Skip to content

Use Cases

This page describes who Kube Agentic Networking is for and the user journeys that drive the project's API design. If one of these journeys matches a problem you have, the Quickstart is a good place to see the current APIs in action.

Personas

AI Engineer: A hands-on builder focused on the end-to-end development, deployment, and optimization of AI agents. They are distinct from ML Researchers and ML Engineers; AI Engineers are product-first, operating on the other side of the LLM Inference Serving API, and are not responsible for training, tuning, or deploying the models themselves.

Platform Engineer: A builder and operator of the foundational platform (e.g. the provider of ingress/egress Gateways for the cluster).

AI Platform Engineer: A builder and operator that leverages the foundational platform and builds layers on top that enable AI engineers to develop and deploy agents at scale.

AI Security Engineer: A specialist focused on designing safeguards to ensure AI agents operate safely and securely.

Application Developer: A builder that is primarily focused on traditional APIs / applications but also surfaces functionality to agents using MCP.

Tool Developer: A builder focused on developing MCP tools that can be leveraged by agents.

Critical User Journeys

Agent Identity

As an AI Engineer, I want to assign a unique, verifiable identity to my agent running in Kubernetes, so that gateways or external systems can securely authenticate it and make authorization decisions.

Protocol-Aware Authorization

As an AI Platform Engineer, I want to:

  • Deny any traffic coming from Agents to MCP servers & other Agents by default

  • Allow agents to connect to specific, defined sets of MCP servers (e.g. "toolsets", "virtual service")

  • Allow agents to use specific tools

  • Allow agents to use specific tools from specific MCP servers

  • Control whether access to tools is read, write or both

Observability

As an AI Engineer I want to:

  • Understand why my agent is getting denied when calling a certain tool

  • Audit agent actions in the context of the user who delegated authority, so that I can attribute outcomes to both human intent and agent behaviour.

As an AI Platform Engineer I want to:

  • Have an aggregated way of seeing failures/denials across the platform

Security

As an AI Security Engineer I want to:

  • Develop MCP guardrails for pre-request filtering to prevent attacks such as prompt injection.

  • Develop MCP guardrails for post-response filtering to prevent data breaches.