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Nane KratzkeOVERCOMING EX ANTE COSTINTRANSPARENCY OF CLOUDS Prof. Dr. rer. nat. Nane Kratzke 1 Computer Science and Business Information Systems

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Analyzing Impacts of Clouds <=)@:":0$.$"#):"+)A4?$%":"2$) )"*!&1($$)($234")56B8) !"#$%&%($)*+$) 9&$%:34")4;)<=> ,-(#$.)/$(0") ,$%?2$() !"#$%&& !() 1($$)($234")5678) 1($$)($234")5678) Prof. Dr. rer. nat. Nane Kratzke 2 Computer Science and Business Information Systems

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Analyzing Impacts of Clouds to COBIT Reduced efforts for Additional efforts for• Continuous Service • Assess and manage IT-Risks• Manageability of Performance and Capacity • Ensure compliancy with external requirements• Procure IT-Resources and Identify and allocate costs • More complex Configuration management and IT-• Monitor and evaluate IT-performance Processes/Relationships Prof. Dr. rer. nat. Nane Kratzke 3 Computer Science and Business Information Systems

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Analyzing Impacts of Cloudsto TOGAF Reduced efforts for • Use billable SaaS or PaaS items as building blocks for information systems architecture • Data architecture • Application architecture • Use billable IaaS items as building blocks for technology architecture • Use scalability and cost associativity as well as pay-as-you-go to generate new oportunities and solutions • 100 processing units for one hour • 100 hours of one processing unit • Produce (almost) the same costs • Experimentation is cheap Prof. Dr. rer. nat. Nane Kratzke 4 Computer Science and Business Information Systems

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Analyzing Impacts of Cloudsto ITIL Reduced efforts for • Service Design • Capacity Management • Availability Managemet • Continuity Management • Service Operation • Event Management • Incident Management • Problem Management Additional efforts for • Service Design • Service Level Management • Information Security Management • Service Transition • Asset and Configuration Management Prof. Dr. rer. nat. Nane Kratzke 5 Computer Science and Business Information Systems

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Qualitative Weaknesses and Strengths of Clouds Strength Weakness l cture and low leve Physical infrastru mer perspective) o service free (cust mpliancy More complex co t ted functional managemen Pro vision of automa services t cu rity managemen More complex se (ex post) Cost transparency d rvice, process an More complex se anagement ntinuousity and configuration m Inhe rent scalability, co availability Prof. Dr. rer. nat. Nane Kratzke 6 Computer Science and Business Information Systems

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So – everthing is beautifull?No substantial show stoppers?• Higher order showstoppers for cloud approaches Hard to handle • Security and Compliance Management • Incompatible SLAs • Especially national laws, privacy, data ownership, confidentiality, data location, forensic evidence, auditing, etc.• Decision making showstoppers for cloud approaches Could be solved • Ex post but no ex ante cost transparency • Relevant costs of cloud approaches must be known before a system enters operation • Otherwise IT investment decisions pro or contra cloud based approaches can not been made Prof. Dr. rer. nat. Nane Kratzke 7 Computer Science and Business Information Systems

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Costs are influenced by Your System Usage Your System Costs XaaS Usage Architecture Prof. Dr. rer. nat. Nane Kratzke 8 Computer Science and Business Information Systems

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Costs are influenced by ...To be validated by ongoing research User accounts Your System Usage Amount of unique visitors/users Amounts of user/system requests 24x7 Loadbalancing and autoscaling asset groups Generated Your System XaaS Usage Architecture Structure of processing tier (network) Structure of storage and backup Data transfer tier (network) Data storage Data processing Monitoring efforts (e.g. events, IaaS) Amount of sub-service requests (PaaS, SaaS) Prof. Dr. rer. nat. Nane Kratzke 9 Computer Science and Business Information Systems

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Finding nearest neighbors to exploitcomparable ex-post costs of other systems !"#$%&()*%&)+),*-&).(/*& cost estimations operated systems with ex post costs planned system Prof. Dr. rer. nat. Nane Kratzke 10 Computer Science and Business Information Systems

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Select comparable systems and collecteddata by similarity !"#$%&()*)%()#+,-&(.) !"#$%&()*)%()#+,-&(.) !"#$%&()*)%()#+,-&(.) /012)3%-#2)45678-9#:) /012)3%-#2)45678-9#:) /012)3%-#2)45678-9#:) =+) =+) =+) ;-9) ;-9) ;-9) /-9-) /-9-) /-9-) System Selection of the Architecture most comparable operated system =+) /-9)<%0<10%&() >(9#) :2#0) /-9-) ;0%((,(.)%)<:"%$%30#) /012)3%-#2)45678-9#:) Prof. Dr. rer. nat. Nane Kratzke 11 Computer Science and Business Information Systems

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Conclusionor: Vision for ongoing research • Collect and Provide Data • Your System Usage, Provided Service Usage • Your System Architecture, Costs (Billing) • of real world cloud-based applications/services in order to estimate costs for planned cloud-based costs/services CLOUDLAB Cost, Usage, and Architecture Analytics for Cloud-based Information Systems Prof. Dr. rer. nat. Nane Kratzke 12 Computer Science and Business Information Systems