Challenges in synthetic monitoring

Synthetic monitoring plays a crucial role in mimicking user interactions within a website or application to measure its performance, availability, and efficiency. It is an essential tool for businesses to ensure that their online presence is running smoothly and delivering a flawless experience for users. Although it presents numerous benefits, there are certain challenges that come with its execution. These difficulties stem mainly from the characteristics of simulated tests and the resources needed to uphold a strong synthetic monitoring system. Acknowledging these constraints is crucial in effectively utilizing synthetic monitoring alongside other monitoring methods.

In this article, we will discuss the key challenges faced in synthetic monitoring and how organizations can overcome them.

1. Scripting and maintenance of test scenarios

Applications frequently undergo UI changes, feature updates, and workflow modifications, which often break synthetic test scripts and lead to false alerts. Any changes made to the application's interface can cause these scripts to fail, resulting in inaccurate monitoring. Keeping these scripts up-to-date and maintaining them is a time-consuming and resource-intensive task that demands constant attention from developers.

Solution: Organizations should consider adopting scriptless or low-code synthetic monitoring tools that simplify test creation and reduce reliance on specialized skills. Designing modular, reusable scripts and automating script validation can also help catch failures early. Additionally, maintaining close collaboration with development teams ensures that monitoring scripts stay aligned with application changes.

2. Lack of real-world insights

Synthetic monitoring simulates predefined scenarios and cannot capture unpredictable user behaviors, edge cases, or real-time user context. Every user has a unique browsing behavior, and it is not possible to simulate all the different scenarios that a real user may encounter. This can cause gaps in the monitoring data, making it difficult to identify and troubleshoot issues and leading to false positives or false negatives, where the monitoring solution may report an issue that does not actually affect real users, or miss an issue that is impacting real users.

Solution: Combining synthetic and real user monitoring data can pave the way in providing a holistic view of user experience, covering both expected and unexpected behaviors. While synthetic monitoring helps to provide a simulated view of web app performance based on predefined test scenarios, real user monitoring collects data from actual users, providing a more accurate picture of the user experience. Regularly update and diversify synthetic test scenarios based on user behavior analytics and feedback from these monitoring solutions can help in obtaining a comprehensive view of their website or application performance.

3. Complexity of modern web applications

With the rise of dynamic and interactive web applications, it has become difficult to accurately simulate user behavior and interactions. These applications use complex frameworks and technologies, making it challenging to replicate real user experiences. Modern applications often include dynamic content, personalization, and A/B testing, which are difficult to simulate accurately with static synthetic tests. As a result, synthetic monitoring may not provide an accurate representation of the actual user experience.

Solution: Designing synthetic tests that can handle dynamic data inputs and variable content and incorporating advanced scripting and simulation techniques to accurately mimic user behavior and interactions can be helpful as they have the ability to monitor multiple layers of the application stack, including front-end, back-end, and third-party services, providing a comprehensive view of the application's performance. Also, complementing UI tests with API monitoring can be helpful to validate backend functionality independent of UI changes.

4. Geographic inaccuracy

Synthetic tests run from fixed monitoring nodes, which may not represent the diverse geographic locations of real users. While synthetic monitoring can simulate user interactions from different locations, it may not accurately reflect real-world conditions like varying network speeds or connectivity issues. This can cause inaccurate performance insights and misleading results, especially for global applications.

Solution: Choose a monitoring solution with a global network of test nodes to simulate user experience from different branch offices can be helpful to analyze performance from multiple geographic locations. Incorporating insights from Content Delivery Networks (CDNs) and network providers can also be beneficial to better understand regional performance factors.

5. Resource overheads

As applications grow, ensuring synthetic tests cover all critical user paths and functionalities becomes increasingly difficult. Scaling tests across multiple features and environments can put additional load on production systems, which can be resource-intensive. Moreover, as the number of monitored applications and services increases, managing and maintaining the synthetic monitoring infrastructure becomes a daunting task.

Solution: Striking a proper balance between test frequency and resource usage is crucial to mitigate resource overheads. Focus synthetic monitoring on the most business-critical and high-impact user flows to optimize resource usage. Moreover, adopting cloud-based solutions can offer scalability and flexibility, allowing organizations to monitor a large number of applications and services without worrying about infrastructure limitations. They also offer the advantage of pay-as-you-go pricing, making it a cost-effective option for organizations of all sizes.

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