COMPARATIVE STUDY ON PERFORMANCE TEST METHODOLOGIES TRADITIONAL AND CLOUD

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1 COMPARATIVE STUDY ON PERFORMANCE TEST METHODOLOGIES TRADITIONAL AND CLOUD K.MANGAIYARKARASI 1 K.K.SURESHKUMAR 2 Dr.N.M.ELANGO 3 1 Research Scholar, Department of Computer Science (P.G), Kongu Arts and Science College, Bharathiar University, Tamil Nadu, India. 2 Assistant Professor, Department of MCA, Kongu Arts and Science College, Bharathiar University, Tamil Nadu, India 3 Professor and Head, Department of MCA, RMK Engineering College, Anna University of Technology, Chennai, India ABSTRACT Performance testing entails various components such as the performance testing tools and the application or system under test which are installed on premise, within the local environment. In most organizations, the performance testing is done in a lab environment. In general the lab requires a copy of infrastructure set up, server configurations, hardware and software details from the production environment to host the system or application under test, and the required performance testing tools. Setting up such a local lab environment we require considerable investment (cost), time and effort, and the management of overheads such as maintenance costs, cost involved training the resources and also administrators to maintain and support the lab. In proposed cloud model the environment set up cost will be comparatively less since whenever needed we can buy the cloud environment, no need to pay in all hashes of testing (when not used), cloud will provide the greater test control to simulate the required user load. The hardware, software, infrastructures, data storage, application services and relevant platforms will be created by the cloud provider, we no need to worry about creating or customizing the test environment, we have to buy the cloud environment and complete the test whenever required. The performance test methodologies On-Premises and cloud models are analyzed and compared for better performance test results. Keywords: Performance Testing, Cloud Testing, Traditional Performance Testing, Cloud Model, On- Premises Model 1. INTRODUCTION Nowadays internet is growing at an unprecedented rate. Globally there close to 2.5 billion internet users and this is a phenomenal number. Facebook has crossed a whopping 500 million user market and Twitter receives millions of tweets every month. Lots of devices are available in the market like net books, smart phones, ipads, tablets; etc to use the web application and mobile applications, so the usage 1

2 has increased phenomenally. On one hand, this type of device access making life very easy for the endusers but it is altogether a different phenomena for the application architects and developers who involved in design and development of the product or web application, as they have to ensure that their web applications are performing efficiently and effectively under the huge load [24, 19]. The best test technique used to verify that the created web application will be able to handle this huge load is performance testing. Through performance testing we can ensure that the web application will handle the huge load at better performance effectively and efficiently. A performance testing is a technical investigation used to validate or determine the application or product responsiveness, scalability, flexibility, speed, stability characteristics of the product under test. Performance testing measures system throughput, performance and latency with a variety of concurrent user over long periods of time. Performance testing is normally most time consuming and expensive activity, but it helps mitigate risks of going into production. Performance testers/engineers all over the globe are binding the infinite potential of the cloud model to test the performance of their product/applications. The performance testing over cloud helps to conquer the issues and challenges of a test strategy that relies entirely on traditional/onpremises performance testing models [1]. Load or performance testing over cloud enables testing team to take a huge step forward in conducting more efficient and more realistic large scale tests. In addition, the organizations realized that considerable savings in cost and time made possible by cloud technology. 2. OBJECTIVE OF THE STUDY Performance testing is a tedious and complex activity where the dozens and dozens of factors involved to its success and the effective and efficient usage of all those aspects of performance testing are important to obtain the appropriate and accurate performance testing results. The performance test execution on production similar system or environment and all required resources availability to successfully run the test is essential. Creating the exact replication of the production system or environment is undoubtedly an important part of the whole testing activity as even the minor differences between the production environment and test environment can completely invalidate the test results. Any web application performance test results are purely depends upon the test environment configurations [7]. Many challenges and issues involved while choosing the accurate test environment [17, 22], We have many number of on-premises test environments available in the market to do the performance testing such as Performance Testing on Production Environment, Performance Testing on Scaled Environment and Performance Testing with Service Virtualization but all the above techniques have limitations and issues to implement the effective performance test, in this paper we proposed the effective and efficient test environment called Performance Testing over the Cloud to do the performance test well. The performance test on cloud environment will avoid the bottlenecks of on-premises model and provide the cost effective and time saving solution for performance test [13]. 3. ON-PREMISES MODEL On-premises software is installed and run on computers on the premises (in the building) of the individual or the business which uses the software, rather than used at the remote facility, such as in a cloud platform or server farm located somewhere on the internet. In performance testing point, On-Premises depict setting up the performance test lab in local environment where the organization resides. Performance test lab includes infrastructure, machines, hardware, software, CPU capacity, database server, network configuration etc [24]. The performance test lab set up should satisfy the production system 2

