Mobile Site Tester: Best Practices For Load Testing And Optimizing Performance On Diverse Mobile Networks

When an application development activity is about to be done, one test that is required to determine its readiness for deployment is load testing. This testing enables testers to assess how the web application performs under normal and peak-load scenarios, as well as identify the breaking point. Load testing is primarily used to validate that the web-based application meets the expected performance goals or objectives, which are typically specified in a service level agreement.

With a larger audience than ever before relying on mobile applications, load testing is essential for a mobile site tester to ensure that the application functions effectively under realistic load situations. In addition, load testing reduces the risk of application failure and increases the optimizing performance on diverse mobile networks.

This article on mobile website testing describes the techniques for performing the load testing process, its benefits, and best practices that mobile site testers need to follow to optimize performance on diverse mobile networks. Before that let us understand the basics of load testing first.

What is load testing?

Load testing determines if an application can efficiently manage real-world load situations without compromising its intended performance. It helps to discover possible bottlenecks in applications by simulating concurrent users and transactions under different load situations. During load testing, testers can monitor parameters including application response time, error rates, throughput, and server resource utilization.

Furthermore, it enables testers to set up tests for multiple system transactions, focussing on distinct portions of the application such as a sign-in page, a purchase page, etc.

Load testing can be performed in an environment that stimulates the production environment or in the actual production environment under predefined settings. The load can be defined in several ways, including the amount of requests and concurrent users. Finally, load testing can enhance application performance before delivering code to the production environment. 

How to analyze load testing metrics

Mobile Site Tester establishes various load-testing metrics based on the organization’s particular needs and goals. In general, the metrics listed below are used to provide baseline performance measures for applications under various load situations.

Response time

Most load tests analyze the application’s response time to a tester-specific request. If the response time is much longer than the set SLA, it indicates that load time degrades the user experience. Typically, the final amount is the average time taken to respond, which is usually expressed in seconds or milliseconds.

Error rate

This metric indicates the percentage of unsuccessful requests relative to the total number of requests. This error rate increases when the application is unable to manage it within a certain time frame. A high error rate suggests application resource limitations and ineffective error-handling approaches. 

Throughput

Throughput is the number of transactions handled in a given amount of time. A high throughput proves the application works well under high load. Load testing determines the system’s maximum throughput and identifies any bottlenecks.

CPU and memory usage

The behavior of these two attributes is monitored before, during, and after the load test, allowing teams to find unusual spikes or abnormalities in application resources. High CPU or memory use indicates code bottlenecks and a lack of hardware resources. CPU and memory use are generally measured as percentages.

Number of requests per second

This measure monitors how many requests the application receives per second. These requests consist of API requests, web page loads, document loads, and loads of images. 

Network latency

This metric defines how long it takes for data to travel between the client and the server. The larger the latency, the lesser the application performance would be. For example, networks with high latency take longer to obtain data from a server. Load testing can reveal this sort of network delay issue under various load scenarios. 

Techniques for mobile site testers for performing load testing

Stress Testing– Stress testing is a technique for evaluating the application under excessive loads to determine when it will fail or deteriorate. This aids in identifying the system’s breaking point.

Spike Testing– Spike testing is the technique of assessing the application’s performance during a rapid or dramatic spike in load. This approach assesses the application’s capacity to adapt to unexpected traffic surges and maintains its stability under abrupt usage spikes.

Endurance Testing (Soak Testing)– Testing the application under a heavy load for a long time is known as endurance testing. This assists in identifying persistent problems that usually only become observable after prolonged use, such as memory leaks, database locking, or other issues.

Baseline Testing– Baseline testing is the process of establishing a performance standard for the application under typical loads. It is critical for comparing future test results and monitoring performance variations.

Isolation Testing– Isolation testing focuses on discovering performance issues by isolating various components of the application. This helps to identify any particular cases of degradation in performance.

Concurrency Testing– Concurrency testing evaluates the application’s capacity to manage several users or processes attempting to use it at the same time. This assists in identifying possible bottlenecks associated with concurrent access, such as database locking or connection limitations.

Configuration Testing– This involves evaluating the impact of infrastructure changes on application performance by conducting load testing across various devices or application configurations. This involves testing various application versions, server types, and memory sizes. This aids in determining the best configuration for optimum performance.

Benefits of performing load testing

Identifying performance issues

Load testing can assist testers in identifying performance bottlenecks in the applications before deploying code into production, avoiding issues in the future. Slow database queries, loop circumstances that can have a significant impact on performance under demand, and infrastructure concerns are some examples.

Improve scalability

During a load test, the load progressively increases. This procedure assists in determining the moment at which the application performs inappropriately or deviates from the intended behavior. It also allows testers to evaluate their scalability efforts by adding more resources and increasing the demand.

Improves the user experience

Load tests discover application performance issues before features are released to production, ensuring that users receive the most optimized versions of the application. If underlying issues are discovered and addressed in advance, error rates and response times can be considerably decreased.

