Test Automation Forum

Optimizing performance of your E-commerce apps to ensure seamless customer experience

Introduction: E-commerce platforms are intricate and multi-layered systems that rely on several interdependent components, including servers, databases, networks, and application code. As these systems cater to many users and handle a significant volume of transactions, it is crucial to identify and address performance issues at an early stage. Doing so not only reduces the overall delivery cost but also ensures better user satisfaction. The failure of e-commerce systems during peak shopping periods, such as Black Friday, Cyber Monday, or holiday sales, can have severe consequences. It can result in lost more revenues, customer dissatisfaction, and damage to the brand reputation. However, it is not just limited to e-commerce platforms alone but can also occur in other critical systems such as Healthcare, Finance, and Entertainment etc. To avoid such detrimental outcomes, performance testing is essential. It allows developers to simulate real-world scenarios and identify any potential bottlenecks, scalability issues, or other performance problems. By running a series of tests, including load testing, stress testing, and endurance testing, performance testers can pinpoint issues and provide developers with valuable feedback to fix them. Performance testing helps organizations to ensure that their systems can handle high volumes of traffic and remain stable even during the peak loads. By detecting and fixing performance issues early on, businesses can avoid costly downtime, data loss, and reputational damage. Furthermore, by providing better user experiences, organizations can increase customer loyalty and improve their brand image in the long run. In summary, performance testing is a crucial part of software development that helps to identify and fix performance issues before they affect end-users. It is particularly essential for complex systems, such as e-commerce platforms, that rely on multiple interdependent components. By conducting thorough performance testing, organizations can ensure that their systems are stable, scalable, and provide a seamless user experience, even during high-traffic periods. Why is it essential to conduct performance testing on e-commerce platforms? Effective performance testing is critical to ensure that e-commerce platforms and other complex systems can handle high volumes of traffic and provide a seamless user experience. To conduct successful performance testing, testers must have a thorough understanding of the application’s architecture and its various components. The first step in performance testing is to create realistic scenarios that emulate real-world traffic and user behaviour. These scenarios should consider different user groups, devices, browsers, and network conditions. Once the scenarios are defined, load testing can be performed to simulate expected traffic levels and monitor the application’s performance metrics. These metrics include server CPU and RAM utilization, overall response time, and transactions per second. Stress testing should also be carried out to identify the breaking point of the application in terms of concurrent users. After rigorous testing, all the data from load testing and application performance monitoring tools must be gathered and analyzed to identify potential bottlenecks, slow-running queries, and methods that could affect performance under peak load. Front-end performance tests should also be conducted in parallel with load and stress tests to ensure the application’s user interface is responsive and meets user expectations. Popular performance testing tools available in the IT industry include WebLoad, LoadNinja, Apache JMeter, and Micro Focus LoadRunner. The results of the performance testing should be presented to the development team for analysis and comparison. Tuning should be performed until the system under test achieves the expected levels of performance. By prioritizing performance testing, e-commerce platforms and other critical systems can identify defects in the development lifecycle and reduce overall delivery costs. This approach can enhance the quality and performance of the project, increase processing speed, and improve data transfer velocity, ultimately providing a seamless experience for customers and increasing revenue. How to do effective performance testing? Effective performance testing involves a thorough understanding of the application’s architecture and its various components. The first step is to create realistic scenarios that emulate real-world traffic and user behaviour. These scenarios must take into account different user groups, devices, browsers, and network conditions. Once the scenarios are defined, load testing can be performed to simulate the expected traffic levels and monitor the application’s performance metrics. The metrics that need to be monitored include server CPU and RAM utilization, overall response time, and transactions per second. Stress testing should also be carried out to identify the breaking point of the application in terms of concurrent users. After rigorous testing, all the data from the load testing and application performance monitoring tools must be gathered to analyse the results. This analysis helps identify potential bottlenecks, slow-running queries, and methods that could affect performance under peak load. Front-end performance tests should also be performed in parallel with load and stress tests to ensure the application’s user interface is responsive and meets user expectations. To ensure a seamless experience for customers and increase revenue, e-commerce platforms must prioritize performance testing. Performance testing helps to identify defects in the development lifecycle, reducing overall delivery costs. The collapse of systems such as e-commerce can affect people’s digital quality of life, and failures can occur in all types of platforms, including health, entertainment, banking, and more. To conduct effective performance testing, it is crucial to understand the application’s architecture and the various components of its landscape. After creating the best possible scenarios to test, a performance test strategy can be developed. Load testing should be conducted by gradually increasing the load and monitoring performance while also monitoring server CPU and RAM utilization, overall response time, and transaction per second. Once load testing is completed, a summary report should be inspected to identify which requests are taking the most time. Stress testing can be conducted to find the breaking point of the application in terms of concurrent users. Data should be gathered from load testing tools and application performance monitoring tools to analyse results, identify the application’s breaking points and where its throughput got saturated with increasing load. Additionally, potential bottlenecks such as slow running queries and Java methods should be identified. Front-end performance tests should also be conducted in parallel with

