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Integrating Agentic AI Into Internal Developer Platforms To Minimize Errors and Downtime - Lin Sun, Solo.io & Sara Qasmi, NTT Data

Ever deployed a config without semantic validation—only to break a critical API or route? Or seen staging pass while production fails due to policy mismatches? Imagine if Agentic AI could proactively validate configs and explain risks in natural language.

In this talk, we share how we enhanced our GitOps-based internal developer platform by integrating AI agents into the deployment workflow. Our platform uses the GitOps model to declaratively manage environments from Git, ensuring consistency and repeatability. However, the absence of semantic validation meant misconfigurations—such as resource requests exceeding quotas or Kyverno policy conflicts—would occasionally slip through. These issues led to failed scheduling, degraded availability, or blocked rollouts. Using kagent, our agents analyze the live cluster, Git state, and runtime config to detect semantic issues—like resource quota violations or Kyverno policy conflicts—and surface them in PRs with human-readable feedback.