Agentic AI Transforms Network Operations, Shifting Focus to Proactive Management

SolarWinds has unveiled Avior, an agentic AI system designed to revolutionize network operations. This new platform integrates goal-oriented agents that can execute tasks autonomously, building upon SolarWinds' existing AI framework. Avior aims to automate operational tasks, significantly reduce alert noise, and enhance overall infrastructure management across both on-premises and SaaS products. The significance of this release lies in its practical implications for IT and DevOps professionals. As Shannon Kalvar, Senior Research Director for AIOps at IDC, notes, "Agentic operations is the engineering response to the growing complexity inherent in networked digital estates." Avior directly addresses this by allowing network teams to offload repetitive and time-consuming tasks, such as correlating alerts, identifying configuration drift, auditing devices against compliance policies, and managing configuration backups. This shift from merely providing recommendations to actively executing solutions means engineers can redirect their expertise to more strategic initiatives, fostering innovation rather than being bogged down by manual incident response. The system's ability to track capacity and monitor infrastructure utilization also aids in proactive resource management, preventing bottlenecks before they impact services. This development fits squarely within the broader trend of AIOps evolving towards autonomous and predictive capabilities. The AIOps market has been rapidly expanding, driven by increasing enterprise reliance on cloud computing, digital transformation, and the need for real-time IT infrastructure monitoring. The industry is moving beyond basic alert aggregation and correlation, with a strong emphasis on self-healing systems and proactive problem-solving. Platforms are increasingly integrating generative AI to provide natural language incident summaries and runbook recommendations, further streamlining operations. The introduction of agentic AI like Avior is a natural progression, enabling a more sophisticated level of automation where systems not only detect issues but also take bounded decisions and execute remediation workflows. In practice, this means practitioners should focus on understanding how to effectively implement and govern such agentic systems. The configurable autonomy offered by Avior, allowing administrators to define the level of independent action agents can take, is a critical feature. Organizations must establish clear risk-based guardrails and leverage audit trails to maintain human oversight and ensure compliance. The goal is to move towards a state where AI systems handle execution and routine operational decisions, while humans define desired future states and ensure proper governance. This necessitates a re-evaluation of existing operational workflows and a commitment to training teams on how to collaborate effectively with AI agents, ultimately leading to more resilient and efficient IT operations.