Sympozium¶
Kubernetes-native AI Agent Management Platform
Every agent is an ephemeral Pod. Every policy is a CRD. Every execution is a Job. Orchestrate multi-agent workflows and let agents diagnose, scale, and remediate your infrastructure. Multi-tenant. Horizontally scalable. Safe by design.
Quick Install¶
Then deploy to your cluster and activate your first agents:
sympozium install # deploys CRDs, controllers, and built-in PersonaPacks
sympozium # launch the TUI — go to Personas tab, press Enter to onboard
sympozium serve # open the web dashboard (port-forwards to the in-cluster UI)
New here?
See the Getting Started guide — install, deploy, onboard your first agent, and learn the TUI, web UI, and CLI commands.
Why Sympozium?¶
Sympozium serves two powerful use cases on one Kubernetes-native platform:
- Orchestrate fleets of AI agents — customer support, code review, data pipelines, or any domain-specific workflow. Each agent gets its own pod, RBAC, and network policy with proper tenant isolation.
- Administer the cluster itself agentically — point agents inward to diagnose failures, scale deployments, triage alerts, and remediate issues, all with Kubernetes-native isolation, RBAC, and audit trails.
Sympozium takes the agentic control model and rebuilds it on Kubernetes primitives. Every concept that traditional agent frameworks manage in application code, Sympozium expresses as a Kubernetes resource — declarative, reconcilable, observable, and scalable.
Key Features¶
- Ephemeral agent pods — each agent run is an isolated Kubernetes Job with its own security context
- Skill sidecars — every skill runs in its own container with auto-provisioned, least-privilege RBAC
- PersonaPacks — pre-configured bundles of agents that activate with a few keypresses
- Multiple interfaces — k9s-style TUI, full web dashboard, or CLI
- Channel integrations — Telegram, Slack, Discord, WhatsApp
- Persistent memory — agents retain context across runs via ConfigMap-backed memory
- Policy-as-CRD — feature and tool gating enforced at admission time
- OpenTelemetry — built-in observability with traces and metrics
- Web endpoints — expose agents as OpenAI-compatible APIs and MCP servers
- Scheduled tasks — cron-based recurring agent runs
- Local inference discovery — node-probe DaemonSet discovers Ollama/vLLM/llama-cpp on host nodes with automatic model listing and node pinning
Learn More¶
| Topic | Description |
|---|---|
| Getting Started | Install, deploy, and onboard your first agent |
| Architecture | System design and how it all fits together |
| Custom Resources | The six CRDs that model every agentic concept |
| PersonaPacks | Pre-configured agent bundles |
| Skills & Sidecars | Isolated tool containers with ephemeral RBAC |
| Security | Defence-in-depth at every layer |
| Writing Skills | Build your own SkillPacks |
| Writing Tools | Add new tools to the agent runner |
| Ollama & Local Inference | Node-based and in-cluster Ollama setup with auto-discovery |
Project Links¶
- GitHub Repository
- Releases
- License — Apache 2.0