Agentic Workflow for Automated Network Device Configuration Compliance

Manual, periodic configuration audits are slow, error-prone, and leave security gaps open for weeks. This workflow deploys persistent agents that continuously pull running configs from routers, switches, and firewalls, compare them against CIS/NIST baselines and internal golden configs, and flag drift in real time. This transforms a quarterly compliance scramble into a continuous state of assurance, closing vulnerability windows from months to minutes.

The real operational burden isn't finding drift—it's fixing it safely. This architecture includes remediation agents that generate Ansible playbooks or Salt states for corrective changes. Low-risk changes (like NTP server updates) are applied autonomously. High-risk changes (ACL modifications, routing protocol tweaks) are routed to a human-in-the-loop approval queue in ServiceNow or Jira, complete with a pre-built rollback plan. This balances speed with operational safety.

To be operationally viable, automation cannot live in a silo. This workflow is built to integrate bi-directionally with your Network CMDB (like NetBox) for device context and with ITSM tools (ServiceNow) for change management. Every audit finding and remediation action is logged as a CI-linked activity, creating a complete, auditable trail from non-compliant device to corrected state, which is critical for internal audits and regulatory compliance (SOX, PCI-DSS).

Unpatched configuration vulnerabilities are low-hanging fruit for attackers and a constant source of costly audit findings. By autonomously enforcing configurations—like disabling unused services, enforcing password policies, and ensuring logging is enabled—this workflow systematically hardens your network. The ROI comes from avoided breach-related costs, reduced manual labor for audit prep and remediation, and lower cyber insurance premiums due to improved security posture.

As networks grow (5G, IoT, edge), manual configuration management becomes impossible. This agentic workflow scales horizontally, allowing a single network engineer to govern the compliance state of thousands of devices. Specialized agents handle different device families (Cisco IOS, NX-OS, Juniper Junos, Palo Alto PAN-OS), normalizing the complexity. The result is operational leverage: you can manage more devices, more securely, without proportionally increasing team size.

Continuous configuration compliance is the foundational data layer for Intent-Based Networking. This workflow creates a closed loop: it interprets high-level intent (e.g., 'all branch firewalls must have these five security policies'), measures current state via continuous audit, and autonomously corrects drift. Implementing this workflow is a practical first step toward a full IBN architecture, moving from reactive CLI management to proactive, policy-driven network assurance.

This agent continuously pulls live configurations from routers, switches, and firewalls via APIs (NETCONF, RESTCONF) and compares them against a golden-source repository of CIS, NIST, or custom business rules. It identifies deviations, tags them by severity (critical security gap vs. informational), and generates a prioritized diff report. The agent integrates with the network CMDB to understand device roles and enforce role-based compliance templates.

Upon receiving a drift report, this agent analyzes the proposed corrective changes. It simulates the impact using a network digital twin or pre-checks to avoid service disruption. For high-risk changes (e.g., core router ACLs, BGP policies), it automatically drafts a change request with a rollback plan and routes it to a human approval queue in ServiceNow or Jira. For low-risk, repetitive fixes (e.g., standardizing SNMP community strings), it proceeds to the execution phase.

The core orchestration layer, built with frameworks like LangGraph or custom Python, sequences the approved remediation actions. It interfaces with automation platforms like Ansible, SaltStack, or vendor-specific APIs (Cisco IOS-XE, Juniper Junos) to push configuration snippets. Execution occurs within defined maintenance windows, with pre- and post-change validation checks to confirm device reachability and basic functionality. All actions are logged with full context for audit trails.

This agent monitors the network post-change for a stabilization period. It checks for new alarms, performance degradation, or compliance regression. If a failure condition is triggered, it automatically executes the pre-defined rollback plan to revert to the last known good configuration. Successful changes are logged, and the CMDB is updated. This closed-loop control is critical for maintaining availability while automating at scale.

The workflow directly targets costly operational burdens: Eliminating manual audit cycles that consume network engineer hours. Reducing mean time to remediate (MTTR) for critical vulnerabilities from weeks to hours, shrinking the attack surface. Preventing configuration drift-induced outages that cause unplanned downtime. The ROI comes from reduced compliance audit preparation effort, lower risk of breach or outage fines, and freeing engineering staff for strategic work.

A production build requires integrating several systems: a source of truth (CMDB like ServiceNow), network inventory and APIs, a compliance rule engine, and the orchestration platform. The workflow is deployed as a containerized microservice with idempotent agents. Key constraints include managing credentials securely via a vault, handling heterogeneous device OS types, and designing exception routing for complex, non-standard configurations that always require human review.