3 requirement, if suppose there are 2000 users are using the production/real world system then we need to set up our local Lab environment to support such 2000 user load. This on-premises approach to deploy and use the business software was the most commonly used model until around 2005, when software running on a remote location became extensively available and adopted. The latest, alternative deployment model typically uses the Internet to remove the need to install any software on premises and had other benefits [10]. Remotely running the software can bring considerable cost savings because of maintenance, reduced staffing, power consumption, and other considerable factors. Since the initiation of software runs on remote environment, on-premises software has sometimes called as old-style software, although it is still the preferred model in some organizations such as finance, insurance, defense and banking, where the ability to manage and secure data on premises that are locally owned/controlled is required [16, 18]. The first and the very basic step of on-premise performance testing are to set up a test environment. This will involve putting together a appropriate infrastructure, procure servers, software and hardware to host the load generation hardware and system under test. Setting up this kind of an environment would require substantial investment, time and efforts and has expenses such as maintenance and license costs. Also we need to engage administrators to maintain and support the test environment [18]. 4. CLOUD MODEL Cloud computing remains a hot topic in the IT industry as a model that provides computing resources on demand with reduced administration costs. The main service layers of cloud model are infrastructure as a service (IaaS), software as a service (SaaS) and platform as a service (PaaS). It supports an everything-as-a-service (XaaS) delivery model, providing Internet services ranging from security and databases to storage and integration [14, 15]. Cloud computing is changing the way we deliver and use the software; traditional software licensing is diminishing, whereas companies hiring software services is increasing [23]. In 2010, Gartner Research predicted that 20 percent of business would have zero possession of IT assets by 2012 and instead seek to attain assets from the cloud. Cloud-based services growth is apparent, but clouds should still go through development and testing before deploy them. Testing in cloud computing has comparatively low entry barriers. Now Cloud testing is carried out on demand and billed per use [25, 9, 2]. Many organizations already provide cloud-based testing services such as performance testing, load testing, and Webbased application testing, as well as the testing of environments hosted in the cloud. The key benefit of cloud-based testing is reduced costs for set up, maintenance, and licensing internal testing environments [8]. E.g. Amazon s cloud tested a network management system for a VOIP telephony system for less than US$ Other benefits include the flexibility to obtain a testing environment as needed and global market access for both vendors and clients. In spite of these benefits, other costs are less obvious and more difficult to evaluate [12]. Cloud testing requires unique technical skills for test case generation, test script generation, and providing and monitoring security may also involve additional costs [3]. 3

