variety ofexecution environments23456789 1 0 11 1 2 13 1 4 15 16 17 18 19 20 21 22 23 24MonthBiz Trans per Month per DI Do llarApp & SS Transactions per CPU FootprintOn Premise201816141210864201234567891 0 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Tra nsaction s pe r CPU Footprin tShare d Services Transactio ns per CPU Footp rintApp & SS Transactions per CPU FootprintOn Premise201816141210864201234567891 0 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Tra nsaction s pe r CPU Footprin tShare d Services Transactio ns per CPU Footp rintCPU Footprint: Available vs. UsedOn Premise3 ,0002 ,5002 ,0001 ,5001 ,0005000123456789 1 0 11 1 2 13 1 4 15 16 17 18 19 20 21 22 23 24MonthTo tal CPU Foot print UsedTotal CPU Foot print Availa bleEstimated Power Usage per Month (kWh)On Premise8,0 007,0 006,0 005,0 004,0 003,0 002,0 001,0 000123456789 1 0 11 1 2 13 14 15 16 17 18 19 20 21 22 23 24MonthDat abasePowe r Used (kWh)Web AppPower Used (kWh )Power Limit4

A Bit of History2013We presented the CapacityPlanning Stack as a new way toview, analyze & communicateDigital Infrastructure capacityBusiness Transactions per DI DollarCloud Migration7 ,0006 ,0005 ,0004 ,0003 ,0002 ,0001 ,0000123456789 1 0 11 1 2 13 1 4 15 16 17 18 19 20 21 22 23 24MonthBiz Trans per Month per DI Do llarApp & SS Transactions per CPU FootprintOn Premise2018161412108642012014We presented a taxonomy thatorganizes the metrics supportingthe Stack234567891 0 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Tra nsaction s pe r CPU Footprin tShare d Services Transactio ns per CPU Footp rintApp & SS Transactions per CPU FootprintOn Premise201816141210864201234567891 0 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Tra nsaction s pe r CPU Footprin tShare d Services Transactio ns per CPU Footp rintCPU Footprint: Available vs. UsedOn Premise3 ,0002 ,5002 ,000Today The Language of Capacityplanning; utilizing the Stack todescribe communication betweenthe levels of the Stack for anyservice delivery model1 ,5001 ,0005000123456789 1 0 11 1 2 13 1 4 15 16 17 18 19 20 21 22 23 24MonthTo tal CPU Foot print UsedTotal CPU Foot print Availa bleEstimated Power Usage per Month (kWh)On Premise8,0 007,0 006,0 005,0 004,0 003,0 002,0 001,0 000123456789 1 0 11 1 2 13 14 15 16 17 18 19 20 21 22 23 24MonthDat abasePowe r Used (kWh)Web AppPower Used (kWh )Power Limit5

The Capacity Planning Stack6

Demand & FeedbackDemand ( )- Volume & priorities- Logical resourcerequirementsFeedback ( )- Performancerequirements & SLAs- Cost- BudgetDemand ( )- Total time tosatisfy- Physical resourcefootprint & instances- Expectedperformance- Performancerequirements &SLAs- Budget7

A Revolutionary Approachto Capacity PlanningBusiness Transactions per DI DollarCloud 6789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24MonthBiz Trans per Month per DI DollarApp & SS Transactions per CPU FootprintOn Premise20The Capacity Planning Stack- a revolutionary approach tocapacity planning thatsimplifies, structures andfocuses the practice.181614121086420123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Transactions per CPU FootprintShared Services Transactions per CPU FootprintApp & SS Transactions per CPU FootprintOn Premise20181614121086420123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24MonthApplication Transactions per CPU FootprintShared Services Transactions per CPU FootprintCPU Footprint: Available vs. UsedOn Premise3,0002,5002,0001,5001,0005000123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24MonthTotal CPU Footprint UsedTotal CPU Footprint AvailableEstimated Power Usage per Month (kWh)On 3456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24MonthDatabasePower Used (kWh)Web AppPower Used (kWh)Power Limit8

The Capacity Planning Stack Taxonomy9

Benefits of the Stack Taxonomy Provides a structured approach to evaluating today’s DigitalInfrastructureSimplifies & guides the selection of metrics required to supportdecision makingEquips the capacity planner with a structured way to think about,organize, communicate and collect the metrics that apply to thedecision support processPaves the way for federated capacity planning across today’s DigitalInfrastructure10