Reduce unnecessary costs

Application failures or unresponsiveness might occur when there are unexpectedly significant user loads. These interruptions might result in considerable financial losses for the organization. Load tests assist testers in preparing the production environments for such situations by improving the code, networking, and infrastructure for peak performance.

Reduced risk for system downtime

It may be used to identify scenarios that could lead to a system failure. This makes it a great option for identifying solutions to high-traffic issues.

Limitation of performing load testing

• Load testing can be difficult, necessitating specialized knowledge and experience to set up and perform successfully. Teams with limited resources or experience may find it challenging to perform load testing.

• Performing load testing can be resource-intensive, necessitating extensive resources to simulate many users. This can make it costly and time-consuming.

• Simulating real-world usage is tough, as is predicting how users will interact with the system. This makes it difficult to predict whether the application will manage the anticipated load.

• Load testing focuses on the system’s performance under stress, therefore it might not be able to detect all sorts of issues or defects.

• As it formulates a huge number of data, analyzing the results and figuring out the reason for performance issues will become a difficult task.

Best practices for optimizing the performance of mobile sites across various mobile networks

When it comes to load testing and optimizing the performance of mobile sites across various networks, several best practices can help ensure a smooth user experience. Here’s a comprehensive guide:

Develop Realistic Scenarios

Developing realistic scenarios is one of the key approaches in load testing since it involves the process of thinking like a user, such as which applications are crucial to the users. By conducting it realistically, organizations may gain a better understanding of how the application will behave in production with real users. This practice allows testers to comprehend the minds of real users to some extent.

Determine the Metrics

There is no standard checklist of metrics since it varies depending on the application, technology used, and environment. Some frequent criteria include user-perceived response time, geographically specific response time, resource utilization (CPU, memory, disc, bandwidth), error count, maximum user capacity, and other performance metrics.

Design Load Test with Existing Data

When designing the load test, mobile site testers can engage other teams to collect historical testing data. This can be useful for obtaining data on page views, peak sessions in a specific hour, and the number of concurrent users. Using this data will help testers understand how to set up the load test to ensure that the load test is accurate and resembles website and application usage.

Test early and regularly

Whether the team is adopting an agile or DevOps approach, it is critical to test frequently and at the beginning. After completing the development task, frequent performance testing must begin. Nowadays the rise in feedback throughout the application development life cycle has been helpful in quickly identifying and resolving problems.

Leverage the Real-life Data

Use existing data to create realistic situations and benchmarks. Reusing data using monitoring tools might assist in clarifying what “realistic” implies in certain situations. As a result, in most circumstances, monitoring the tools involves both proactive and reactive operations.

Analyze the Test Data

The first step in running and analyzing data is to identify issues and take the required actions to fix them, which includes associating performance bottlenecks with code to establish the main cause of the problem. When utilizing standard testing tools, it might be difficult to translate test findings into data that can be used and shared with the development team to identify the issues.

Targeting the Right Workload

Ultimately, never test the application on a wide scale; it is unnecessary to push the platform beyond what is required. Developers should primarily focus on determining the appropriate workload that the program will encounter in production.

Understand Mobile Network Conditions

Be aware that mobile users can connect using Wi-Fi, 2G, 3G, 4G, and 5G, each of which has different latencies and speeds. To see how the website functions, use tools to simulate various network circumstances and speeds.

Choose the Right Testing Tools

For load testing use tools that can simulate real user interactions and load, such as Apache JMeter, Gatling, or BlazeMeter. Additionally, use performance monitoring tools such as WebPageTest, GTmetrix, or Google Lighthouse to analyze performance and pinpoint bottlenecks.

Alongside the load testing and performance monitoring tools, utilizing platforms like LambdaTest which is primarily known for cross-browser testing. It offers cloud-based testing functionalities; leveraging this platform, testers can test their websites under various load conditions while optimizing performance on diverse mobile networks.

LambdaTest is an AI-powered platform for test orchestration and execution, allowing for the large-scale execution of both automated and manual tests at scale. With the platform, testers can also perform automated and real-time testing on over 3000 environments and real mobile devices.

Moreover, it is an ideal option for providing testers’ Selenium automated testing to cloud-based infrastructure, which not only helps testers boost test coverage across numerous desktop and mobile browsers but also allows them to reduce test execution time by executing tests in parallel.

In addition to load testing, testers can also perform Selenium mobile testing to monitor the performance of the web application across diverse mobile environments.

Conclusion

Load testing is a critical component of optimizing analysis in mobile networks. By simulating high volumes of network traffic, load testing helps optimize network performance, validate protocol behavior, identify scalability issues, and evaluate network resources.

To ensure effective load testing, it is essential to design realistic test scenarios, set up an accurate test environment, generate and simulate diverse traffic, monitor performance metrics, and test the network’s scalability. Following the above best practices organizations can further enhance the effectiveness of load testing, and ensure reliability, scalability, and performance on diverse mobile networks.