Managing AI Agents on Servers with JetPatch

This whitepaper explains how to manage AI software agents that run on servers, virtual machines and containers in private and hybrid infrastructure. It is written for enterprise IT and infrastructure teams who need visibility and control over these workloads.

The paper opens with trends driving on-premises AI, including storage growth and cloud cost pressure, each cited to an outside source. It then outlines the main risks: limited visibility, heavy resource use, and compliance gaps from outdated or unapproved agents. The second half describes how JetPatch extends its server agent management to AI agents, using a lightweight .vai package instead of heavy containers.

What you’ll learn

• How policies define which AI agents run on which servers, and how deployment and updates follow from them
• How a watchdog restarts or reinstalls AI agents that crash or fail health checks
• How CPU and memory throttling keeps AI agents from overwhelming shared servers
• How to fit .vai packaging into CI/CD and MLOps pipelines
• Use cases in cybersecurity agents, AIOps and AI model rollouts

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