The need to comprehend clouds IT goes Cloud Athanasios Tsitsipas OMI, University of Ulm, Germany

Page 2 The Cloud Hype Everybody moves to the cloud Nothing but benefits, if you believe the advertisements elastic always available secure access from anywhere reliable virtually endless space high speed cheap sounds like… magic

Page 3 There is NO common answer to that! The term became popular with Amazon’s “Elastic Clouds” No clear concept behind it  Related areas have jumped on the wagon  Rebranded offerings to “clouds”  Diverging usage  Confusion about the term by now What IS a “Cloud”?

Page 4 SO WHAT ARE CLOUDS? source:

Page 5 Cloud Timeline [1961]John McCarthy: “computing as a utility” [1969]J.C.R. Licklider: “intergalactic computer network” [1993]IETF: Telecom “clouds” = loadbalancing [1999]Salesforce.com: applications over the internet (originally called “platform computing” or “force.com”) [2001]Microsoft: “clouds” = internet [2006]Amazon EC2: “clouds” = elastic computing infrastructure (IaaS) [2007]IBM starts “cloud research project” [2007]Dell wants to trademark “cloud computing” (rejected) [2008]Gartner: “clouds shape relationship between consumer and provider of IT services” [“cloud”=?] [2009]Google App Engine: “clouds” = PaaS Start to use the term “Cloud” widely

Page 6 So, what is a “cloud” then? Different approaches to find a definition in retrospect  According to the “Future of Cloud Computing” report: Terminology Characteristics Related Areas

Page 7 Types of Clouds Infrastructure as a Service exposes resources as data or computing hosts exposes resources as data or computing hosts manage the resources in an elastic fashion manage the resources in an elastic fashion Examples: Amazon S3 / EC2, Zimory Infrastructure as a Service exposes resources as data or computing hosts exposes resources as data or computing hosts manage the resources in an elastic fashion manage the resources in an elastic fashion Examples: Amazon S3 / EC2, Zimory Software as a Service exposes dedicated functionalities as services exposes dedicated functionalities as services services exploit cloud capabilities to ensure availability etc. services exploit cloud capabilities to ensure availability etc. Examples: Google Docs Software as a Service exposes dedicated functionalities as services exposes dedicated functionalities as services services exploit cloud capabilities to ensure availability etc. services exploit cloud capabilities to ensure availability etc. Examples: Google Docs Platform as a Service exposes a platform and typically an API exposes a platform and typically an API services can be developed and hosted in this platform services can be developed and hosted in this platform Examples: Windows Azure, Google App Engine Platform as a Service exposes a platform and typically an API exposes a platform and typically an API services can be developed and hosted in this platform services can be developed and hosted in this platform Examples: Windows Azure, Google App Engine Infrastructure as a Service exposes resources as data or computing hosts exposes resources as data or computing hosts manage the resources in an elastic fashion manage the resources in an elastic fashion Examples: Amazon S3 / EC2, Zimory

Page 8 Non-FunctionalEconomicTechnological qualities of cloud systems, rather than technological aspects. These include: Scalability Elasticity Quality of service Agility and adaptability Availability Reliability Ease of use High performance key driver behind (commercial) cloud systems. Typical interest rests on: Cost reduction Pay per use Improved time to market Return of investment CAPEX to OPEX “Going green” Arise from realising non-functional / economic concerns. Particular issues: Virtualisation Multi-tenancy Security, privacy APIs and / or programming enhancements Metering Tools in general General Characteristics of a Cloud

Page 9 Essential Cloud Properties Offer “services” Adapt “elastically” to changes in usage, thus dynamic number of services pay as you go (pay per use) improved resource utilisation

Page 10 Prepare data for Send out mass s Analyze error logs IT support Database Server Dashboard

Page 11 Prepare data for Send out mass s Analyze error logs IT support Database Server Dashboard Rule-based analysis Rule engine Drop contact from CRM Business IT alignment

Page 12 Prepare data for Send out mass s Analyze error logs IT support Database Server Dashboard Rule-based analysis Rule engine Drop contact from CRM

Page 13 Prepare data for X Send out s Send regular mails via post

Page 14 Prepare data for X Send out s Send regular mails via post Database as a Service Customer analysis service service Cloud provider ACloud provider B

Page 15 SLA Invoicing, Payment and Taxed- based Archiving Business Process Alternatives on Cloud My Selected Business Processes Business Process Library CompareSelectCancel Invoicing and Payment SLA Direct Invoicing SLA … … …

Page 16 Task/Action ATask/Action B Task/Action C Level-I Service XJira Level-II Level-III Jira Atlassian Jira Provider Y Jira Self-hosted Levels of Business Processes (semantics omitted) Cloud Provider YCloud Provider Z VM Self-hosted VM Level-IV Cloud orchestration and deployment tool

Page 17 Business Process as a Service Infrastracture Services PaaS SaaS

Page 18 Business Process as a Service (BPaaS) Companies automating business processes for decades Forced to Business IT Alignment with manual labor What they want to address: Unexpected behaviors? Increased usage? Management of middleware, networking or database? Packaged offerings? What they get: Smart Cloud Deployment Orchestrate different services, systems or components Exploit all the capabilities of the Cloud to the business level

Page 19 Thank you for your attention.