What is synthetic monitoring?

Synthetic monitoring typically relies on a robot client that executes automated scripts simulating the end user’s clickstream through the application. Broadly speaking, the scripts, or synthetic tests, are created by QA (quality assurance) engineers to test a website, application, or system. Depending on the adopted framework and synthetic monitoring tool, these scripts take many forms and syntaxes. Synthetic monitoring solutions execute the tests and report on their results to the monitoring tool. The data is analyzed to assess the system’s behavior. If a need is identified, the system is improved or modified accordingly. New synthetic tests are written to further verify the changes and possibly continue improving the quality of the system.

Often synthetic testing comes in the form of an automated task that would typically be performed by engineers. It is normally also possible to run synthetic tests manually, even if it is rarer. Most occurrences of manual intervention happen when tests are updated to reflect changes in the monitored systems’ behavior and UI.

Synthetic monitoring has synthetic testing at its core, as it all revolves around correctly writing and executing the tests for your own use cases. In most synthetic monitoring solutions, there are synthetic tests possible for a myriad of scenarios, with a wide coverage of any company’s needs, within the limits of what the vendor has built into the software. Whether you need to test an end-user clickstream through your e-commerce platform, or monitor shopping transactions or even online gaming, synthetic tests are possible.

Synthetic monitoring can take different forms depending on what needs to be tested — from simple uptime checks to advanced transaction validation and web performance monitoring. Each type serves a specific purpose, whether it’s ensuring basic availability, verifying website performance, or monitoring business-critical workflows. Below are the main types of synthetic monitoring along with their typical use cases.

Also known as availability monitoring, it helps to track the availability and responsiveness of a web application. Synthetic tests may involve simply using a ping or a GET request to specific resources to test their accessibility, or creating multiple concurrent requests to monitor the responsiveness and performance of your web application.

As part of availability monitoring, synthetic tests can also be written for non-HTTP services (such as mail or database servers) by establishing a TCP connection to a specified host and port, measuring latency, and verifying the expected response.

Uptime monitoring also extends to API monitoring, where synthetic API tests verify that endpoints respond correctly, measure response times, ensuring backend services and integrations remain reliable.

As the name suggests, synthetic website monitoring tests the availability and navigability of a website. It can include not only simple uptime checks but also more complex scenarios that simulate a user navigating through the site. With this type of monitoring, response times, page load times, and other performance metrics can be measured and analyzed.

Synthetic transaction monitoring goes beyond synthetic website monitoring and is broader. It is used to test both websites and web applications to ensure bug-free functionality and smooth, error-free workflows. Typical use cases include validating form submissions, verifying login processes, and checking that business-critical operations — such as shopping cart checkouts — are working as expected.

These tests are often run at regular intervals from servers around the world to guarantee the continuous availability of critical functions. In addition, monitoring third-party services is essential to ensure that external integrations do not negatively affect overall performance.

Creating a solid synthetic monitoring system starts with pinpointing the most crucial user interactions and processes within your application. Pay special attention to high-impact user journeys, like login flows, payment gateways, and other key transactions that directly influence customer satisfaction and business success. Once you’ve identified these vital areas, choose a synthetic monitoring tool that aligns with your organization’s needs and budget, making sure it can handle the types of synthetic tests you require.

Next, configure your synthetic monitoring system to mimic user interactions from various geographical locations and across different devices. Establish clear performance thresholds and set up alert criteria so your IT team can be quickly informed of any anomalies or performance hiccups. It’s also essential to regularly review and update your synthetic monitoring scripts to keep up with changes in your application and shifts in typical user behavior.

Bringing synthetic monitoring into your CI/CD pipelines is a smart move that helps catch performance issues before they affect real users. By incorporating synthetic tests into your continuous integration and delivery workflows, you can automatically check your application's performance with every code change or deployment. This allows you to spot regressions, broken user flows, or slow response times early in the development process.

Most modern CI/CD tools, like Jenkins or GitLab CI/CD, support the automation of synthetic tests as part of your build and deployment routine. You can also use APIs to connect synthetic monitoring tools directly with your pipeline, enabling smooth execution and real-time feedback.

Solutions like Robotmk take this idea a step further by integrating synthetic tests into both your monitoring environment and your delivery pipeline. By embedding synthetic monitoring directly into your CI/CD process, you create a continuous feedback loop that not only protects application performance but also speeds up development cycles while promoting a culture of quality and reliability.

There are clear benefits to implementing synthetic monitoring. It not only helps validate performance and stability before systems go live, but also ensures reliability and user satisfaction throughout the application’s lifecycle.

One of the biggest perks of synthetic performance monitoring is that it allows us to validate how well a system performs. These tests are specifically crafted to see how a system holds up under pressure and to figure out if any tweaks are needed before it goes live.

Even after launch, these tests remain crucial, keeping an eye on overall performance and making sure that any changes don’t negatively affect users or internal processes. By gathering in-depth insights into how the system behaves, synthetic monitoring helps catch potential problems early on and makes it easier to pinpoint the root causes of errors or performance dips.

Synthetic transaction monitoring also helps in setting a performance benchmark. By watching how an application reacts during a series of controlled synthetic tests, teams can establish a baseline for what normal looks like. Once the application is up and running, its performance can be measured against this benchmark, giving immediate insight into any drops in responsiveness or reliability.

Another key advantage is in accessibility monitoring. By mimicking the actions of users who depend on specific accessibility features, synthetic tests can uncover how inclusive and user-friendly a system or interface really is. This approach often brings to light issues that might go unnoticed during regular testing or when looking at real user data.

Synthetic monitoring also allows teams to replicate the experiences of users who are far away from the data center. Developers and QA engineers can simulate typical request patterns or set up tests to reflect the routing conditions that users in a specific region would encounter. This helps identify latency, connectivity, or performance issues that might differ significantly across various locations around the globe.

Finally, synthetic monitoring contributes to compliance with service level agreements by providing objective performance measurements. These metrics help organizations verify that they are meeting their reliability and performance commitments, while also offering concrete evidence to stakeholders and customers that agreed standards are consistently maintained.

Synthetic monitoring is not without its challenges. For instance, many of the difficulties in setting up a synthetic monitoring system lie in preparing the right synthetic tests. This becomes even more complex when trying to achieve true end-to-end monitoring across a mix of cloud and on-premises assets. For instance, in many infrastructures nowadays, a mix of cloud and on-premises assets are used. The larger the distributed environment is, the more challenging it is for DevOps or engineering teams to simulate every possible scenario.

Errors can slip through the cracks if we don’t anticipate and test for specific locations or situations. Take web apps, for instance—if we don’t have a clear understanding of the paths users take, synthetic testing can feel more like a game of chance. It’s crucial to lay some groundwork before diving into synthetic monitoring software.

Setting up synthetic monitoring isn’t a walk in the park; it demands a particular skill set from engineers, and not everyone is well-versed in it. Different testing languages and frameworks have their own quirks when it comes to writing tests and building a functional synthetic monitoring system. If your team lacks this specialized knowledge, getting synthetic monitoring up and running can be a real challenge and quite time-consuming.

Even small changes to the user interface in client-facing applications can lead to testing scripts failing, which sets off alerts and notifications, causing unnecessary stress for system administrators. That’s why it’s vital to have a solid alerting and notification system in place to prevent unnecessary triggers that lead to "alert fatigue." While fixing most failures is usually straightforward, synthetic monitoring still has a long way to go before it can truly be considered a "set it and forget it" solution.