A comparison of two-level and multi-level modelling for cloud-based applications

Transcription

1 A comparion of two-level and multi-level modelling for cloud-baed application Aleandro Roini Nikolay Nikolov Juan de Lara Ether Guerra UNIVERSIDAD AUTONOMA

2 Challenge

3 22 Feb million uer regiter to Telegram and Telegram crahe

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5 Self-adaptive cloud-baed application Cloud-baed application that elf-adapt to change in environment and requirement

6 Cloud-baed application Applica)on Data Run- )me SaaS PaaS IaaS OS Virtualia)on Server Storage Network

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8 Reaoning engine Diff Target model -me Current model Adapta0on engine Running ytem

9 Deployment model: deign-time Ubuntu Tomcat Type SenApp HAProxy haproxy1 enapp1 [intance range: 1..4] tomcat1 ubuntu1 [loca)on: NO]

10 Deployment model: run-time Ubuntu Tomcat Type SenApp HAProxy Implicit intance Explicit intance Before adapta)on AXer adapta)on Before adapta)on AXer adapta)on haproxy1 haproxy1 haproxy1 haproxy1 enapp1 [intance range: 1..4, intance=2] enapp1 [intance range: 1..4, intance=3] enapp11 enapp12 enapp11 enapp12 enapp13 tomcat1 tomcat1 tomcat11 tomcat12 tomcat11 tomcat12 tomcat13 ubuntu1 OpenStack [loca)on: NO] ubuntu1 OpenStack [loca)on: NO] ubuntu11 [CPU load = 99] OpenStack [loca)on: NO] ubuntu12 [CPU load = 90] ubuntu11 [CPU load = 80] ubuntu12 [CPU load = 70] OpenStack [loca)on: NO] ubuntu13 [CPU load = 60] If CPU load of a VM i above 90%, then cale out

11 CloudML abtract yntax: two level

12 haproxy1* Deployment model: implicit intance enapp1* [intance range: 1..4, intance=2] tomcat1* ubuntu1* OpenStack* [loca.on:*no]* C1: elf.hotedcomptype- >forall(t CompInt.allIntance()- >exit(i i.type = elf and i.hotedcompint- >exit(ci ci.type = t))) hotedcomptype * CompType lingui1c typing SenApp ST type ontological typing Tomcat TU VMType Ubuntu type hotedcompint * CompInt enapp1 currentint = 2 minint = 1 maxint = 4 currentint: Int minint: Int maxint: Int t1 tomcat1 currentint = 2 minint = 1 maxint = 4 C2: elf.currentint >= elf.minint C3: elf.maxint <> - 1 implie elf.currentint <= elf.maxint C4: elf.hotedcompint- >forall(i elf.type.hotedcomptype - >include(i.type)) tu1 VMInt cpuloadavg: Double ubuntu1 currentint = 2 minint = 1 maxint = 4 cpuloadavg = 94.5 metamodel model

13 haproxy1* C5: elf.hotedcomptype- >forall(t CompInt.allIntance()- >exit(i i.type = elf and i.hotedcompint- >exit(ci ci.type = t))) hotedcomptype * CompType type Deployment model: explicit intance C6: elf.hotedcompint- >forall(i elf.type.hotedcomptype - >include(i.type)) hotedcompint * CompInt enapp11* enapp12* tomcat11* tomcat12* ubuntu11* ubuntu12* [CPU load = 99] [CPU load = 90] OpenStack* [loca.on:*no]* VMType SenApp ST /cpuloadavg: Double = let load:set = VMInt.allIntance()- >elect(m m.type=elf) - >collect(cpuload) in load- >um() / load- >ize() Tomcat type enapp12 t1 tomcat12 VMInt cpuload: Int tu1 metamodel model TU Ubuntu /cpuloadavg = 94.5 ubuntu12 cpuload = 90

14 haproxy1* haproxy1* Deployment model: enapp1* [intance range: 1..4, intance=2] tomcat1* enapp11* enapp12* tomcat11* tomcat12* implicit and explicit int. ubuntu1* OpenStack* [loca.on:*no]* ubuntu11* ubuntu12* [CPU load = 99] [CPU load = 90] OpenStack* [loca.on:*no]* hotedcomptype * CompType linguitic typing SenApp ST type ontological typing Tomcat C1 TU hotedcomptemp * CompTemp currentint:3int minint:3int maxint:3int VMType type VMTemp Ubuntu enapp1 currentint =32 minint =31 maxint =34 t1 type tomcat1 currentint =32 minint =31 maxint =34 C2,% C3,"C4,% C5 tu1 /cpuloadavg:3double3=3 ubuntu1 currentint =32 minint =31 maxint =34 /cpuloadavg =394.5 hotedcompint * CompInt type enapp12 C6 metamodel model t12 tomcat12 VMInt cpuload:3int tu12 ubuntu12 cpuload =390