Planning HorizonsBusinessBusiness planning horizons are generally in the range of 6 months to 1 year.Factors that influence their planning horizon include: New application deploymentApplication Seasonal fluctuations (e.g., Black Friday and Cyber Monday) Acquisitions and mergers Organic workload growthThe Application planning horizon is generally in the 3 to 6 month range.Factors that influence their horizon include: New application rollout InfrastructureDevOps Organic workload growth for existing applicationsInfrastructure planning horizon is also in the 3 to 6 month range.Although the Infrastructure and Application levels have similar planning horizons,the factors that drive them are different. The factors that drive the Infrastructureplanning horizon include the following: Technology refreshFacilities Application support Capacity demand Procurement timelinesFacilities planning horizons are in the range of 5 to 10 years.Since they are concerned with the hosting data center they want to plan for as fewchanges as possible because change is expensive and time consuming. Changesto support additional power, space and cooling are not small or incremental; that isthe primary reason for their long-term view.A consequence is that Facilities generally builds in more room for growth than theother Stack levels.

Business metric that can be related to the use of computer system resources (e.g., CPU, I/O,memory, network traffic) Examples: Number of accounts, customers, loans, hotel beds, cars manufactured, product orders,insurance contracts, nk business plansto IT PlanningModels &Scenarios12

NFUs & the Stack Each Stack level has its own notion of a Natural Forecasting Unit NFU demand is passed down the Stack from level to level.NFU Demand Factors ( )BusinessApplicationNFU:Task:NFU:Infrastructure Task:NFU:FacilitiesTask:NFU:Business volumetrics (e.g., number of loans)Translate Business NFU to applicationarchitecture & metricsApplication resource footprint and instancecount (logical resources such as VMs, JVMsand threads)Translate Application NFU into physicalInfrastructure requirementsPhysical hardware requirements (e.g., servers,storage and network)Translate Infrastructure NFU into Facilitiesspace, power & tureFacilitiesPower draw, space & cooling requirements13

NFU - ExamplesMortgage company Number of existing loans Number of new loansBankChallenge–How do you transform an NFUinto computer systemresource usage? Number of accounts Number of customers using electronicbill paymentHow much CPU, I/O, etc. arerequired to:Insurance company Service an existing home loan Number of current insurance contracts Create a new loan Number of claims per month Generate monthly statementHotel chain Process a customer claim Number of hotels & beds Register a new guest Number of registered guests Generate bill for checkout14

ExternalPublic l Public Cloud:Servers and storage ondemand(AWS, Rackspace)Private Cloud:We own(or pretend we own) the serversand storage (Cloudstack, OpenStack,hosted private cloud)Hybrid:Private and public resources managedtogether as needed (RightScale, Dell)SaaS:Applications on demand(Salesforce, Google Docs)15

451 Research Best Execution Venue Thought Leadership

For each of the following categories of workload/business functions, what is yourprimary deployment method likely to be in the next two years (internal private cloud,external public cloud, hybrid cloud, or SaaS)?17

18

TraditionalIn-HouseBusinessDemand NFU Demand ( )o Business to Application- Business volumetricso Application to Infrastructure- Resource footprint & instance count- Logical resourcesFeedbackApplicationInfrastructureo Infrastructure to Facilities- Physical hardware requirements Feedbacko Describe what will be implemented to satisfy the demand at eachlevelFacilities Budget ( ) & Cost ( )On-Premise Digital InfrastructureNFUs & Communication/Language19

Hosted In-House BusinessDemandInternal is identical to the traditionalOn-Premise modelExternal communication of demandto hosting providero Hardware requirementsFeedbacko Feedback is cost based on space, powerApplicationand cooling at the provider’s cilitiesAdd External Infrastructure &FacilitiesNFUs & Communication/Language20

IaaS In-House BusinessDemandFeedbackInternal is identical to the traditionalmodelExternal communication of demandto IasS providero In-house Infrastructure to Cloud ProviderApplicationIaaSProvidero Physical hardware requirementso Feedback is cost based on instance usage& type, storage and network itiesIaaS can be Public or Private CloudNFUs & Communication/Language21