Selecting the right Test Automation Tool for your organization

There are hundreds of test automation tools that are being offered in the market today and many new entrants are also coming to market every now and then which makes the tool selection process a bit cumbersome. Selecting the right automation tool will drive the success of your automation journey as the right tool will bring the desired outcomes like the productivity, cost savings and the speed to the market. Few of you might have already carried out this exercise in the past as well. In the current times of digital transformation, the factors that drive the tools selection process have changed considerably, because of the changes in software development models e.g., Agile, DevOps, shift-left etc. and also due to the emergence of the latest technologies like AI/ML, RPA and so on. In this article, we will discuss around how to choose the right automation tool for your organization. When we think of selecting a tool for our organization, it’s obvious that we have to consider other programs or projects outside our team. The projects/products outside our team might be using different technologies, different interfaces, services and so on and it is not an easy task to identify one tool to cover all the applications/products in the organization. So, we have to consider and analyse all the applications/products carefully and group them logically so that we can initiate our search for the perfect tool for each of the groups. This will ensure effective utilization of the tool in our organization for better and quicker returns on the investment, Prerequisites Before we proceed with initiating the selection process of automation tools, we must finish the detailed analysis of the scope of the automation i.e. applications/products to be automated, budget/cost, team composition/skillset, tools/platforms that are already in place in the eco system, company’s IT strategy etc., Once the automation scope analysis is completed, in order to kick-off the tool selection process we need to work on identifying the selection criteria for the overall evaluation process. The automation tool selection process generally follows a 4-step method as below: Stakeholders, roles and responsibilities Who should be part of the overall evaluation, review and final selection process? Well, for a structured, unbiased and an overall effective tool selection process, we strongly recommend you involve below members as part of the exercise: Test engineers Tech. Architect Test managers Project Managers BU Leader/QA Head (recommended for selection process for enterprise-wide rollout) A representative from your sourcing team (for a better negotiation/deal with the vendor at the later stage of your selection process) For a smooth coordination, a Test Lead or a QA Manager should own and champion this task under the guidance of a senior leader like QA Head or so. The above structure can be customized as needed depending on several factors like centralized/decentralized evaluation and so on. Before this task begins, ensure you have roles and responsibilities identified for each stakeholder in the overall evaluation process. Below is a sample RACI matrix for your reference. You can add/remove other stakeholders to customize it as per your Org structure or for any specific evaluation need. One more crucial point to be considered during the overall process is professional ethics. Senior leaders have a critical responsibility here to set some ground rules around how do we communicate and partner with the representatives of the vendors partners and guide the team as needed. The vendor partners should be dealt with due professionalism and transparency for the best outcomes. Each and every tool have their own advantages as per their designs. Our goal should be primarily focused on identifying our automation need and ultimately selecting the one that fits to most of our requirements and not finding faults with the individual tools. Identifying the selection criteria for the right automation tool This is the critical phase of the tool selection process. In order to make our selection process structured and unbiased, we need to evaluate all the potential tool candidates against the same selection criteria so that we have a common rating method to identify the best tool for our purpose. We will discuss about a template later in the article that captures the common selection criteria and the rating for individual tool candidates to find out the best tool. Below are several aspects or selection criteria of automation tools that you might consider as part of your overall evaluation process. The list might not be an exhaustive one; you have to add/remove/edit criteria based on your company’s automation needs, IT strategy, etc. Test coverage/Versatility: In today’s digital age, modern Apps/Products use complex architecture covering Web, Windows, Linux/Unix, Mobile, Databases, Web Services and so on. You have to ensure the tool you are picking up from the market has the ability to support the required end to end UIs/Layers of your app. We also recommend you to check if the tool can also help in doing other types of testing like Unit, Integration, Code reviews/performance checks, security scans, etc. Learning curve, scripting speed, maintenance effort and reusability: This criterion will help you evaluating the ease of adoption of the tool for your project/company. The skillset/competency of the current team, ease of developing/debugging the script and the script maintenance effort etc. are few important factors that you have to check to determine the right tool. Script reusability inside or outside your project is also a key factor. Script reusability will help driving the productivity of the QA team. You should also study the abilities of the tools around development of frameworks like Key-word driven, Data-driven or script-less models etc. that best fit to your need. Seamless integration with other tools: As we adopt more and more of processes like Agile, DevOps etc. the software development ecosystem becomes more diversified in terms of other tools (open source/commercial) that are used for different other activities like version control, build, testing, deployment, etc. as part of the overall development process. In this scenario, the test automation tool’s capabilities around talking to

