I’m looking into ways to validate critical production endpoints safely, especially when we can’t create or modify data due to downstream or financial impact.
Has anyone used synthetic monitoring as a way to run post-deployment smoke tests in production?
I’d love to hear:
What tools you’ve used (e.g., Grafana, Prometheus, Datadog, etc.)
What types of tests or flows you cover
How you manage safe, synthetic data
Any lessons learned or anything to avoid
Any examples or insights would be really helpful! Thanks in advance
Very valid point!
We use DD synthetic monitors (€€€) to check certain endpoints that are particularly important for the company. The goal is to ensure the service status in production. Personally, I am against this approach because we deploy our services on a managed cluster, allowing us to test these “important” endpoints from within the cluster, thereby reducing costs. Ensuring connectivity from outside the cluster should be the responsibility of the cloud provider, as defined by their SLAs. So what is the point of Synthetic monitors in production in a managed environment?