4 5. COMPARISON OF ON-PREMISES AND CLOUD MODEL We have analyzed the On-Premises model and cloud model benefits, restriction and challenges based on different performance test criteria in the below table. For detailed reference see [4, 5, 15, 21, 4, 20]. Table.1 Comparison of On-Premises and Cloud model based on Performance Test Criteria On-Premises Model Cloud Model Infrastructure Set up: Setting up the infrastructure such as Performance test lab, hardware, software, network connections, security bridges etc. 1. In On-Premises model, we need to establish the IT infrastructure by software domain expertise and solid backup and security strategy. 2. The performance lab set up will be more Obviously, if we start using testing in cloud services, we will save money and large amounts of time. 1. We can buy the performance test lab available in cloud providers based on the need. expensive when generating more user 2. We do not need to buy hardware for the new resemblance. Have to spend more efforts and time to set up the infrastructure. Conventional companies with the capability to build the required upfront investment to purchase and implement the software. Minimum timeframe to testing lab. Just continue using the same hardware we have and pay for service. 3. We won't have to hire support engineers for the new testing lab. So HR managers no need to spent additional efforts to hire a resource. do set up for an on-premise solution should be 4 6 years. 3. The organization should have several sites across geographic locations and should have a sustaining network infrastructure. Software Investment: Software investment involves software purchase, maintenance, license fee and software upgrades cost when new versions are introduced 1. Software license fee more expensive for the company to own the software. Upfront purchase with annual maintenance / subscription renewals in the 20 25% range. 2. A good canon of thumb is to spend everywhere from $1 - $2 for each dollar spent on the early software license. 3. Every months, the test lab needs to upgrade the software, technical support and business process consulting as necessary. 1. In cloud SaaS (Software As A Service) will provide the necessary software and we need to pay for this at initial stage of cloud set up [15]. 2. By using SaaS for load testing, we won't be tied to certain software because we can switch to another vendor anytime. There will not be any cancellation fee for switching vendors. Service providers thus provide excellent customer service to make sure we are happy. 3. In addition, the company can cancel their services with the vendor automatically. Long process of technical support of the SaaS vendor need not be followed while cancelling. Hardware Investment: Hardware investment involves CPU, Memory storage devices, device drivers, input/output devices, disaster recovery, network support cables etc. In On-Premises model, cost involved to set up In cloud only initial cost will be involved to buy 4

5 the traditional IT components including server such hardware needs. Cloud testing allows running hardware and software, data backups, storage, tests from anywhere the Internet connection and a disaster recovery, and remote access and browser is available. The cloud testing enable network connectivity. greater scalability and flexibility in work schedules and also potentially reduce the stress on the fact that the possibility of the internal testing lab break down. This helps ensure testing schedules remain intact. As a result of cloud testing, the chances of on time product releases will increase. Implementation Time: The time involved to implement the actual application in the performance test lab or production system. In On-Premises model, the time taken for implementation will be varies by scope and size of the project, but implementation time be likely to be a bit longer and most involved, conceivably adding 2 3 months to the timeline of a comparable cloud-based implementation. Configuration Set Up: 1. Need identify the system configuration details of the server machines in the target environment like the number of CPUs, CPU capacity (clock speed), RAM capacity, disk capacity, free space available in the disk, NIC card capacity and network bandwidth. The organization needs to put more cost and effort to achieve this configuration set up. Identifying and setting up the required configurations is more difficult since the organization space, time and resources may not be sufficient to reach the target load. 2. The organization needs to set up the required network infrastructure to balance the production user load. Such a complex network configuration is tedious, time consuming and most expensive process. Once the cloud test lab has been brought and ready to use then the implementation will be taken care by the cloud provider but the implementation time will be comparatively less from the on-premises model. 1. Need to request the cloud provider for system configuration like the number of CPUs, CPU capacity (clock speed), RAM capacity, disk capacity, free space in the disk, NIC card capacity and network bandwidth are needs to be considered to perform the load test [3]. 2. No need of spending effort and time to set up the system configurations, only concern is we have to pay for these necessary configurations. Database Set Up: Buying and setting up the data base servers based on the data load. There is a high possibility of risk where some database issues will be hidden if the product is not tested for predictable database volume. The table index and the order of record arrangement may create a huge performance impact on the product. 1. The execution time taken by SQL engine will be very less while loading the database with 1000 records, but when the database record volume has increased to 10000, then the execution time will have tremendous change in SQL execution engine and this time increase 1. In Cloud we no need to buy the SQL server on own, only we need to pay the lease amount for data base server. 2. No need to spend time, space and effort to set up the database server, only we need to identify and provide the data load details to the cloud provider. 5

