Distributed testing involves breaking a test into multiple segments, each executed on a separate machine. Learn more!
OVERVIEW
Distributed testing is the testing type that uses multiple systems to perform load and stress testing. This test is applied for validating and verifying the websites and server applications when working with diverse users simultaneously. It is not a new concept but has significantly evolved in recent years due to the rise of modern software technologies and testing methodologies in line with a surge in complex software applications.
The complexity of software applications signifies new features, advanced behavior, and updates. Significantly, these software applications perform seamlessly across different devices, platforms, browsers, network conditions, and others. To ensure the above functionality, we must perform a robust test that checks its functionality and performance and saves testing time and effort.
However, the testing of software applications may become challenging when done in a centralized testing environment. Some of the challenges may be incurring more testing time, testing effort, and delay in the release of the application. A more scalable and efficient solution is required to effectively test complex applications, and to this, distributed testing is the perfect answer.
With distributed testing, the test is bifurcated into different parts, and each is executed on separate computing nodes, and simultaneous tests are executed on different systems. These test components interact with one another during execution.
Distributed testing involves breaking a test into multiple segments, each executed on a separate machine. This configuration is necessary because a distributed test case comprises various components that interact with one another, with each component being processed on a distinct system. What distinguishes distributed testing is precisely this interplay between different test case elements.
Typically, the focus lies on testing the interaction between different computer systems, such as evaluating a client-server application or the configuration of a file system. All the test cases for distributed testing processed across various processors collectively contribute to a unified result.
This differs from simultaneous testing, as even though simultaneous testing involves the execution of different test case components on separate processors, they do not interact with one another or with the processors. As mentioned earlier, this interaction factor sets distributed testing apart.
Distributed testing is an important part of software testing for modern software application development. Here are some of the reasons why it matters.
Knowing when to employ distributed testing is crucial to harness its benefits effectively. Consider the following scenarios when distributed testing is particularly valuable:
In distributed tests, having an effective test scenario is very important. The test scenario outlines all the test cases and elucidates their processing methodology. In a distributed test environment, you can use directives to define and control how your tests are run across multiple machines or nodes. These directives are instructions or commands that specify how the testing should occur.
However, setting up the hardware environment and network connection is essential before executing the distributed test. Once the hardware environment is established and network connections among various systems are set up, the next step involves specifying the approach for executing the test cases.
In the case of serial test case processing on a local machine, no directives are required—you just need to have a sequential list of test cases for processing. However, the test scenario introduces a potent capability for defining tests that may need repetition, either a specified number of times or for a duration. Directives allow you to distribute this load across multiple systems.
In distributed tests, remote or distributed directives are used to know which test cases have to be distributed and executed. These are the directives that are leveraged by the testers to define which part of test cases will be executed in which system. This, in turn, allows for the running of multiple tests concurrently and orchestrating and managing the execution of test cases.
Additional directives enable testers to run multiple tests concurrently, enhancing their capability. Furthermore, these directives can be nested within one another, allowing for complex configurations. For example, parallel and remote directives can be combined to facilitate simultaneous testing, where distinct tests are executed on different systems simultaneously.
The distributed directive serves as the means to specify distributed tests, and the scenario file having this directive is read by a controller. The controller's role involves allocating distinct sections of the tests to separate control services. Let us learn this in detail in the below section.
The architecture of distributed testing generally involves different components and communication flow in a distributed test environment. To know these in-depth, it is important that you know exactly how it works.
Components Involved:
Architecture Flow:
It is important to set up a distributed test environment. It involves an extensive process, including configuring software and hardware components to execute the test.
Here, we will discuss the crucial aspects of setting up such an environment that supports efficient testing.
Hardware Requirement
To start with the setting up of the test environment, the first step involves careful evaluation of the hardware requirement, addressing the need for testing projects like the scale of the test, the complexity of the application, etc. The tester shouldn't skip it because the evaluation will guide them in selecting servers, workstations, storage devices, etc.
In addition, hardware configuration also includes an approach where testers allocate the resources effectively. This involves the distribution of CPU, memory, and network bandwidth to ensure the accurate function of the system. This approach aligns with the expected workload. It indicates that the distribution of resources can be done based on the workload.
Software Requirement
In setting up a test environment, fulfilling software requirements is equally important. In this phase, testers ensure that all the machines or systems used for distributed test environments have compatible operating systems. It is important that both master and slave nodes have compatible OS so that there is no incompatibility issue during the test process.
Further, on the software side, testers install and configure the selected automated tool or framework to synchronize in terms of versions. This is required to ensure they are suitable for distributed testing and compatible with your chosen software stack. To maintain communication between the distributed test environment, network infrastructure analysis is done for factors like latency, security, and bandwidth.
