Synthetic Monitoring
Synthetic monitoring is the practice of proactively testing a system's availability and performance by running scripted, simulated user interactions — such as loading a webpage or completing a checkout flow — from external locations on a…
Definition
Synthetic monitoring is the practice of proactively testing a system's availability and performance by running scripted, simulated user interactions — such as loading a webpage or completing a checkout flow — from external locations on a regular schedule, rather than waiting for real users to encounter a problem.
Overview
Synthetic monitoring flips the usual detection model: instead of waiting for real user monitoring (RUM) or customer complaints to reveal that something is broken, scripted checks run continuously — often every few minutes, from multiple geographic locations — simulating exactly what a real user would do, such as loading a homepage, logging in, or completing a checkout flow. If a check fails or exceeds a latency threshold, it can trigger an alert to the on-call rotation before a single real customer is affected. Because synthetic checks run at predictable, controlled intervals regardless of actual traffic, they're especially valuable for low-traffic services or times of day when real user data is sparse, and for catching regressions immediately after a deployment rather than waiting for enough real traffic to surface a problem statistically. They're also commonly used to validate third-party integrations and critical multi-step user journeys end-to-end, not just whether individual endpoints respond. Synthetic monitoring complements, rather than replaces, RUM and broader observability tooling: synthetic checks tell you a known journey is broken from a controlled vantage point, while RUM and distributed tracing reveal how real, diverse users are actually experiencing the system in the wild. Tools like Datadog, New Relic, and Dynatrace commonly offer synthetic monitoring alongside their broader observability platforms.
Key Concepts
- Scripted checks that simulate real user actions on a fixed, regular schedule
- Runs proactively, independent of actual live traffic volume
- Executed from multiple geographic locations to catch region-specific issues
- Catches deployment regressions immediately, before real users encounter them
- Validates complete multi-step journeys, not just individual endpoint health
- Commonly paired with alerting that pages on-call when a check fails