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Agentic Controller

Kubernetes controller for managing AI agent workloads. Defines CRDs under the konveyor.io API group and controllers for composing and executing agent workloads via Agent Sandbox.

Overview

The controller follows the Tekton Task/TaskRun pattern: an Agent declares what is available (skills, LLM providers, container image, prompt, typed parameters) and an AgentRun supplies concrete values (model selections, parameter values, instructions) to trigger execution.

The controller is domain-agnostic. It does not call Hub, Backstage, or any inventory system. Parameter values are opaque — the controller validates and passes them through. The creator of the AgentRun (UI, CLI, CI pipeline) resolves application metadata before creating the CR.

CRDs

CRD Purpose
SkillCard Individual skill or rule. Resolves to an OCI artifact mounted at /opt/skills/{name}/.
SkillCollection Group of skills. References skills by OCI image, git source, or SkillCard CR name.
LLMProvider LLM service endpoint, credentials, and available models.
Agent Template declaring available skills, providers, container image, prompt, and typed parameters.
AgentRun Execute a single Agent with specific values. Creates an Agent Sandbox.
AgentPlaybook Ordered sequence of stages, each referencing an Agent.
AgentPlaybookRun Execute a playbook. Creates AgentRuns sequentially per stage.

Key design decisions

  • Agent Sandbox is a hard dependency for workload execution
  • Git credentials stay in the harness — the agent does not receive push credentials
  • Skills are OCI artifacts mounted via ImageVolumes (K8s 1.33+)
  • Workspaces are ephemeral — git is the persistence layer
  • ACP over HTTP (via goose serve) provides real-time observability and human-in-the-loop interaction
  • Hub provides curated REST endpoints for the UI

See docs/adr/ for the full set of architecture decision records.

Project structure

agentic-controller/
  api/v1alpha1/           CRD type definitions (Go structs)
  internal/controller/    Controller implementations
  internal/registry/      OCI registry client
  docs/adr/               Architecture Decision Records
  skills/                 Agent skills for contributors
  CONTEXT.md              Domain glossary
  AGENTS.md               Agent-facing instructions

Platform requirements

  • Kubernetes 1.33+ (ImageVolume GA)
  • OpenShift 4.20+
  • Agent Sandbox v0.5.x

Related projects

Project Role
konveyor/enhancements Enhancement proposals
konveyor/tackle2-hub Application inventory, curated REST API for agent resources
konveyor/tackle2-ui Web UI
kubernetes-sigs/agent-sandbox Sandbox CRDs for agent workloads
redhat-et/skillimage OCI skill packaging and distribution
NVIDIA/OpenShell Secure runtime for autonomous agents

Contributing

Read AGENTS.md for project conventions. Use the skills in skills/ for design workflows — grill-with-docs for stress-testing designs against the domain model.

Code of Conduct

Refer to Konveyor's Code of Conduct here.

About

Kubernetes controller for managing AI agent workloads. Defines CRDs (Agent, AgentRun, AgentPlaybook, SkillCard, SkillCollection, LLMProvider) and controllers for composing and executing agent workloads via Agent Sandbox.

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