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Cloud drift detection: How to resolve out-of-state changes

Cloud drift detection: How to resolve out-of-state changes

Cloud configurations constantly change due to the adoption of new technologies, release of new features, and support of new business requirements. When real-life configurations differ from predetermined build-time states, drift occurs. Drift can lead to environment instability, deployment issues, unpredictable costs, and security or compliance gaps. To resolve out-of-state changes in cloud drift detection, follow these steps:

  • Understand when drift becomes a risk:Not all drifts pose a real or exploitable risk.
  • Implement drift detection automation relevant to your stack:Continuously compare the configuration within your IaaS (Infrastructure as a Service) with that of your IaC (Infrastructure as Code) plan files.
  • Classify and route their response to the right individual or team:Surface and resolve drifts as close to developers as possible, as they have the most comprehensive history and knowledge of any given configuration.
Implementing a systemic drift detection strategy is crucial for understanding and improving your cloud posture. This involves understanding the risks associated with drift, detecting drift between IaC and the cloud, and responding to drift effectively by routing the response to the appropriate individual or team.


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The FAUN watches over the forest of developers. It roams between Kubernetes clusters, code caves, AI trails, and cloud canopies, gathering the signals that matter and clearing out the noise.
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