Agentic Workflow for Automated API Governance for Open RAN Interfaces

Multi-vendor Open RAN introduces an interoperability bottleneck where non-standard API implementations between RICs, O-RAN interfaces, and vendor-specific elements degrade performance and stall deployment. This workflow automates continuous API governance, eliminating manual conformance testing and reactive troubleshooting. The business value is direct: accelerated integration cycles, reduced vendor-lock risk, and lower operational cost from preventing service-impacting API drift in production networks.

Implementation integrates with the Service Management and Orchestration (SMO) framework, using a dedicated governance agent to orchestrate test harnesses like O-RAN SC's Non-RT RIC. The agent schedules scans, deploys containerized tests against live vendor elements, and analyzes latency, payload correctness, and schema adherence. Exceptions trigger Jira/Servicenow tickets and can request policy enforcement via the RIC. This creates a closed-loop system for maintaining API integrity, essential for scalable, zero-touch Open RAN operations.

This workflow automates the critical bottleneck of ensuring API compliance and performance across the disaggregated Open RAN stack—spanning RIC, O-RAN, and vendor-specific interfaces. By deploying specialized validation agents, operators eliminate manual, periodic conformance testing, which is too slow for dynamic networks. The architecture directly reduces integration risk, prevents costly interoperability failures post-deployment, and cuts the labor required for vendor onboarding and change management by over 70%, protecting both capital investment and service quality.

Implementation integrates the orchestrator (e.g., LangGraph) with the Service Management and Orchestration (SMO) framework and CI/CD pipelines. Validation agents, built as containerized services, pull current API specifications and test policies from a central repository. They execute synthetic transactions and monitor live traffic, comparing responses against contractual schemas and performance SLAs. Exceptions are scored for severity and routed to a human-in-the-loop dashboard in ServiceNow or Jira. The system requires robust observability for agent performance and immutable audit trails to support vendor disputes and regulatory evidence.

This workflow automates the critical bottleneck of manually testing and validating hundreds of API endpoints across RIC (RAN Intelligent Controller), O-RAN, and vendor-specific interfaces. The operational upside comes from preventing costly interoperability failures, reducing mean-time-to-resolution for integration issues, and enabling faster, safer onboarding of new network functions. Savings are realized through avoided service degradation, reduced vendor dispute resolution cycles, and lower testing labor. The architecture is built on specialized agents for conformance testing, anomaly detection, and policy enforcement, integrated with the Service Management and Orchestration (SMO) framework.

Implementation follows a phased delivery: Phase 1 deploys foundational conformance agents with synthetic test traffic against staging environments, integrated into CI/CD pipelines. Phase 2 adds real-time drift detection and anomaly correlation, requiring integration with live RIC and Element Management Systems (EMS). Phase 3 introduces autonomous remediation actions, such as rolling back non-compliant configurations, governed by approval gates. Controls include immutable audit logs of all agent actions, severity-based escalation to network engineering teams, and a mandatory human review loop for any proposed configuration changes affecting live traffic. Observability is built into the orchestrator, providing a single pane for API health, test coverage, and exception trends.

This workflow automates the continuous validation of O-RAN, RIC, and vendor-specific interfaces, a critical bottleneck in multi-vendor Open RAN operations. It eliminates manual API conformance testing and post-upgrade regression checks, directly reducing integration delays and preventing costly service degradation from undetected specification drift. Savings come from accelerated deployment cycles, lower testing labor, and avoided interoperability incidents that impact network KPIs and customer SLAs.

Implementation integrates with the Service Management and Orchestration (SMO) framework, deploying lightweight test agents that execute against the RIC (Near-Real-Time and Non-Real-Time) and network elements. The architecture requires a centralized policy engine defining API schemas, performance thresholds, and automated remediation playbooks. Controls include anomaly scoring logic, gated human review for non-standard deviations, and immutable audit trails for compliance reporting. Phased rollout starts with a single vendor domain, expanding to cross-vendor interface validation and finally predictive drift detection.