Configuration of Test Environment
When testers have met the software and hardware requirements to perform testing, the next step is configuring the test environment. Typically, it involves replicating production settings, mirroring server configurations, database schemas, and network parameters. This involves some of the key steps, which are as follows:
In the configuration of test environments, major challenges can be encountered, like resource conflict, data contamination, and network interference. To avoid such, the use of virtualization or containerization technologies is recommended for environment isolation. Testers also do network segmentation that ensures that test environments remain distinct and insulated from each other.
Scalability Considerations
Lastly, scalability considerations are essential, especially in the dynamic testing landscape. This involves assessing potential workloads, devising a scaling strategy to accommodate changing demands, and planning resource scaling by adding or reducing hardware or virtual nodes as required.
With all software and hardware requirements in place for distributed tests, this also involves robust test planning. This planning is comprehensive preparation and strategic decision-making to ensure that all the testing efforts are required to meet your software development project and give accurate test results. Here is the way for testing planning for distributed tests.
Test Strategy and Objectives
The testing of software applications must have a clear objective and test strategy so that the QA analysts and developers in a team can keep tracking the progress. You must highlight the underlying goal of the test, like validation of specific functionality, ensuring compatibility for browsers, devices, and OS, or verifying the performance of the software application under load and stress. The goal can vary, and based on this, the test strategy is prepared by considering factors like the criticality of diverse test scenarios. This creates a roadmap for the team to follow.
For example, if your objective is to test a web application's scalability, you might prioritize load testing over other types of testing. Conversely, if the primary goal is to find critical functional defects, functional testing might take precedence.
Test Data Management
In this phase, data distribution is important for distributing the test data across different nodes in the established test environment. No matter if your test node is a remote machine or virtual system, the testers performing distributed tests should have a consistent data source for the test scenario. You can use synthetic or production data to create controlled testing environments and realistic scenarios. This helps replicate real-world conditions and ensure consistent test results.
Test data management also ensures data privacy and security issues, mainly when testers work with confidential data in distributed testing. Here, data masking or anonymization techniques are used to protect the sensitive data and its integrity for testing purposes.
Test Case Selection and Prioritization
Selecting and prioritizing test cases in a distributed test environment is a strategic process that optimizes resource utilization and test coverage. First, you have to prepare the test cases based on finding which test scenario is critical and appropriate for your software development goal. However, several test cases must be executed; you have to prioritize those based on criticality, allowing for early detection of critical issues.
Several factors influence test case selection and prioritization, including:
The central part of distributed testing is to execute the different test cases parallelly. For instance, if you have a suite of test cases for various functionalities of a web application, you can identify subsets of test cases that can run independently without dependencies on one another. By running these subsets concurrently on different test nodes, you can significantly reduce testing time and expedite the feedback loop in your development process.
In the distribution testing process, the execution of tests in the distribution environment is essential because this involves running multiple test cases in various test nodes. Let's explore how this process works:
To perform distributed testing effectively, we must ensure the following three prerequisites:
Parallel Test Execution
To perform distributed testing, different selected test cases are executed on multiple machines to lower the testing time and effort. For example, if you have a suite of 100 test cases, you can divide them into smaller groups and execute each group on separate test nodes. This way, instead of running one test case at a time, you can execute 10 test cases concurrently on 10 different nodes.
In this process, the major challenge involves conflict with resources. To avoid this, concurrency control is recommended to manage the test execution parallelly. For example, if two test cases require access to the same database, concurrency control mechanisms ensure that they don't interfere with each other, potentially leading to inaccurate results.
Load Distribution Strategies
Load distribution is a key strategy for distributing user loads evenly across different nodes in a distributed test environment. In the test process, it’s important to maintain the stability of work and function of other machines or nodes and ensure that no single node creates any issue or blocks the complete process. To ensure this, different strategies are used:
Handling Synchronization
The most significant obstacle in distributed testing is ensuring that all tests are executed on all systems in the correct sequence. To address this challenge, synchronization methods for the test cases are used. Techniques like mutexes, semaphores, or explicit synchronization commands control the flow of test execution.
Synchronization can happen automatically, initiated by predefined system checkpoints (such as the start and end of each test case), or manually at intervals specified by the user.
Distributed testing poses a dual challenge: synchronization and managing the testing process itself. This encompasses activities like configuring remote systems, generating scenario files, and processing the results to produce meaningful reports. Equally important is the ability to consistently replicate tests and choose which tests to repeat based on their outcomes, especially for regression testing. This repetition must occur consistently across various platforms, including UNIX, Windows, and Linux.
Monitoring and reporting in distributed tests is one of the most critical steps. It is conducted to ensure that the test process is monitored for real-time detection of issues and to have a report on the test result. Let us now understand the process in detail.