6 will have an impact on fetching the data and processing the business logic on those fetched data. 2. Buying the SQL server will be most expensive when huge loads are involved. We need to spend more time and effort to set up the data base server based on the application requirement. Need to maintain the data base server space in our performance test lab. Performance Test Tool Set up Limitations: Normally we will use the test tools to do the performance test, so we need to set up the tools in our test lab before start the actual test. 1. When the performance test tool is configured to simulate 10 Virtual users, then the tool generates 10 threads or process (depending on the configuration setting of the tool) which sends the client requests to the server as per the recorded think time intervals available in the test script. The performance test environment should have enough hardware resources (CPU and Memory) to handle the running threads. 2. In turn to run a 1000 users performance test, suppose the load generators are installed on 5 different machines and configured to create 200 virtual users load on each machine. The user load fashioned on 5 different IPs were sent to the server, as the load generators are configured to execute the test scripts that are billed in the scheduler (controller), from where the test script is running. In cloud model, the adapted performance test tool will be configured to replicate 10 Virtual users in cloud lab machine, then the performance tool generates 10 threads or process (depending on the configuration setting of the tool) which will send the client/user requests to the server as per the recorded think time intervals available in the performance test script. The cloud provider will set up the system to have the enough hardware resources (CPU and Memory) to handle the running threads. Based on the load we need to pay for cloud lab. Scalability: If we need to increase amount of users for testing from 1,000 to 20,000 and then reducing back to 1,000 users [6]. In On-Premises model, it is a time consuming In cloud model, we can use the resources only for process to increase the number of machines on the purpose of actual performance testing and we demand and if suppose we have 2000 machine can simply select the amount of services we want on set up in our performance lab and only 1000 are an on-demand basis. So in cloud model we can buy needed then the remaining 1000 will be idle for the cloud lab based on the need, suppose if we need long time machine then we can pay only for 1000 machines to the cloud provider and can use those machines for our testing. If the machine need has reduced to 500 then we can pay only for 500 no need to hold all 1000 machines. So cloud based performance testing approach provides the greater scalability on performance test. Flexibility: Different levels of tests can be executed on discrete environments. 6

7 We cannot change the environment and cannot Different levels of tests can be executed on discrete carry out different level of test in one environments at the convenience of an enterprise. performance test lab, we need to wait for setting Performance testers no longer have to remain till the up the different environments to test different end of the testing phase stirred to a production-like types of tests. environment for their performance and stress tests. Instead such an environment can be brought into action at will. Cleaner and Greener Testing: Consideration on environment, time, and effort and resource usage. Suppose different organization needs the same set of performance lab to do their performance test then each organization has to set up their own performance lab, so the time, effort, cost, environment, resources will be more and it leads to environmental waste. Realistic Load: Test for the actual production load, that happen on a live production server. Testing the actual production load in on-premises model will be a very tedious task. Testing the performance of the application behind the company firewall is like we cannot test the DNS errors, no disconnections will be tested and no third-side traffic will be tested and simulating actual production load is a tedious task in traditional performance lab. Security: There will be very less data leakage or external access while the performance testing has been done on internal lab environment. It seems that the cloud computing facilities make it appreciably greener than traditional models and this is true for testing process. The cloud will eliminate environmental waste by just sharing resources such as infrastructure, software, hardware, network, storage, and disk on demand. By using cloud infrastructure, the consumers can minimize the usage of energy and save the environment on carbon-dioxide around 50%. response time, throughput, all sorts of errors Through cloud resources we can simulate real users who come directly from the Internet in cloud lab. And also we can be simulating the actual production load easily while testing in cloud. Security in the public cloud is still a big concern for organizations that are preferring cloud [11]. Cloud test is based on the internet. So it may come up to the situation about the leakage of private information, internet suspending, and service provider may suddenly announce disruption of service due to a maintenance window, virus attacks, slow internet speed and so on. Cost Reduction: The cost involved in setting up the lab, resource management, configurations etc.. In On-Premises model the cost is a major concern for all phases like setting up the When we are using the cloud model will reduce the cost by pay per use approach, this will reduce environment, resource management, environmental management cost. Most of the maintenance, software licensing etc companies moved to cloud because of this cost There is no word cost reduction involved in reduction factor. Cloud performance testing internal lab testing. Since everything we need to set up in our internal lab, no way of lease or leverages the cloud infrastructure, minimizing the unit cost of computing and increasing the efficiency 7