15 CloudML abtract yntax: multiple level

16 @3 * hotedcomp Component /currentint@2: int = $ elf.allintance().ize() $ VirtualMachine cpuload@3: int /cpuloadavg@2: double = $ elf.allintance()- >collect(cpuload )- >um()/elf.currentint $ Language SenApp: Component * Tomcat: Component * Ubuntu: VirtualMachine Component type enapp1: SenApp [1..4] /currentint = tomcat1: Tomcat [1..*] /currentint = ubuntu1: Ubuntu [1..*] /cpuloadavg = 94.5 /currentint = 2 Deployment model: implicit enapp11: enapp1 tomcat11: tomcat1 ubuntu11: ubuntu1 cpuload = 99 enapp12: enapp1 tomcat12: tomcat1 ubuntu12: ubuntu1 cpuload = 90 Deployment model: explicit int.

17 Comparion

18 Criteria Size of language definition Complexity of OCL contraint Preciion Extenibility Flexibility Tooling

19 @3 * hotedcomp Size of language definition Component /currentint@2: int = $ elf.allintance().ize() $ VirtualMachine cpuload@3: int /cpuloadavg@2: double = $ elf.allintance()- >collect(cpuload )- >um()/elf.currentint $ Language definition: Multi-level hotedcomptype * CompType( C1! type VMType( hotedcomptemp * CompTemp( type currentint: Int minint: Int maxint: Int type VMTemp( /cpuloadavg: Double = hotedcompint * CompInt( C2,%C3,!C4,%C5% C6% type VMInt( cpuload: Int Language definition: Two-level

20 Tooling

21 CloudML two-level tooling 21

22 CloudML multi-level tooling MetaDepth 22

23 MetaDepth Potency-baed multi-level modelling Textual modelling Integration with Epilon language (adapted to multilevel): Epilon Object Language Epilon Tranformation Language Epilon Generation Language Analyi of conflict between integrity contraint at different level

24 // Level 3: Language definition Model { Node Component { hotedcomp: Component[*]; CloudML in MetaDepth /currentint@2: int = $ elf.allintance().ize() $; } Node VirtualMachine: Component { cpuload@3: int; /cpuloadavg@2: double = $ elf.allintance().collect ( c c.cpuload ).um() / elf.currentint $ ; } } // Level 2: Component type definition CloudML ComponentType { Component Tomcat { tomcathot: SenApp[*]{hotedComp}; } } Component SenApp {} VirtualMachine Ubuntu { ubuntuhot: Tomcat[*]{hotedComp}; }

25 CloudML in MetaDepth // Level 1: Deployment model with implicit intance ComponentType DeploymentModel { SenApp enapp1 [1..4] {} Tomcat tomcat1 [1..*] { t1hot: enapp1[1] {tomcathot}; } Ubuntu ubuntu1 [1..*] { u1hot: tomcat1[1..4] {ubuntuhot}; } } // Level 0: Deployment model with explicit intance DeploymentModel intance { enapp1 enapp11; enapp1 enapp12; tomcat1 tomcat11 { t1hot = [enapp11]; } tomcat1 tomcat12 { t1hot = [enapp12]; } ubuntu1 ubuntu11 { cpuload = 99; u1hot = [tomcat11]; } ubuntu1 ubuntu12 { cpuload = 90; u1hot = [tomcat12]; } }

26 Concluion and Future Work

27 Concluion A fundamental principle in engineering, including oftware engineering, i to minimize the amount of accidental complexity which i introduced into engineering olution due to mimatche between a problem and the technology ued to repreent the problem. C. Atkinon and T. Kühne Reducing accidental complexity in domain model, 2008

28 Future Work Tranformation two-level<->multi-level Further development of tooling Empirical tudy

29 Acknowledgement PAA AGE Go Lite

30 Thank you! More info: cloudml.org Get in aleandroroini.org