Hey r/googlecloud ,

I’m looking for real-world feedback on using Google Cloud built-in metrics (Compute Engine, Cloud Run, GKE, Cloud Load Balancing) to drive automated systems.

Built-in metrics are great for dashboards and retrospectives. However, when you try to build tight automated loops—such as: * Automated rollbacks during faulty deployments (e.g., memory/CPU spikes), * Fast cluster autoscaling or traffic shifting, * Self-healing / automated remediation scripts,

the delay between an event happening and the metric being queryable (sampling window + aggregation overhead) can stretch to several minutes, making it difficult to protect tight SLOs.

I’m collecting feedback to share directly with the GCP observability and telemetry teams, and would love your input:

What automated workflows are you driving (or trying to drive) using built-in GCP metrics?

Which specific metrics are the most useful to you for automation?

What is your workaround when built-in metrics are too slow?…