MELA: Monitoring and Analyzing Elasticity of Cloud Services -- CloudCom 2013
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Transcript of MELA: Monitoring and Analyzing Elasticity of Cloud Services -- CloudCom 2013
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Daniel Moldovan,Georgiana Copil, Hong-Linh Truong,
Schahram Dustdar
MELA: Monitoring and Analyzing Elasticity of Cloud Services
Work partially supported by the European Commission in terms of the CELAR FP7 project (http://www.celarcloud.eu/)
Distributed Systems Group (http://dsg.tuwien.ac.at/)
Vienna University of Technology (http://www.tuwien.ac.at/)
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MotivationElastic Cloud Service
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Data-as-a-Service for Machine to Machine platforms Load balancer distributes incoming requests to Event Processing instances Distributed Data Store: Controller and Nodes
Start with an initial lighter configuration
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MotivationElastic Cloud Service
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Data-as-a-Service for Machine to Machine platforms Load balancer distributes incoming requests to Event Processing instances Distributed Data Store: Controller and NodesAdd service unit instance when load
increases
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MotivationElastic Cloud Service
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Data-as-a-Service for Machine to Machine platforms Load balancer distributes incoming requests to Event Processing instances Distributed Data Store: Controller and NodesRemove service unit instance when load
decreases
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MotivationElastic Cloud Service
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Data-as-a-Service for Machine to Machine platforms Load balancer distributes incoming requests to Event Processing instances Distributed Data Store: Controller and Nodes
Add service unit instance and data node instance when load increases too much
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Service Level Monitoring Response time Number of clients Other specific metrics
System Level Monitoring Ganglia, Nagios, etc. CPU usage Memory usage Network transfer
User-Defined Requirements violation: - Cost per client too highReasons: - Too much logging? Monitoring chatter? - Too expensive VMs? Which one can be downsized? - Not enough clients? Why?
Controlling the service’s elasticity
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MotivationInsufficient Cloud Service Monitoring and Analysis Support
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Approach and ChallengesStructure Monitoring Data
How to map system data to service level? How to derive higher level information?
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Monitoring Data
Service Structure
Impose service structure over collected monitoring data
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Multi-Level Monitoring Snapshot
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Metrics composition and enrichment
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Multi-Level Monitoring Snapshot
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Multi-Level Monitoring Snapshot
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Enrich metric with COST information
COST/VM * numberOfVMs
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Multi-Level Monitoring Snapshot
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Propagate activeConnections from LoadBalancer service unit
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Multi-Level Monitoring Snapshot
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Multi-Level Monitoring Snapshot
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Multi-Level Monitoring Snapshot
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Compute cost/client/h
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Evaluate Service’s Elasticity How to characterize service elasticity? How to derive service‘s behavior limits? How to characterize and predict elasticity behavior?
Approach and Challenges
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Runtime Properties of Elastic Cloud Services Background
Elastic process: cost, quality and resources elasticity Extend concept to cloud services
Elasticity Space Collection of monitoring snapshots I.e. the space in which an elastic service moves
Elasticity Boundary Elasticity Space boundaries in which service’s requirements are
respected
Elasticity Pathway Characterizes service evolution trough elasticity space
Elasticity Dimensions
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Multi-Level Elasticity SpaceEvent Processing Topology
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Elasticity Space Snapshot
Elasticity Space “Clients/h” Dimension
Elasticity Space “Response Time” Dimension
Service requirement COST<= 0.0034$/client/h 2.5$ monthly subscription for each
service client (sensor)
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Multi-Level Elasticity SpaceEvent Processing Topology
Service requirement COST<= 0.0034$/client/h 2.5$ monthly subscription for each
service client (sensor)
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Elasticity Space “Clients/h” Dimension
Elasticity Space “Response Time” Dimension
Determined Elasticity Space Boundaries Clients/h > 148 300ms ≤ ResponseTime ≤ 1100 ms
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Multi-Level Elasticity Pathway
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Service requirement COST<= 0.0034$/client/h 2.5$ monthly subscription for
each service client (sensor)
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Multi-Level Elasticity Pathway
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Cloud Service Elasticity Pathway
Service requirement COST<= 0.0034$/client/h 2.5$ monthly subscription for
each service client (sensor)
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Multi-Level Elasticity Pathway
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Event Processing service unit Elasticity Pathway
Cloud Service Elasticity Pathway
Service requirement COST<= 0.0034$/client/h 2.5$ monthly subscription for
each service client (sensor)
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Conclusions
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Concepts Elasticity Space and Elasticity Boundary Elasticity Pathway
Mechanisms Constructing cross-layer monitoring snapshots Determining elasticity space and boundary Determining elasticity pathway
MELA Customizable framework for monitoring and
analyzing elasticity of cloud services
MELA: Monitoring and Analyzing Elasticity of Cloud Services
Work partially supported by the European Commission in terms of the
CELAR FP7 project (http://www.celarcloud.eu/)
Distributed Systems Group(http://dsg.tuwien.ac.at/)
Vienna University of Technology (http://www.tuwien.ac.at/)
http://dsg.tuwien.ac.at/research/viecom/mela/