8 rental benefits. ISSN Print Real Time Test Data Usage: No real production data can be used for testing but still we will get some masked and simulated test data for our internal lab testing from customers. Accuracy: Measuring the performance test accuracy Here we cannot test different geographical location load, and the test will be carried out only on the predefined network and bandwidth. The test accuracy will be moderate in on-premises model. of performance testing. Cloud testing provides the cost savings usually range from 50% to 70%. Pay per use approach in cloud model provides the greater flexibility on performance testing. The management of test data is a fragile issue. For effective testing we are highly depends on the actual customer or production data. In some cases, due to rules and regulations, customers are banned from supplying confidential or production data to third parties. So the test data should be doubly examined for testing in cloud. The performance or load test will be carried out in different environment and different geographical locations. Only thing is we need an internet and browser to carry out the cloud test. Based on the above analysis, the Time, Effort and Cost involved in both On-Premises and Cloud model for each performance test criteria has been summarized in the below table. Table.2 Summary of Time, Effort and Cost involved in On-Premises and Cloud model Performance Test On-Premises Model Cloud Model Criteria Time Effort Cost Time Effort Cost Infrastructure Set up High High High Medium Low Medium Software Investment Medium Medium Medium Low Low Medium Hardware Investment High High High Medium Medium High Implementation Time High Medium Medium Medium Low Low Configuration Set Up High High High Medium Medium High Database Set up Medium Medium Medium Medium Low Medium Performance Test Tool Set up Medium High Medium Medium Low Medium 8

9 Low Low ISSN Print High Medium High Medium On-Prem Time Cloud Time On-Prem Effort Cloud Effort On-Prem Cost Cloud Cost Figure.1 Summarization of Performance Test Criteria Based on the above analysis, the performance test parameters like scalability, flexibility, realistic load, cost reduction, cleaner and greener testing, accuracy, security and real time test data are summarized in the below table. Table.3 Summary of Performance Test Parameters Performance Test Model Scala bility Flexibilit y Realistic Load Cost Reduc tion Cleaner and Greener Testing Accuracy Secu rity Real Time Test Data On-Premises Low Low Medium Low Low Medium High Medium Cloud High High High High High Medium Low Low 9