Real-time Monitoring of Distributed Test
Real-time oversight of distributed test processes involves ongoing tracking of the progression and performance of test execution across multiple test nodes. This continuous monitoring is crucial for quickly identifying and addressing issues as they arise.
Integral aspects of real-time oversight include:
Real-time monitoring allows testing teams to respond to issues promptly, re-run failed tests, and make informed decisions to ensure the accuracy and reliability of test results.
Logging and Handling Errors
Encountering errors in distributed testing is a common phenomenon. However, logging and managing errors is the needed activity that allows the team to capture and handle them related to test execution. This is how it can be done:
The team has the important role of handling those issues in a way that does not impact the overall testing process. Thus, the error is handled in a controlled manner where other tests continue to run. For this, the team thoroughly documents the failure by recording all relevant information and context.
This documentation can include the steps leading up to the failure, the expected outcome, and the observed behavior. Thus, logging and error handling help troubleshoot the issue and ensure the development of thorough test reports.
Generating Comprehensive Test Reports
The final step involves the generation of test reports based on the collected information from logging, error handling, etc. The test report has detailed information and views on the testing efforts, test outcomes, and any issues. Here are the key components of the test reports:
Test reports may provide insights into trends and analysis, including identifying defect trends, regression testing results, and comparisons with previous testing cycles.
Distributed testing can be leveraged using software testing tools that simplify the test process across multiple machines and different test environments. The tools also help in the effective management and execution of the test cases in parallel, which in turn also ensures test coverage and gives accurate test outcomes. Here are some of the popular testing tools that can be used to perform distributed testing:
Explore this comprehensive guide to understand what is Selenium and its functionalities.
Also, if you want to run distributed tests using the Selenium grid, we recommend you to check our tutorial - Selenium Grid 4 Tutorial For Distributed Testing.
Furthermore, you can use Selenium 4 to perform Selenium automation on cloud-based testing platforms like LambdaTest, which offers a scalable online Selenium grid. It is an AI-powered test orchestration and execution that provides automation testing on over 3000+ real browsers and operating systems. With LambdaTest, you can significantly speed up your release cycles by conducting tests in parallel. In fact, you can reduce test execution times by over tenfold, which is a substantial improvement in efficiency and productivity.
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Note : Run Selenium tests with TestNG across 3000+ real browsers. Try LambdaTest Now!
In the above section, we have seen many different testing tools that can be leveraged to perform distributed testing. However, the primary challenge testers encounter is choosing the right tool for the software projects. Here are some key considerations to be addressed while selecting the right tool to run distributed tests:
Now, let us learn how to execute distributed tests.
JMeter is a widely used open-source tool designed for load and performance testing. It is particularly popular for distributed test scenarios because of its scalability and flexibility. Here, we will use JMeter as an example to demonstrate how to run distributed tests. Examining the process of distributed load testing using JMeter, a well-known open-source load testing tool, involves three primary components: the master, the slaves, and the target system.
To distribute the load effectively, multiple slaves can be employed, all following commands issued by the master. The JMeter GUI runs exclusively on the master machine, overseeing test monitoring and report generation. The master doesn't generate the load itself but rather orchestrates the slave machines to do so. A noteworthy challenge arises with JMeter since the master and all slaves must be on the same network subnet.
Additionally, due to JMeter's limitations of handling only around 500 simultaneous requests, scenarios necessitating load testing for hundreds of thousands of users demand multiple machines equipped with JMeter servers. Given that such an approach isn't always practical, extensive load testing for large user volumes requires utilizing cloud-based load testing tools.
Here is the step-by-step process to run distributed tests using JMeter.
Prerequisites:
In distributed testing, the security of the data, system, test environment, access control, etc., has a significant role. The reason is an expansion of test activity across multiple nodes, environments, systems, etc. We know that in distributed testing, different data are shared between the nodes and the system.
Such data may be sensitive or proprietary data related to software applications being tested. Thus, it is important to ensure the security and privacy of the data during the execution of distributed tests.
Some of the key security challenges that occur while running distributed tests include the following:
To navigate the intricacies of distributed testing while upholding security, consider adopting these best practices:
Distributed testing represents the shift in the software testing approach as it offers a robust way to verify and validate the functionality of the software application in a short time. In this guide, we have comprehensively discussed about distributed testing, its key aspects, best practices, etc .
Furthermore, we have highlighted the importance of addressing security challenges, as data privacy and access control become paramount when testing across distributed nodes. It is imperative to adopt secure coding practices, robust network security measures, and data protection protocols to mitigate risks effectively.
It is recommended that organizations use distributed testing in their test plan for faster release of the software applications in the market, identifying critical issues and fixing them in the early stage of development. By adhering to best practices and leveraging the tips provided, testing teams can navigate the intricacies of distributed testing with confidence.
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