1. Automating Performance and Energy Consumption Analysis for Cloud Applications
Feifei Chen
Swinburne University of Technology
Melbourne, Australia
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2. Outlines
Background
Problem Analysis
Approach
Evaluation 2

3. Cloud Computing 3 Give examples for assignment 2 deployment:
IAAS – Amazon
PaaS – EC2 with tomcat
SaaA – Photo Album 3

4. Benefits of Cloud

5. High CO2 emissions contribution
Dark Side of Cloud
High CO2 emissions contribution
Gartner Report 2007: IT industry contributes 2% of world's total CO2 emissions
New York Times 2012: Data centres use about 30 billion watts of electricity per hour worldwide, equivalent to the output of about 30 nuclear power plants

6. Dark Side of Cloud
High Operational Cost
U.S. EPA Report 2007: 1.5% of total U.S. power consumption used by data centers which has more than doubled since 2000 and costs $4.5 billion

7. Green Cloud Computing

8. Service Level Agreement (SLA)

9. Understand both system performance and energy consumption pattern
A key objective of cloud service providers:
Develop solutions to cloud application deployment and management with minimum energy consumption while still guaranteeing performance and other Service Level Agreement (SLA) targets.
Performance
Service Providers
Energy Consumption
Understand both system performance and energy consumption pattern
Assignment 7 – solution architect – 5 objectives
For this – energy efficiency

10. Outlines
Background
Problem Analysis
Approach
Evaluation 10

11. Understand both system performance and energy consumption pattern:
running extensive experiments with heterogeneous parameters/metrics and workloads;
collecting appropriate cloud and application energy/performance measurements;
performing energy/performance trade-off analysis. 11

12. JPetStore
Deployment
Workload
1000 Users
5000
Users

13. Challenges
Manually performing the tasks is tedious and time- consuming
Cloud system performance is related to
Architecture
Workload
An automated performance and energy consumption evaluation framework is imperative
The framework should be able to accommodate different cloud system architectures and adopt different application workloads during load tests and the trade-off evaluation process 13

14. Outlines
Background
Problem Analysis
Approach
Evaluation 14

15. Automated Performance and energy analysis tool - StressCloud

16. Automated Performance and energy analysis tool - StressCloud
Cloud Architecture Model:
All available resources in the target cloud system and their detailed configurations.

17. Automated Performance and energy analysis tool - StressCloud
Cloud Application Workload Model:
A set of Tasks modelling the target cloud application behaviour
Computation-Intensive
CPU-Intensive
Memory-Intensive
Data-Intensive
Communication-Intensive
Task:
A stochastic form chart specifying the detailed user requests and required responses from the cloud system
Task Type
Service Type in StressCloud
CPU-intensive
Fibonacci sequence calculating
Memory-intensive
File processing
Data-intensive
Rational database operating
Communication-intensive
HTTP request/response

18. High-level Workload Model of JPetStore

19. Stochastic Form-Chart Example
Of Each Task

20. Cloud System Architecture Model Example

21. Workload Deployment Scripts Example

22. Load Testing Scripts Example

23. Visualized Results

24. Outlines
Background
Problem Analysis
Approach
Evaluation 24

25. Experiment Setup Energy and performance profiling framework
VM configuration
Virtual Machine
Number of Cores
RAM
Hard Disk
Small 1
2GB
80GB
Medium 2
4GB
Large 3
6GB
XLarge 4
8GB

26. Energy Consumption and Throughput
Experiment Results
Test set 1: Keep the resource allocation strategy constant while changing workload
System Configurations: 1 Large VM (3CPUs and 6GB RAM)
Workload: user workload 50~200
Energy Consumption and Throughput
Deploy MJPetStore on one VM with 3 CPUs and 6GB RAM. The initial number of users was set to 10. We then increased the concurrent requests number of each user from 50 to 200 in steps of 50.

27. Energy Consumption and Throughput
Experiment Results
Test set 2: Keep the workload constant while changing the resource allocation strategy
System Configuration:
1Large: Deploy three types of tasks on the 1 VM.
3Small(D): Deploy three types of tasks on different VMs.
3Small(S): Deploy three types of tasks on the same VM with workloads evenly distributed across all VMs.
Workload: user request 100.
Energy Consumption and Throughput

28. Thanks! Feifei Chen feifeichen@swin.edu.au 28
Save this template as a new PowerPoint Presentation, giving it the name you require OR copy these templates from Slide Master view into your existing presentation’s Slide Master options
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In the Slides area, select ‘New Slide’ to add a new slide.
To apply a slide style to the new/highlighted slide - in the Slides area, select ‘Layout’ menu, select preferred slide style from the menu (eg. ‘Title and Content’) , select ‘Reset’.
If you are updating an existing presentation, existing styles may not automatically update (hence using ‘reset’,) especially if the existing slide has not been produced with a template.
Text from imposed text boxes may need to be cut & pasted into new auto-generated template text boxes etc.
You should only use one colour template for each presentation (eg. Only black background, or white, or grey – not a combination)
The Design uses only 24pt Arial as the font, with 22pt the minimum text size (used at third level).
The title page ‘wave’ graphics can be increased in width, but not height.
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