## [Drift Prevention vs Detection: Does a Polling Approach make sense At Scale?](https://docs.rafay.co/blog/2025/08/05/drift-prevention-vs-detection-does-a-polling-approach-make-sense-at-scale/)

Many organizations typically rely on pull-based GitOps tools (e.g. Argo CD) to detect and remediate drift on their Kubernetes clusters. This approach allows clusters to diverge before reconciling them on the next polling interval. For the last 4 years, Rafay customers have benefited from an architecturally different approach that focuses on true drift prevention, backed by robust detection capabilities across both [**cluster blueprints**](https://docs.rafay.co/blueprints/overview/) and [**application workloads**](https://docs.rafay.co/workloads/workload_types/).

In a previous [**blog**](https://docs.rafay.co/blog/2025/08/04/understanding-argocd-reconciliation-how-it-works-why-it-matters-and-best-practices/), we discussed how ArgoCD's reconciliation works and its best practices.