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Deploy AI Agents on Kubernetes
The simplest way to deploy, manage, and scale AI agents in your Kubernetes cluster with declarative YAML configurations
β¨ Why Choose KubeAgentic?
Multi-Provider Support
OpenAI, Anthropic (Claude), Google (Gemini), and self-hosted vLLM models - all in one platform
Declarative Configuration
Standard Kubernetes Custom Resources (CRDs) for easy management and GitOps workflows
Auto-Scaling
Automatic scaling based on demand and resource usage with Kubernetes HPA integration
Secure by Default
API keys managed with Kubernetes Secrets and RBAC for enterprise-grade security
Built-in Monitoring
Real-time health checks, metrics, and status reporting with Prometheus integration
Tool Integration
Extend agents with custom tools, APIs, and services for complex workflows
π Quick Start
π³ Optimized Docker Images
Operator
sudeshmu/kubeagentic:operator-latest
108MB - Highly Optimized
Red Hat UBI Micro base image
Agent Runtime
sudeshmu/kubeagentic:agent-latest
625MB - 66% Smaller!
Red Hat UBI Minimal + Python optimizations
β¨ Multi-stage builds β’ Red Hat UBI security β’ Non-root execution β’ Multi-architecture
π³ View on Docker HubποΈ How It Works
Kubernetes Cluster
Your existing K8s infrastructure
KubeAgentic Operator
Deploy & manage AI agents
AI Models
OpenAI, Claude, Gemini, vLLM
Auto-Scaling
Monitor & scale automatically
π Documentation
π― Use Cases
Customer Support
Deploy scalable support bots that can handle multiple conversations simultaneously with context awareness
Code Review
Automated code analysis and feedback for improved code quality, security, and best practices
Knowledge Management
Internal Q&A assistants for company documentation, procedures, and knowledge base queries
Content Generation
AI-powered content creation for marketing, documentation, and automated report generation
π€ Community & Support
Licensed under the Apache License 2.0. See LICENSE for details.
Β© 2025 KubeAgentic. Built with β€οΈ for the Kubernetes community.