10 High Medium Low On-Premises Cloud Scalability Flexibility Realistic Load Cost Reduction Cleaner and Greener Testing Accuracy Security Real Time Test Data Figure.2 Summarization of Performance Test Parameters 6. CONCLUSION In this paper we have analyzed the benefits, challenges and limitations between On- Premises and Cloud Model to do the better performance test. We have analyzed several performance test criteria s like Infrastructure Set up, Software Investment, Hardware Investment, Configuration Set Up, Database Set up, Implementation Time, and Performance Test Tool Set up against On-Premises and cloud model. Based on the analysis the cloud model gives us a complete understanding of the final user experience and the investment on configuration cost, infrastructure set up cost will be reduced drastically. Cloud environment will provide scalability, flexibility, simplicity, comprehensive testing, cost reduction, cleaner and greener testing, greater control, realistic load test experience, Buy and go techniques over the performance testing. The cloud model is a perfect suite for non sensitive applications with respect to security and integrity. Different levels of tests will be done on separate environments at the convenience of an enterprise. Cost reduction is the major factor influencing companies to choose Cloud. Cloud Testing leverages the cloud infrastructure, minimizing the unit cost of computing and increasing the efficiency of performance testing. There are other values of response time, throughput, all sort of errors that happen on a live production server. And cloud testing services allow us to test our all important applications under these real-life conditions. In cloud testing the cloud computing resources are used to simulate the real user experience. REFERENCES [1]. European Commission, The New SME Defi ni- tion: User Guide and Model Declaration, Enterprise and Industry Publications, 2005; [2]. Foley. J, The Cloud s Next Big Thing: Software Testing, InformationWeek, 23 June 2009; [3]. Ganon. Z and I.E. Zilberstein, Cloud- Based Performance Testing of Network Management Systems, Proc. IEEE 14th Int l Workshop Computer Aided Modeling and Design of Communications Links and Networks (CA- MAD 09), IEEE CS, 2009, pp [4]. Gartner, Business Models in Global Software Ecosystem, executive summary, Finnish Funding Agency for Technology and Innova- tion, August [5]. Gartner, Gartner Highlights Key Predictions for IT Organizations and Users in 2010 and Beyond, press release, 13 Jan. 2010; 10

11 [6]. Henry H. Liu, Software Performance and Scalability: A Quantitative Approach [7]. Ian Molyneaux, The Art of Application Performance Testing, O'Reilly Media [8]. Imad Mouline, Ryan Breen, Performance Testing - Putting Cloud Customers Back in the Driver s Seat [9]. Iosias Jody, Cloud Testing Cred Press, 2011 [10]. Jeff McWherter; Ben Hall, Testing ASP.NET Web Applications [11]. JIAN ZHEN, Five Key Challenges of Enterprise Cloud Computing [12]. Kevin Roebuck, Cloud Testing, Emereo Pty Limited, 2011 [13]. Manish Dhote, Introduction to Cloud Computing Performance Testing: Basic, Concepts and Approach [14]. Mell. P and T. Grance, The NIST Defi nition of Cloud Computing, US Nat l Inst. Standards and Technology, Sept. 2011; csrc.nist.gov/publications/nistpubs/ / SP pdf. [15]. Melvin B. Greer, Software As a Service Inflection Point: Using Cloud Computing to Achieve Business Agility [16]. MICROSOFT ACE TEAM, Performance Testing Microsoft.NET Web Applications [17]. Microsoft Corporation, Performance Testing Guidance for Web Applications [18]. Ramya Ramalinga Moorthy, Software Performance Testing Handbook: A Comprehensive Guide for Beginners [19]. Riungu L.M, O. Taipale, and K. Smolander, Software Testing as an Online Service: Observations from Practice, Proc. 3rd Int l Software Testing, Verifi cation, and Validation Workshop (ICSTW 10), IEEE CS, 2010, pp [20]. Riungu L.M, O. Taipale, and K. Smolander, Research Issues for Software Testing in the Cloud, Proc. 2nd Int l Conf. Cloud Comput- ing Technology and Science(CloudCom 10), IEEE CS, 2010, pp [21]. Robert Mullins Robert L. Scheier InfoWorld Gomez, Risk In The Cloud What to do if our cloud provider disappears 12 Steps to Ensure Successful SaaS Delivery [22]. Scott Barber and Colin Mason, Web Load Testing for Dummies, Compuware special edition [23]. Scott Robert Tilley, Tauhida Parveen, Software Testing in the Cloud: Perspectives on an Emerging Discipline, IGI Global Snippet, 2013 [24]. Subraya B.M, Integrated Approach to Web Performance Testing: A Practitioner's Guide - IRM Press, 30-Jan-2006 [25]. Vengattaraman. T, Dhavachelvan. P, Baskaran. R, Model of Cloud Based Application Environment for Software Testing, (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 3,

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