IaC Drift Detection and AI-Driven Remediation Pipelines

AI generates your Terraform now. LLM writes the module, Checkov scans it, PR gets merged, infrastructure deploys. Beautiful workflow. Then drift happens. Someone clicks in the console. A security group gets modified. A network ACL changes outside version control. Your AI-generated infrastructure, your security policies, and your network configurations diverge from declared state. Now what? Drift is not just an infrastructure problem - it's a security incident waiting to happen and a network outage in progress. The generation problem is solved. The operations problem crosses team boundaries. Modern observability stacks, policy engines, and agent frameworks have matured. OPA can enforce policy continuously. State comparison can be automated. LLMs can analyze drift and generate remediation. The engineering challenge is building systems that work across DevOps, SecOps, and NetOps while keeping humans in control.

This session covers the building of unified drift detection pipelines, spanning infrastructure, security policies, and network configurations. We'll explore AI agents that analyze root cause and generate domain-specific remediation PRs, governance guardrails for AI agent behavior using policy-as-code, and GitOps integration with cross-team approval workflows. We'll also cover failure modes: remediation loops, alert fatigue from noisy detection, and compliance risks of over-automation.