Now Open Source v0.1

Infrastructure
Intelligence

Kubernetes was built for web apps. Clawbernetes is AI-native infrastructure management you talk to — deployments, diagnostics, scaling, and secrets, all through conversation. Built in Rust.

Get Started → View on GitHub
Morpheus AI Assistant
👤
You
Deploy Llama 70B inference. Need 4 H100s with low latency for production traffic.
🔮
Morpheus
Analyzing your cluster topology... I found node-01 with 8× H100s connected via NVLink — perfect for your latency requirements.
✓ Deployed in 2.3s
✓ Allocated 4× H100 (NVLink topology)
✓ Monitoring active — p99: 42ms
👤
You
What's the VRAM usage looking like?
🔮
Morpheus
VRAM utilization is healthy at 68GB/80GB per GPU. I've configured automatic scaling — if traffic spikes above 1000 req/s, I'll spin up 4 more H100s on node-02.
👤
You
Perfect. Alert me if p99 latency goes above 100ms.
🔮
Morpheus
Alert configured. I'll notify you via Slack if p99 exceeds 100ms for more than 60 seconds. Your workload is running smoothly! 🚀

What is Clawbernetes?

Clawbernetes is a conversational replacement for Kubernetes — same capabilities, none of the YAML — where you describe what you need in plain language and an AI agent handles scheduling, secrets, networking, scaling, and self-healing across CPUs, GPUs, and heterogeneous clusters.

🚀
Deployments
You "Deploy a vLLM server with Llama 3 70B on the node with the most VRAM"
Agent Selects the best node, pulls the image, starts the container with GPU passthrough, and sets up health monitoring — all in one turn.
🔍
Diagnostics
You "Why is inference slow on morpheus?"
Agent Checks GPU temps, VRAM, CPU load, and container stats. "GPU 0 at 89°C — thermal throttling. Want me to reduce batch size?"
📊
Fleet Overview
You "What GPUs do we have across the cluster?"
Agent Queries every connected node and returns a full inventory — GPU models, VRAM, utilization, temps, and running workloads per node.
🔐
Secrets Management
You "Store the HuggingFace token as a secret and rotate it monthly"
Agent Encrypts with AES-256-GCM, stores on the node, and sets up a cron rotation schedule. No Vault needed.
⚖️
Autoscaling
You "Scale the inference server between 2 and 8 replicas based on queue depth"
Agent Creates an autoscale policy, monitors the metric, and adjusts replicas automatically. Reports scaling events to you in chat.
💰
MOLT Marketplace
You "I need 4 A100s for 6 hours. Find the cheapest spot on MOLT."
Agent Scans the P2P marketplace, verifies hardware attestation, escrows MOLT tokens, and provisions the GPUs.
66K
Lines of Rust
23
Crates
2.1K
Tests
0
Unsafe in Core
5
GPU Backends
Capabilities

Everything K8s promised. Actually delivered.

🗣️

Intent-Based Operations

Describe workloads in natural language. The AI agent handles GPU selection, networking, secrets, monitoring, and scaling automatically.

🔍

AI-Native Observability

Ask "why is training slow?" and get a diagnosis. Replaces Prometheus, Grafana, Alertmanager, Loki, and Jaeger.

⚡

GPU Topology Awareness

NVLink, PCIe, VRAM-aware scheduling. The agent understands interconnect bandwidth and places workloads optimally.

🔐

Zero-Trust Security

AES-GCM encryption, attestation-based access, built-in PKI, automatic certificate and secret rotation.

🌐

Flexible Networking

WireGuard for full control, Tailscale for zero-config, or MOLT P2P for decentralized compute marketplace.

🔄

Autonomous Self-Healing

Automatic rollback with root cause analysis. The agent learns from failures and prevents recurrence.

Multi-Platform

Every GPU. One API.

