SLA PROTECTION. MODELS for Virtualized Data Centers. Gambi Pezzè

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1 SLA PROTECTION MODELS for Virtualized Data Centers Gambi Pezzè Young

2 INTRODUCING THE APPROACH Context, Problem and Approach main ideas 1

3 DATA CENTER WAN SITE SITE Physical Resource

4 DATA CENTER WAN SITE SITE Component Physical Resource

5 DATA CENTER WAN SITE SITE Service Component Physical Resource

6 DATA CENTER SLA WAN SITE SITE Service Component Physical Resource

7 DATA CENTER Static resource allocation Over Provisioning (OP) SLA WAN SITE SITE Service Component Physical Resource Under Utilization (U 2 )

8 VIRTUAL DATA CENTER * Physical Resource * ref architecture inspired by Reservoir EuP

9 VIRTUAL DATA CENTER * Virtualization Physical Resource * ref architecture inspired by Reservoir EuP

10 VIRTUAL DATA CENTER * VEE and VAN Virtualization Physical Resource * ref architecture inspired by Reservoir EuP

11 VIRTUAL DATA CENTER * Live migration Vertical scaling Horizontal scaling VEE and VAN Virtualization Physical Resource * ref architecture inspired by Reservoir EuP

12 VIRTUAL DATA CENTER * Component VEE and VAN Virtualization Physical Resource * ref architecture inspired by Reservoir EuP

13 * VIRTUAL DATA CENTER Service Component VEE and VAN Virtualization Physical Resource *ref architecture inspired by Reservoir EuP

14 * VIRTUAL DATA CENTER Dynamic binding Service Component VEE and VAN Virtualization Physical Resource *ref architecture inspired by Reservoir EuP

15 * VIRTUAL DATA CENTER SLA SLA GOLD SILVER SLA Service Component VEE and VAN Virtualization Physical Resource *ref architecture inspired by Reservoir EuP

16 * VIRTUAL DATA CENTER SLA Dynamic resource management Automatic control enabled SLA SLA GOLD SILVER New opportunities Service Component VEE and VAN Virtualization Physical Resource OP-U2 may be reduced *ref architecture inspired by Reservoir EuP

17 THE BIG CHALLENGE Timely responses Control Mechanisms unpredicted situations

18 THE BIG CHALLENGE Timely responses Control Mechanisms Automatic unpredicted situations Autonomic

19 THE BIG CHALLENGE Timely responses Automatic unpredicted situations Monitoring Data Control Mechanisms Monitor Analyze Knowledge Plan Execute Autonomic Control Actions Decision Process Input Workload

20 THE BIG CHALLENGE Autonomic SLA Protection Timely responses Automatic unpredicted situations Monitoring Data Control Mechanisms Monitor Analyze Knowledge Plan Execute Autonomic Control Actions Decision Process Input Workload

21 OUR FOCUS It s too late to apologize Reaction RECOVERY Determine suitable changes on the system to guarantee that SLAs will be not violated at runtime PREVENTION Proaction pobody is nerfect

22 AUTONOMIC SLA PROTECTION Model Driven abstract knowledge representation automatic processing and reasoning expected effects of control actions not one big model: inefficiency several dimensions: heterogeneity past, present and future: time Multi-Model Multi-Layer System organized in layers QoS depending on underlying layers Dependencies Inter- and Intra- layers

23 MULTI-MODEL AT WORK Case Study, Motivating scenarios and Uses of models 2

24 VIDEO ON DEMAND Web Server Storage Server Video Server Server Cluster

25 MODELS Workload Service composition N Req RetrieveMovie VerifyAccess ChannelSetup t x Time Architectural Physical resource VEE allocation Available Occupied

26 SCENARIO Resp Time RT MAX t x Time An increasing number of user requests are served with a response time approaching the upper limit.

27 Workload CASE A Service composition N Req RetrieveMovie VerifyAccess ChannelSetup t x Time Resp Time RT MAX Architectural t x Time Physical resource VEE allocation S1 VERT. SCALE VERT. SCALE S4 S4 S2 S2 S1 S4

28 Workload N Req CASE A+ Service composition RetrieveMovie t x Time VerifyAccess ChannelSetup Resp Time RT MAX Architectural t x Time Physical resource VEE allocation C1 S1 S2 S2 HORIZ SCALE C1 S1 VERT. SCALE

29 Workload N Req CASE B Service composition RetrieveMovie VerifyAccess ChannelSetup Resp Time RT MAX t x Time Architectural t x Time VEE allocation REALLOCATE Physical resource S1 S2 S2 S1 C1 C1

30 SUMMING UP Conclusions and Related work 3

31 CONCLUSIONS SLA protection in VDC depends on structure and behavior at many abstraction levels A set of interrelated models can capture the information needed by the controller

32 RELATED WORK The Reservoir Seed Team. Reservoir - An ICT infrastructure for reliable and effective delivery of services as utilities. Tech Report IBM L. Cherkasova, D. Gupta, and A. Vahdat. When virtual is harder than real: Resource allocation challenges in virtual machine based it environments. Tech Report HP M. Woodside, T. Zheng, and M. Litoiu. Service system resource management based on a tracked layered performance model. ICAC B. Urgaonkar, P. Shenoy, A. Chandra, and P. Goyal. Dynamic provisioning of multi-tier internet applications. ICAC D. Gmach, J. Rolia, L. Cherkasova, and A. Kemper. Capacity management and demand prediction for next generation data centers. ICWS M. Litoiu, M. Woodside, and T. Zheng. Hierarchical model-based autonomic control of software systems. DEAS M. Autili, L. Berardinelli, V. Cortellessa, A. Marco, D. Ruscio, P. Inverardi, and M. Tivoli. A development process for self-adapting service oriented applications. ICSOC

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