"The Kubernetes of AI Agents" — A multi-tenant, zero-trust operating system for autonomous agent execution.
E-GAOP is designed as a distributed orchestration system, decoupling the management of agent lifecycles from their execution, memory, and policy layers.
graph TD
subgraph "Control Plane (Brain)"
API[API Server] --> Registry[Agent Registry]
Registry --> Temporal[Temporal Workflow Engine]
API --> Secret[Dynamic Secret Store]
end
subgraph "Execution Plane (Body)"
Sandbox[gVisor Sandbox]
Proxy[Tool Proxy]
Router[LLM Router]
end
subgraph "Memory Plane (Senses)"
Working[Redis Working Mem]
Entity[PG Entity Mem]
Semantic[Vector DB]
end
subgraph "Policy Plane (Immune System)"
OPA[OPA/Rego Engine]
PII[PII Detection]
end
subgraph "Observability Plane (Consciousness)"
Collector[OTel Collector]
Replay[Execution Replay Gen]
end
Temporal --> Sandbox
Sandbox --> Proxy
Proxy --> OPA
Proxy --> Secret
Sandbox --> Router
Router --> Collector
| Feature | Legacy Agent Frameworks | E-GAOP Platform |
|---|---|---|
| Isolation | Single process (Local) | Kernel-Level (gVisor/Firecracker) |
| Durability | Ephemeral, lost on crash | Persistent (Temporal Workflows) |
| Security | Shared API Keys | Dynamic Secret Injection |
| Governance | None / Hardcoded | OPA-based Runtime Policies |
| Observability | Console logs | Deterministic Execution Replay |
| Scalability | Laptop-scale | Kubernetes-native (FAANG level) |
E-GAOP treats agents as untrusted workloads with strictly defined resources:
| Primitive | Description | Analogy |
|---|---|---|
AgentSpec |
The declarative definition of an agent's runtime, LLM, and tools. | PodSpec |
ToolGrant |
Fine-grained RBAC permissions for tool access. | RoleBinding |
MemoryScope |
Namespace-isolated access to Working, Session, or Entity memory. | PersistentVolume |
LLMPolicy |
Routing strategy for cost, quality, and latency optimization. | Ingress |
ExecutionRecord |
A complete trace bundle for deterministic replay. | AuditLog |
- Zero-Trust Networking: Agents have NO direct network access. All tool calls and LLM requests are proxied, validated, and scrubbed.
- Multi-Model Resiliency: Automated fallback chains across OpenAI, Anthropic, and local LLMs.
- Differential Memory: Separation of cold static facts (Entity) from hot, stateful execution context (Working).
- Security Hardening: level-4 encryption for all secrets-at-rest and in-flight.
- Orchestration: Go / gRPC / Protobuf
- Database: PostgreSQL (Entity) + Redis (Working) + Qdrant (Semantic)
- Security: OPA (Policy) + gVisor (Isolation) + AES-256 (Secrets)
- Frontend: Next.js 15 + Tailwind CSS + Lucide React
- Telemetry: OpenTelemetry (OTel) + Zipkin
egaop/
├── admin-console/ # Next.js 15 Management Interface
├── api/proto/ # Unified Resource Definitions (gRPC)
├── control-plane/ # API Server, Secret Store, Workflow Engine
├── execution-plane/ # Sandbox Runtime, Tool Proxy, LLM Router
├── memory-plane/ # Federated Memory Management
├── policy-plane/ # Rego Policies & Enforcement
└── observability-plane/ # Telemetry & Execution Replay- v0.1.0: Core Five-Plane Architecture & gRPC foundation.
- v0.2.0: Security Hardening (gVisor enforcement & Dynamic Secrets).
- v0.3.0: Distributed Durability (Full Temporal Integration).
- v0.4.0: Multi-Region Memory Plane (Global Entity Memory).
- v1.0.0: Production Stable Release.
Built with precision for the future of Autonomous Infrastructure.