Agent Pod

Overview

An Agent Pod is the foundational compute environment where a single AI agent executes.

Each Agent Pod delivers dedicated resources and runtime isolation, ensuring agents operate independently without sharing infrastructure.

Core Principle: 1 Agent = 1 Agent Pod

Agent A → Agent Pod A (GPU + Runtime + Model A + Data A)
Agent B → Agent Pod B (GPU + Runtime + Model B + Data B)
Agent C → Agent Pod C (GPU + Runtime + Model C + Data C)

Pod Architecture

┌─────────────────────────────────────┐
│              Agent Pod              │
├─────────────────────────────────────┤
│  ┌──────────────────────────────┐   │
│  │         Container            │   │
│  │  ┌─────────────────────┐     │   │
│  │  │   Agent Runtime     │     │   │
│  │  │   (OpenClaw)        │     │   │
│  │  ├─────────────────────┤     │   │
│  │  │   Model Runtime     │     │   │
│  │  │   (Ollama)          │     │   │
│  │  ├─────────────────────┤     │   │
│  │  │   Local LLM         │◄────┼───│← Model Weights
│  │  └─────────────────────┘     │   │
│  │  ├─────────────────────┤     │   │
│  │  │   Agent Tools       │     │   │
│  │  └─────────────────────┘     │   │
│  └──────────────────────────────┘   │
├─────────────────────────────────────┤
│  Compute: GPU/CPU                    │
│  Memory: 16-128GB                    │
│  Storage: 50GB+ Persistent           │
│  Networking: Managed Endpoints       │
└─────────────────────────────────────┘

Compute Resources

Agent Pods provision tailored compute based on agent requirements:

Resources scale dynamically based on deployment configuration.

Runtime Environment

The Agent Pod container orchestrates:

1. Agent Framework (OpenClaw) - Handles request processing and tool execution
2. Model Runtime (Ollama) - Manages local LLM inference
3. Local LLM - Loaded model weights for autonomous reasoning
4. Tools - Custom functions and integrations

Pod Start → Load Framework → Initialize Model → Agent Ready → Process Requests

Multi-Level Isolation

Agent Pods enforce comprehensive isolation:

┌─────────────────────────────┐
│  COMPUTE ISOLATION          │ ← Dedicated hardware allocation
├─────────────────────────────┤
│  RUNTIME ISOLATION          │ ← Separate container processes
├─────────────────────────────┤
│  DATA ISOLATION             │ ← Private storage + memory
├─────────────────────────────┤
│  NETWORK ISOLATION          │ ← Managed endpoints only
└─────────────────────────────┘

Zero shared state between agents prevents interference, data leakage, and resource contention.

Pod Lifecycle

Deploy Agent → Create Pod → Pod Running → (Start/Stop/Resume) → Terminate Agent → Destroy Pod

Summary

Agent Pods power MoltGhost's isolation model by providing each agent with:

✅ Dedicated compute (GPU/CPU/Memory/Storage)
✅ Isolated runtime (OpenClaw + Ollama)
✅ Local model execution
✅ Multi-level isolation guarantees
✅ Full lifecycle control

Agent Pods enable production-grade AI agents that scale independently without infrastructure conflicts.