Features
Concrete capabilities shipped in recent releases.
Live Agents
Agents run as persistent Deployments with zero cold start. Shared context across tasks, session history survives restarts.
Web Terminal
Access any Agent directly from the browser via the built-in web terminal. Real-time interactive sessions without SSH or port-forwarding.
Standby (Auto Suspend/Resume)
Agents auto-suspend after idle timeout, auto-resume when new Tasks arrive. Connection-aware — active sessions prevent suspension.
CronTask
Scheduled and recurring task execution. Concurrency policies (Allow/Forbid/Replace), manual trigger support, and retention control.
Git Auto-Sync
HotReload syncs Git contexts in-place without restart. Rollout policy triggers rolling updates with active Task protection.
Concurrency & Quota
Limit concurrent tasks per Agent and rate-limit task starts with sliding time windows. Tasks queue automatically when limits are reached.
Skills
Reusable AI agent capabilities from Git repos. Share skills across Agents and templates, auto-injected as slash commands.
Declarative CRDs
Fully Kubernetes-native. GitOps-friendly, works with Helm, Kustomize, and ArgoCD. Just kubectl apply.
How It Works
Two simple resources. One powerful workflow.
Define an Agent
Deploy persistent AI agents your team can interact with in real time — through the web terminal, CLI, or by submitting Tasks.
- Zero cold start — agent is always running
- Interactive terminal access via CLI or web
- Auto-suspend when idle, resume on demand
- Session history persists across restarts
apiVersion: kubeopencode.io/v1alpha1
kind: Agent
metadata:
name: dev-agent
spec:
profile: "Interactive development agent"
workspaceDir: /workspace
port: 4096
persistence:
sessions:
size: "2Gi"
standby:
idleTimeout: "30m"
Submit a Task
Run stable, repeatable AI tasks in ephemeral Pods. Perfect for CI/CD pipelines, batch operations, and automated workflows.
- No new tools to learn — just
kubectl apply - Works with any CI/CD pipeline
- Scale with Helm templates for batch operations
- Rate limiting and quota controls
apiVersion: kubeopencode.io/v1alpha1
kind: Task
metadata:
name: update-dependencies
spec:
templateRef:
name: ci-runner
description: |
Update all dependencies to latest versions.
Run tests and create a pull request.
Architecture
A simple, Kubernetes-native design with no external dependencies.
Task
WHAT to do
Agent
HOW to execute
Pod (OpenCode)
WHERE it runs
Frequently Asked Questions
KubeOpenCode is an open-source platform that brings AI coding agents into the Kubernetes ecosystem. It lets you deploy, manage, and scale AI agents as Kubernetes-native services with declarative CRDs, RBAC, and enterprise-grade governance.
OpenCode is a terminal-based AI coding tool for individual developers. KubeOpenCode builds on top of OpenCode to provide a Kubernetes-native platform for teams and enterprise — adding multi-tenancy, persistent agents, task orchestration, and infrastructure-level controls.
Yes, KubeOpenCode runs on any standard Kubernetes cluster (v1.26+). You can use managed services like EKS, GKE, AKS, or a local cluster with Kind or minikube for development.
KubeOpenCode supports any model that OpenCode supports, including Claude, GPT-4, Gemini, and local models via Ollama. You configure model access through Agent credentials and the OpenCode configuration.
Yes, KubeOpenCode is free and open-source under the Apache License 2.0. You only pay for your own infrastructure (Kubernetes cluster) and AI model API usage.
KubeOpenCode is currently in early alpha (v0.0.x). The API may change without backward compatibility. We recommend using it for development, testing, and evaluation while we stabilize the API toward a v1.0 release.
Contributions are welcome! Check out our GitHub repository for open issues, join the Slack community for discussions, or submit a pull request. See the CONTRIBUTING guide in the repository for details.
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