Harness Chaos Engineering's GCP Cloud Monitoring probe transforms existing Google Cloud Platform (GCP) metrics into objective, automated pass/fail validations for chaos experiments, eliminating the need for subjective observation. By supporting flexible authentication methods and PromQL queries, it allows users to validate infrastructure performance against predefined thresholds during controlled failure scenarios, thus creating an audit trail for system behavior under stress and enabling automated resilience testing within CI/CD pipelines. The probe integrates with GCP's Cloud Monitoring to leverage existing metrics, such as CPU usage and memory pressure, to provide clear success criteria for chaos experiments. It offers two authentication options: IAM with workload identity for seamless integration within GCP and GCP service account keys for more granular control, particularly useful when chaos infrastructure runs outside GCP. Users can craft PromQL queries to monitor specific metrics and define pass/fail thresholds, while tuning probe behavior through runtime properties to match experiment characteristics. This approach turns passive monitoring into active validation, providing an audit trail that aids in capacity planning, SLO refinement, and infrastructure budgeting, ultimately enhancing the learning process in chaos engineering by providing objective and repeatable measurements of system resilience.