PaaSIn-House Business DemandFeedbacko Application to PaaS nal is identical to thetraditional modelExternal communication ofdemand to PaaS providerInfrastructureo Resource footprint & instance counto Logical resourceso Primary use is developmento Feedback is cost based on instanceusage & type, storage and networkactualsFacilitiesFacilitiesPaaS can be Public or Private CloudNFUs & Communication/Language22

SaaS In-HouseBusinessSaaS licationInfrastructure Internal is identical to thetraditional modelIn-house LOB to SaaSProvidero Number of users, size of datastores, network trafficrequirements, any specific SaaScustomization or add-on featureso Feedback is cost based on actualFacilitiesSaaS will be external CloudFacilitiesusers, special features, storageand networkNFUs & Communication/Language23

IT-AS-A-SERVICEManaging Capacity AcrossBest Execution Venues

What is ITaaS? ITaaS is a business and operating modelRecognizes that lines of business (LOBs) have options for IT resources and services and the ITorganization must compete for their business ITaaS is enabled by a software-defined architectureFor private, public and hybrid clouds where infrastructure (e.g., servers, storage andnetworking) is virtualized, automated by software and delivered as a service Uses self-service cataloguesExpose services (applications, tools, resources) to LOBs and users IT organization acts as an advisor and brokerTo recommend and/or curate additional resources and services, on-demand, to maintainresiliency and accommodate changing business needs Performance metricsUsed to measure customer satisfaction and competitive positioning25

ITaaS - Best Execution Venues Every application has a best execution venueo Some are mature, others are evolvingo All are headed toward “the cloud” Cloud computing is mainstreamo This means choice, access and diversity for ITo Benefits are material - business drives choice of venue There are ways to systematically make the best choiceof venue for each workloado Enterprises are making these choices todayo Providers are/should be targeting these workloads and creating thevenueso There is a snowball effect across the IT landscape as cloudbegets automation and automation begets growth26

ITaaS - Maturity Model27

ITaaS - Basic Business communicates withITaaSITaaS makes its own internaldecisions based ono Business demando ITaaS internal operationo ITaaS will choose the best executionvenue ITaaS communicationFeedback is cost based on whatis required to provide the satisfythe Business demandNFUs & Communication/Language28

ITaaS - Evolved ITaaS communicationITaaS will choose thebest execution venueNFUs & Communication/Language29

Case Study: Global Fortune 500 Consumer Product Co.Pre transformation state: Owned/operated multiple data centers Utilized third party managed services outsource provider Typical infrastructure design/develop/deploy times of 6 months Traditional siloes of technology, development, operations and management All APP development efforts were bespoke standalone projects with no sharing ofinfrastructureCloud-First post transformation state: Started with consumer facing APPS deployed in private cloud. Experienced sticker shock of 10% rise in APP environment cost increase Version 2 deployed to AWS cloud technologies. On demand, elastic and turned OFFwhen not in use 20% reduction in TCO vs. pre transformed (non cloud) state Design/build times of less than 2 weeks start to finish30

Previous Client Organizational Structure: Complex/SiloesClient ITDesign/OrchestrationMgmtStrategyCloudPartnersOn PremiseCloud PartnerClient CloudOperationsVEND1PartnerVEND2PartnerClient ITOperationsNextPartnerLegacy OpsPartner31

451 Research Recommended IT OrganizationClient ITaaSStrategyHybrid ITPartner(Traditional/Private Cloud) Outsourcing?Legacy OwnedPrivate CloudDRaaSClient ITaaSOperationsBest ExecutionWorkloadPartnerPublic CloudPartner SaaSIaaSPaaSDRaaS Consumer FacingEnterprise ServicesOrchestration ExecutionData portabilityHypervisorPartner Core ToolsAutomationCompute32