NVIDIA
CUDA
H100 / A100 / RTX
✓ Ready
Apple
Metal
M1–M4 Ultra
✓ Tested
AMD
ROCm
MI300X / Radeon
✓ Ready
Cross-Platform
Vulkan
Intel / AMD / NV
✓ Ready
Fallback
CPU SIMD
AVX / NEON
✓ Ready
Comparison

Kubernetes vs Clawbernetes

Concern Kubernetes Clawbernetes
Configuration 500+ lines of YAML Natural language intent
GPU Scheduling Device plugin hacks NVLink/PCIe/VRAM native
Monitoring Prometheus + Grafana + Loki "What's wrong?" → Diagnosis
Deployments Helm + ArgoCD + Kustomize Agent-managed intents
Secrets External Secrets + Vault Built-in encrypted rotation
Language Go Rust — 0 unsafe in core
Workloads

Built for Every Workload

🤖

LLM Inference

Deploy and scale large language models with automatic batching and load balancing.

GPU Optimized
🧠

Model Training

Distributed training across nodes with checkpoint management and failure recovery.

GPU Optimized
🔄

ETL Pipelines

Data transformation workflows with intelligent scheduling and resource allocation.

CPU + GPU
📊

Batch Processing

High-throughput batch jobs with priority queuing and automatic retry logic.

CPU Workload
🎨

Image Generation

Stable Diffusion, DALL-E, and custom diffusion models at scale.

GPU Optimized
🎬

Video Processing

Transcoding, analysis, and AI-enhanced video pipelines with GPU acceleration.

GPU Optimized
🔬

Scientific Compute

Simulations, molecular dynamics, and research workloads with multi-node support.

HPC Ready
🌐

Web Services

Stateless APIs and microservices with auto-scaling and health monitoring.

CPU Workload
Architecture

Fleet-Scale GPU Orchestration

┌─────────────────────────────────────────────────────────────────────────┐ │ Control Plane │ │ ┌──────────────────────────────────────────────────────────────────┐ │ │ │ OpenClaw Gateway │ │ │ │ ┌────────────┐ ┌────────────┐ ┌────────────┐ ┌────────────┐ │ │ │ │ │ Fleet │ │ Intent │ │ Node │ │ Workload │ │ │ │ │ │ Agent │ │ Parser │ │ Registry │ │ State │ │ │ │ │ └────────────┘ └────────────┘ └────────────┘ └────────────┘ │ │ │ └──────────────────────────────────────────────────────────────────┘ │ └────────────────────────────────┬────────────────────────────────────────┘ │ WebSocket + Protobuf (TLS) │ ┌────────────────────────┼────────────────────────┐ ▼ ▼ ▼ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ clawnode │ │ clawnode │ │ clawnode │ │ 8x H100 │ │ 4x A100 │ │ M4 Ultra │ │ NVLink │ │ PCIe │ │ Metal │ └───────────────┘ └───────────────┘ └───────────────┘
Quick Start

Get Started in 5 Minutes

1

Install OpenClaw

The control plane that powers Clawbernetes.

npm install -g openclaw@latest && openclaw onboard --install-daemon
2

Build clawnode

The agent binary that runs on each machine in your fleet.

git clone https://github.com/clawbernetes/clawbernetes && cd clawbernetes && cargo install --path crates/clawnode
3

Connect a node

Generate config, run the node agent, approve from the gateway.

clawnode init-config --gateway ws://gateway:18789 && clawnode run --config ./clawnode-config.json
4

Install skills & plugin

Teach the agent infrastructure ops — deploy, scale, diagnose, heal.

cp -r skills/* ~/.openclaw/workspace/skills/ && openclaw plugins install --link ./plugin/openclaw-clawbernetes
5

Talk to your infrastructure

No YAML. No dashboards. Just tell it what you need.

"What GPUs do we have?" · "Deploy nginx on the node with the most free RAM." · "Why is inference slow?"

Ready to replace Kubernetes?

Open source. Written in Rust. MIT licensed.

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