What is Synthetic testing & How Does It Work

Synthetic testing, also known as synthetic monitoring, is a process for simulating real user traffic to detect performance issues in critical user journeys. Synthetic testing is used by organizations in active monitoring, including service availability and application response times, and whether customer transactions are functioning correctly. This guide will walk you through everything you need to know about conducting synthetic testing. Let's get started.

What is Synthetic Testing and Why is it Important?

Synthetic testing is any form of testing that uses artificial scenarios to look at system or application performance. Synthetic testing will be all the more important as there is an increasing demand to deliver software quickly, along with requirements to have high-quality and reliable software. This is why it matters:

·         It helps identify potential problems before they become major issues.

·         Assures the reliability of an application and improves the user experience.

·         Performance benchmarks that optimize system performance and scalability.

·         It minimizes the time lost on application failure.

·         It helps the enterprise fulfill the SLAs and thus does not damage its brand value due to poor performance or inaccessibility of an application.

How Does Synthetic Testing Work?

Synthetic testing is generally automated and is used to test the performance and functionality of a software system or application. It carries out virtual requests to simulate real users' behaviour and measures the response times, scalability, and other performance indicators. Scripts need to be developed that define user actions, such as clicking links and filling out forms, and need to check how long it took for the response. Such scripts can be executed again and again with verification of consistency in the results.

However, synthetic testing can also be conducted manually, particularly during the initial stages of testing or when validating specific user journeys or edge cases. Manual testing may be used to validate automated test results or assess scenarios that require human judgment or creativity.

Benefits of Synthetic Testing

Let’s delve into the specific benefits of synthetic testing.

1. Identify Performance Problems Early

By conducting synthetic testing early in the software development lifecycle, developers can identify and address potential issues before they become significant problems. This proactive approach leads to high-quality, reliable software that meets user expectations.

2. Enter New Markets with More Confidence

By emulating real-world scenarios in diverse geographic locations, the companies ensure that their applications are ready to be taken to new markets. This in turn minimizes application failures or downtimes, thus providing a path to confident expansion.

3. Enable Frequent Code Deployment

It detects performance issues that may occur in advance and ensures that changes in the code do not have a negative impact on application performance. This in turn provides for the continuity of code deployment, whereby companies can bring in new features and updates at a faster rate with assurance about the quality and reliability in software.

4. Reduce Mean Time to Resolution (MTTR)

The faster the detection and diagnosis of a performance problem, the sooner developers can resolve it. This minimizes MTTR-mean time to resolution-reducing downtown and making sure applications stay up and functional.

5. Consistently Meet Performance Standards

Maintaining optimal application performance under varying conditions is essential for consistently meeting performance standards. This ensures that companies can deliver high-quality, reliable software, giving them a competitive edge.

6. Achieve Performance Targets Efficiently

By establishing performance benchmarks and optimizing system performance, companies can meet performance targets effectively. This also ensures that applications remain performant even under heavy traffic loads.

7. Support Agile Development Practices

Synthetic testing supports agile development practices by enabling continuous testing and providing quick, reliable feedback to developers. This enhances software quality while allowing for faster releases and shorter development cycles.

Synthetic Testing Challenges

Though beneficial, synthetic testing does have a number of challenges that need to be dealt with for maximum output.

1. Difficulty in the Design of Test Cases

The test case development for all the possible user actions and scenarios is tough to develop for an application with higher complexity. Though the capture and playback tool helps in recording the user's interaction with the application and based on that creates the test cases, this may not be a complete reflection of real users and may omit important scenarios.

2. Keeping the Test Scripts Up-to-Date

This is because the test scripts are subject to change with every upgrade of the application or system being tested. For instance, any change in the UI or the flow of an application may need changes in test scripts. Failing to update the scripts can lead to errors and inaccurate results.

3. Handling Dynamic Content

Synthetic testing can struggle with dynamic content, such as generated data that changes frequently and needs to be accurately captured in test cases. For example, if an application generates user IDs, transaction numbers, or timestamps, synthetic tests must account for such dynamic content to ensure accuracy.

4. Test Data Management

The quality and accuracy of test data can significantly impact the results of synthetic testing, making the management and organization of test data crucial. Test data used in synthetic testing should closely represent the actual data used in the live environment. Poorly managed test data can lead to test case failures and errors.

