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Synthetic performance monitoring uses scheduled, automated requests or user-like scripts to check how a website, application, service, or API performs under defined conditions. It measures the test you set up—not actual users—so it can catch failures proactively, while real user monitoring (RUM) shows how real visitors experience the service.
What synthetic performance monitoring means
A synthetic monitor repeatedly runs a predefined check against a target and records whether it met its expected conditions. Depending on the check, it may request an endpoint, inspect response data, call an API, or run a scripted browser journey. Results commonly include success or failure and latency; monitoring systems can also alert a team when a run fails. MDN Web Docs describes the method as simulated monitoring, while Google Cloud Monitoring documents periodic requests and scripted tests that record execution outcomes and latency.
Because the checks run on a schedule and use selected conditions, teams can repeat them over time and compare results. They can run before real traffic arrives or in places where little real traffic is available. Their findings apply to the designed test and its conditions, not every possible device, network, location, or user behavior.
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What a synthetic monitor can test
A monitor is defined by its target, request or scripted steps, success conditions, and schedule. Depending on the service, configuration may also specify a test location or browser. The check’s scope determines what a pass or failure actually establishes.
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Endpoint availability
A lightweight check can test whether an endpoint responds and whether its response meets basic expectations. Google Cloud documents HTTP/S, TCP, and ICMP uptime checks. Such a result is useful for reachability, but it does not by itself show that a user can complete a task in the application.
API behavior
An API check can send a request and evaluate a response against defined assertions. This tests the particular API operation and conditions configured; it is more specific than checking whether a service endpoint is reachable.
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Browser journeys
A browser-based synthetic test can execute a sequence of user-like actions, such as logging in, adding an item to a cart, or proceeding through checkout. Elastic’s synthetic monitoring documentation describes browser monitors and other synthetic checks. A scripted journey covers more of an intended path than a simple availability check, but still only represents the steps and conditions encoded in that script.
Synthetic monitoring versus RUM
Real user monitoring observes performance from actual users’ devices and interactions. Synthetic monitoring runs predefined checks in controlled conditions. As MDN’s comparison of RUM and synthetic monitoring explains, these methods answer different questions: RUM reports what happened across real traffic and its variability, while synthetics provide repeatable proactive tests that can run when traffic is sparse or absent.
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| Aspect | Synthetic monitoring | Real user monitoring (RUM) |
|---|---|---|
| What it observes | Scheduled requests or scripted journeys designed by the team | Performance from actual users’ devices and interactions |
| Conditions | Selected and controlled for the test | Varies with real users, devices, networks, locations, and behavior |
| Useful for | Repeatable proactive checks, including when real traffic is limited | Understanding performance across actual traffic |
| What a result represents | The configured test and its conditions | The users and interactions captured by the monitoring |
Using both gives a broader view: synthetic checks can flag a known path failing under chosen conditions, while RUM can reveal variation among real experiences. A passing synthetic test does not establish that every user has a good experience.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to choose the right scope
Match the check to the question you need answered. If you only need to know whether a service endpoint responds, an uptime check may be sufficient. If you need confidence in a particular API operation or user-visible workflow, use a check that exercises and validates that behavior. New Relic documents synthetic monitoring use cases at its synthetic monitoring use-cases guide; Amazon Web Services describes its canary approach in CloudWatch Synthetics documentation.
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When comparing tools, assess the dimensions that affect your intended coverage and operations:
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- Which test locations, browsers, and private-location options are available.
- How tests are authored and maintained, especially as application flows change.
- What metrics, logs, and failure details the service records.
- Which alerting options and integrations it supports.
- Current operating constraints and pricing, checked directly with the provider.
Documentation from Google Cloud, Elastic, New Relic, and AWS illustrates different service approaches; it does not establish an independent ranking of those products.
What synthetic monitoring can and cannot tell you
A synthetic check is evidence about a specific request or scripted path under selected conditions. Repeated runs help teams spot regressions and failures in that scope. The check cannot stand in for every real-user combination of device, network, location, or behavior; that broader variation is why synthetic results are best interpreted alongside RUM where available.
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