Performance Testing Strategy for Cloud-Based System using Open Source Testing Tool
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This document outlines a performance testing strategy for a cloud-based system using an open source testing tool. It describes introducing virtual users gradually from 1 to 3000 to test response times. Response times remained under 5 seconds for up to 1500 users but slowed for 3000 users. Testing showed faster response for high-speed internet and unloaded servers. The strategy successfully tested the system's ability to handle increasing loads in the cloud. Future work could include hosting the testing tool in the cloud and expanding performance analysis.
![Introduction & Related Works
Performance requirements that should be
specified are throughput level, latency, capacity
and ability to operate in lower mode level
(Hussain and Abdulsalam, 2012].
This study illustrates the
strategy employed for
conducting performance
testing for a cloud-based
software by using open
source testing tool via
distributed performance
testing approach
Important tasks during and after the performance
test execution of the cloud should involve
environment deployment, monitoring of
environment status, controller-agent model
implementation, logs analysis, analysis of slow
queries, errors visualization as well as statistics
comparison (Lynch, Cerqueus and Thorpe, 2012)
A framework for testing scalability of web
application on the cloud should include software
that serves as HTTP server, load balancer,
database, cache and benchmark tool (Vasar,
Srirama and Dumas, 2012)
Testing cloud application shall also deal with
quality of workload generation, complexity in data
analysis and service level agreement (Zhou, Zhang
and Ye, 2013)](https://image.slidesharecdn.com/mysec2013paper53dhiauddin-131203213351-phpapp01/85/Performance-Testing-Strategy-for-Cloud-Based-System-using-Open-Source-Testing-Tool-3-320.jpg)
Performance Testing Strategy for Cloud-Based System using Open Source Testing Tool
- 1. PERFORMANCE TESTING STRATEGY FOR CLOUD-BASED SYSTEM USING OPEN SOURCE TESTING TOOL Assoc. Prof. Dr. Suhaimi Ibrahim Advanced Inforamtics School Universiti Teknologi Malaysia
- 2. Outline • • • • • • Introduction & Related Works Overview of System Under Test Performance Testing Strategy Performance Test Results Findings & Discussion Conclusion
- 3. Introduction & Related Works Performance requirements that should be specified are throughput level, latency, capacity and ability to operate in lower mode level (Hussain and Abdulsalam, 2012]. This study illustrates the strategy employed for conducting performance testing for a cloud-based software by using open source testing tool via distributed performance testing approach Important tasks during and after the performance test execution of the cloud should involve environment deployment, monitoring of environment status, controller-agent model implementation, logs analysis, analysis of slow queries, errors visualization as well as statistics comparison (Lynch, Cerqueus and Thorpe, 2012) A framework for testing scalability of web application on the cloud should include software that serves as HTTP server, load balancer, database, cache and benchmark tool (Vasar, Srirama and Dumas, 2012) Testing cloud application shall also deal with quality of workload generation, complexity in data analysis and service level agreement (Zhou, Zhang and Ye, 2013)
- 4. Overview of System Under Test
- 5. Performance Testing Strategy (1) Sub-System Scenario Number of Virtual Users (VU) Client System Response time to load services home page 1 Server System (Intelligent Services Portal + Content Aggregator + Location Aware) Response time to load services home page (via client test page) 1, 100, 200, 300, 400, 500, 1000, 1500, 3000
- 6. Performance Testing Strategy (2)
- 7. Performance Test Results (1)
- 8. Performance Test Results (2) Client Internet Connection Server Load Response Time (seconds) LAN speed High 7.01 LAN speed Low 4.81 Wireless LAN Low 5.33 1 Mbps wired broadband High 8.57 1 Mbps wired broadband Low 5.33 0.44 Mbps wireless broadband Low 16.52 – 24.88
- 9. Findings & Discussion • • • • • • • • The online services system hosted in the cloud platform could response to specified performance requirement of five seconds from 1 user to 1500 concurrent users without any break. At 3000 concurrent users, the system still can response to huge requests without fail but with delay in response time. When the server is under heavy load or many concurrent users are accessing the online services system, a particular end-user may experience slower response time accessing the online services via the client system. End-user with fast Internet connection will access the online services faster than those with slow speed in any server load condition. Cloud platform allows the virtual web servers to be scaled up in order to meet the performance requirements for faster response time Performance testing activities should be planned earlier in the life cycle and not during execution or after execution completed Performance test cases should mimic the real-world scenarios to ensure the reliability of test results Understanding of the performance requirements will help in selection of suitable performance test tools to accommodate different usage profile, loads, strategy and environment setup
- 10. Conclusion • The study has demonstrated the success of the test strategy in measuring the performance of cloud-base system with the support open source testing tool • it is important to have proper planning and come out with realistic scenarios for performance testing • Performance testing should not be treated as “when required” or “when requested” basis. When performance test is done using the right strategy, right scenarios and appropriate testing tool, any system would be able to deal with increasing loads • Future works? Host the performance testing tool in the cloud too Expanded the performance analysis further to not just on response time, but also other aspects such as CPU utilization, memory utilization, disk I/O and network latency Explore other possible real-world scenarios for the system usage to ensure better performance testing coverage