The Languages of Capacity PlanningSummaryBusiness Transactions per DI DollarCloud Migration7 ,0 00 Started with today’s Digital Infrastructure6 ,0 005 ,0 004 ,0 003 ,0 002 ,0 001 ,0 000123456789 10 11 1 2 13 14 15 1 6 1 7 18 19 20 2 1 2 2 23 24MonthBiz Tra ns p er Month pe r D I Do lla r Created the Capacity Planning Stack to describethe capacity planning process across the breadthand depth of the Digital InfrastructureApp & SS Transactions per CPU FootprintOn Premise20181614121086420123456789 10 1 1 1 2 13 14 15 1 6 1 7 1 8 19 20 21 2 2 2 3 24MonthAp pli cation Tran saction s p er CPU Footpri ntSh ared Se rvices Transa cti ons pe r C PU Fo otprin tApp & SS Transactions per CPU FootprintOn Premise20181614121086420123456789 10 1 1 1 2 13 14 15 1 6 1 7 1 8 19 20 21 2 2 2 3 24MonthAp pli cation Tran saction s p er CPU Footpri ntSh ared Se rvices Transa cti ons pe r C PU Fo otprin t Developed a taxonomy to organize our universeof metricsCPU Footprint: Available vs. UsedOn Premise3 ,0 002 ,5 002 ,0 001 ,5 001 ,0 005 000123456789 10 11 1 2 13 14 15 1 6 1 7 18 19 20 2 1 2 2 23 24MonthTo ta l CPU Footpri nt U sedTo ta l CPU Footpri nt Ava ila bleEstimated Power Usage per Month (kWh)On Premise8 ,0 007 ,0 006 ,0 005 ,0 004 ,0 003 ,0 00 Revived the notion of an NFU - used as touchpoints between Stack levels2 ,0 001 ,0 00012345678Da ta basePow er Used (kWh)9 10 1 1 1 2 13 14 15 1 6 1 7 18 19 20 2 1 22 23 24MonthWe b Ap pPowe r U sed (kWh)Po wer Li mit Illustrated how the Stack can be applied to avariety of execution venues Final step was to show how using the Stack iscritical for ITaaS33

The Languages of Capacity PlanningWhat does this mean to you?Business Transactions per DI DollarCloud Migration7 ,0 00 Use the Stack to think about, discuss & approachcapacity planning – all execution venues6 ,0 005 ,0 004 ,0 003 ,0 002 ,0 001 ,0 000123456789 10 11 1 2 13 14 15 1 6 1 7 18 19 20 2 1 2 2 23 24MonthBiz Tra ns p er Month pe r D I Do lla rApp & SS Transactions per CPU FootprintOn Premise20181614121086420 Leverage the Stack taxonomy to organize anddescribe your metric requirements123456789 10 1 1 1 2 13 14 15 1 6 1 7 1 8 19 20 21 2 2 2 3 24MonthAp pli cation Tran saction s p er CPU Footpri ntSh ared Se rvices Transa cti ons pe r C PU Fo otprin tApp & SS Transactions per CPU FootprintOn Premise20181614121086420123456789 10 1 1 1 2 13 14 15 1 6 1 7 1 8 19 20 21 2 2 2 3 24MonthAp pli cation Tran saction s p er CPU Footpri ntSh ared Se rvices Transa cti ons pe r C PU Fo otprin t Think NFUCPU Footprint: Available vs. UsedOn Premise3 ,0 002 ,5 002 ,0 001 ,5 001 ,0 005 000123456789 10 11 1 2 13 14 15 1 6 1 7 18 19 20 2 1 2 2 23 24MonthTo ta l CPU Footpri nt U sed Language “challenges” can often be traced backto NFU usage & assumed understandingTo ta l CPU Footpri nt Ava ila bleEstimated Power Usage per Month (kWh)On Premise8 ,0 007 ,0 006 ,0 005 ,0 004 ,0 003 ,0 002 ,0 001 ,0 00012345678Da ta basePow er Used (kWh)9 10 1 1 1 2 13 14 15 1 6 1 7 18 19 20 2 1 22 23 24MonthWe b Ap pPowe r U sed (kWh)Po wer Li mit Planning for the cloud fits into the Stack’sframework Navigating the evolving landscape will requirecapacity planners to emerge as leaders in thetransformation from traditional IT to ITaaS34

Make an IMPACT in La Jolla35

Apr 19, 2016 · - Logical resource requirements - Performance . Paves the way for federated capacity planning across today’s Digital Infrastructure Benefits of the Stack Taxonomy 10. Planning Horizons Business Business planning horizons are generally in the range of 6 months to 1 year.

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