Red Hat Demonstrates Governed AIOps and GitOps Workflow for Enterprise Network Security

Red Hat detailed a governed AIOps and GitOps workflow for enterprise network infrastructure, demonstrating how organizations can automate firewall policy lifecycle management using Red Hat Ansible Automation Platform, ServiceNow, and GitHub. The architecture uses Event-Driven Ansible to intercept service requests, invoke large language models to analyze network topology and propose firewall rules, and manage the desired network state as Configuration as Code in Git. Modifications are staged as GitHub pull requests and reconciled deterministically only after passing automated live-to-Git drift verification and two distinct human approval gates: peer engineering review and Change Advisory Board authorization. For DevOps, platform engineering, and NetOps practitioners, manual firewall provisioning has long been an operational blind spot that slows down continuous delivery. Traditional ticket handling requires manual multi-system correlation, direct CLI configuration, and fragmented documentation, creating severe risks of misconfiguration, security exposures, and configuration drift. By bringing firewall rules under GitOps control, every intended state modification is versioned, reviewed, and tested against live network state before execution. If live firewall settings drift from the repository baseline, the automation safely halts, preventing untested overwrites and ensuring that production configurations remain fully reproducible and auditable. This architecture exemplifies the maturation of GitOps beyond pure Kubernetes cluster orchestration into heterogeneous enterprise infrastructure. While GitOps established itself through declarative controllers like Argo CD and Flux for cloud-native workloads, network and perimeter security have historically resisted declarative models due to legacy appliance interfaces and strict IT Service Management compliance mandates. Combining event-driven automation with generative AI proposals and Git pull requests highlights the emerging design pattern where AI proposes changes, Git captures and validates state, and automation engines execute. Rather than granting autonomous agents direct write access to critical infrastructure, Git pull requests serve as deterministic control boundaries where AI recommendations are vetted, versioned, and executed through immutable infrastructure pipelines. Platform and network teams should evaluate applying Git-driven reconciliation patterns to their operational workflows. In practice, adopting this model requires defining clear separation of duties: AI models should only produce structured pull requests and risk documentation, never handle credentials or execute direct API calls. Teams should implement rigorous pre-flight drift detection to ensure automated executions do not overwrite emergency out-of-band changes. Furthermore, organizations should align their Git branching strategies—treating the main branch as the verified production state—with bidirectional webhook syncs to satisfy enterprise audit requirements without saddling engineers with manual compliance logging.