5. Integration with Other Tools and Systems

Synthetic testing should be integrated with other tools, systems, and workflows to enable automated continuous testing. This integration can provide a comprehensive view of the application's performance and improve the accuracy of testing results. However, integrating multiple test tools can present challenges, such as compatibility issues, data storage problems, and management complexities.

Types of Synthetic Testing

There are two main types of synthetic testing:

Browser Tests: Such tests emulate all sorts of user interactions and behaviors in a web application using browsers. Performing end-to-end testing of how the pages load, render, and respond. This test needs to ensure all things work correctly across various browsers and devices.

API Testing: This section primarily needs APIs for their performance, functionality, and reliability testing. The testing of API endpoints involves expected responses and data integrity, along with response times under different conditions.

Synthetic Testing vs. Real User Monitoring (RUM)

There are two methods of testing the performance of a software application: Synthetic Testing and Real User Monitoring. Synthetic testing just emulates the action of users on an application, targeting functionality, performance, and security. In contrast, RUM involves monitoring real-time interactions with the application.

Synthetic Testing Requirements

Several requirements are essential for performing synthetic testing effectively:

·         It needs to have an awfully similar test environment to the actual live environment for it to offer accurate results.

·         Test data used should be realistic, relevant, and up-to-date.

·         Test scripts should be written in a structured manner, laying out possible user actions and scenarios.

·         The testing tools must be efficient, accurate, and capable of supporting different types of testing.

·         The testing process should be based on relevant metrics that allow the team to track and analyze performance data.

·         The testing team must be skilled and experienced in synthetic testing to ensure proper execution and interpretation of results.

·         A well-structured test execution plan covering all scenarios and aspects of the application is crucial for achieving useful results.

Synthetic Testing Best Practices

Here are 15 best practices to consider for synthetic testing:

·         Clearly define the testing objectives to ensure alignment with business goals.

·         Choose reliable, up-to-date, and scalable testing tools that are compatible with other systems.

·         Implement version control systems to manage changes to test data and scripts, ensuring consistency across test cycles.

·         Develop scripted tests with a clear and concise structure to reduce maintenance efforts.

·         Automate test cases where possible in order to increase the efficiency and reliability of the testing process.

·         Create test cases that will handle the various scenarios of negative, edge, and result expected testing.

·         Ensure that test data used in synthetic testing mimics actual data, including variation, complexity, and sensitivity.

·         The test cases should be prioritized, keeping in view the level of risk associated with a particular functionality. This would lead to much better efficiency of testing.

·         Embed continuous testing into the software development lifecycle for non-stop performance monitoring and issue detection.

·         Continuously monitor test results for performance issues or bugs; analyze for patterns and trends.

·         Validate test results against multiple sources, including user feedback, monitoring tools, and industry benchmarks.

·         Foster collaboration across teams, including development, testing, and product teams, to establish common goals and prioritize testing efforts.

·         Partner with external testing services to supplement in-house resources and support broader coverage.

·         Establish standardized testing practices within the organization to ensure consistency, repeatability, and accuracy of test results.

·         Continuously assess and improve testing processes to align with evolving business needs and adopt the latest practices and technologies.

Synthetic Testing Examples

Example 1: Simulating a User Login Journey

Objective: Test the entire user login process, from entering credentials to accessing the account dashboard.

Steps:

·         Simulate a user entering a username and password.

·         Submit the login form and navigate to the account dashboard.

·         Verify successful login by checking for a welcome message or account details on the dashboard.

Expected Result: The application should authenticate the user and provide access to the account dashboard without any delays or errors.

Example 2: Testing the E-Commerce Checkout Process

Objective: Ensure the checkout process in an e-commerce application functions smoothly and accurately.

Steps:

·         Simulate adding items to the cart.

·         Navigate through the checkout process.

·         Complete a purchase by providing payment and shipping information.

Expected Result: The application should successfully process the purchase and provide a confirmation message and receipt to the user.

Example 3: Verifying API Response Times

Objective: Assess the responsiveness of an API by measuring the time it takes to respond to requests.

Steps:

·         Send a series of API requests to various endpoints.

·         Measure the response times for each request.

·         Compare the response times against acceptable time frames.

Expected Result: All API endpoints should respond within acceptable time frames, ensuring a smooth experience for users relying on the API.