Performance Testing & Engineering trends of 2020

1 Comment / Performance Testing, Full Automation Testing / By Abhishek Kumar

In this age of Digital Transformation, application performance has become the most important part of business. It is not just about page load or page speed, rather drives the business revenue by ensuring the software can process transactions in a responsive manner for a greater customer experience. Therefore, performance testing/engineering is emerging as a specialization in software testing space and software testers are encouraged to adopt multi-layered testing approach instead of traditional performance testing. In this article, we will talk about some of the best practices that will help testers to uncover different aspects of performance testing & engineering, at a high level. Let’s start with discussing about Test Strategy around performance testing and will also talk about some of the recent trends in Performance Engineering in the Industry in later part of this article. Building a Complete Test Strategy Performance Testing & Engineering requires deep technical knowledge about application & technology which is followed by detailed planning and preparations before execution of test. BA/Product owner, Business Owner, Application developer, Production Monitoring Team are the several participants in planning phase. During planning & strategy prep, we must consider including shift-left and shift-right load testing approach. a) Shift-Left Load testing Shift-Left testing means doing testing in early or every stage of development. It saves time and improves overall quality of application. It doesn’t require to wait until the end of development process to do performance testing for the entire application. b) Shift-Right Load testing Shift-Right testing has big impact on overall quality of application. Applying test practices to production means considering real-world users and their experiences into the development process. Right workload model & plan Right Workload model is always a challenge for Performance Test engineer. Test engineer needs to carefully define think time, pacing, Critical transaction and users’ Load. An inaccurate workload misguides the server optimization and sometimes it might also delay project deployment. Emphasis on baseline tests or one-user load test One-user load test is important for application baselining. It saves time and helps the tester to find defects in full load test. It isolates performance defects in early round of testing (Never forget to consider one-user load test in your plan). Identifying the performance bottleneck Identifying bottleneck is always a challenge for the tester. It requires deep technical knowledge and expertise. There are few techniques generally used by performance engineers: 1. Trend analysis It is a technique that is commonly used to find out the behavior of the data related to the frequency of the performance issues in order to find out the bottleneck. Performance bottleneck can be of various types such as consistent, fluctuating, increase and decrease. This analysis can be done on both client-side and server-side metrices. 2. Correlation It evaluates the relationship between different performance metrices in order to find out the bottlenecks. It is like comparing user’s response time graph with CPU graph during the test to uncover the performance issues or to do the analysis for the subsequent steps. 3. Comparison As the name suggests, here we compare the performance metrices of the baseline test with unacceptable performance test metrices. This helps in finding out the reasons of the bottlenecks. 4. Elimination Using elimination technique we remove certain components during the test to identify real bottlenecks e.g. removing web server and doing load test directly for the application server. Creating report Effective reporting of test results is one of the important & key task for a performance tester. Final performance test report provides detailed analysis and recommendations to the project team and also the business. All the stakeholders make their critical Go/No-Go decisions based on this report. Test report must include: Findings/observations Detailed description of performance test results Recommendations Defect details Sign offs Conclusion Performance testing requires deep technical skills for different technologies. The success of performance test depends upon how we plan and execute. I hope this article helps to outline few critical aspects of successful performance test planning & execution. Performance test engineers need to consider the above tricks and techniques in order to achieve significant performance enhancements of the application under test (AUT). I wanted to keep this article as a starting point to give you a summary around the latest performance engineering trends but keep checking this space for few more articles on performance testing & engineering shortly. 5+

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