Data Flow Lifecycle
Relevant source files
The following files were used as context for generating this wiki page:
The Data Flow Lifecycle in Nexus Orchestrator governs how information moves between AI agents, the orchestration layer, and the underlying infrastructure. Nexus acts as an Autonomous Infrastructure Daemon, providing a "nervous system" that manages state, connectivity, and security for non-human identities.
This lifecycle ensures that data transition from raw agent requests into managed infrastructure actions while maintaining strict governance and persistent context. The system bridges the "infrastructure gap" by synthesizing protocols like MCP and LangGraph into a cohesive execution flow.
Sources: README.md:1-10, README.md:12-18
Core Architectural Pillars
The lifecycle is supported by four primary layers that handle data at different stages of its journey:
| Layer | Responsibility | Primary Technology |
|---|---|---|
| Connectivity | Agent-to-infrastructure communication | MCP-based protocol |
| Orchestration | Workflow management and execution logic | LangGraph |
| Context | Persistent state and agent tracking | AGENTS.md / Context files |
| Governance | Security and identity validation | OPA + Zero Trust |
Sources: README.md:12-18
Data Movement and Execution Flow
The flow of data starts with an AI agent's intent and progresses through validation, orchestration, and final state persistence.
Infrastructure Orchestration Flow
The following diagram illustrates the path a request takes through the Nexus system:
Nexus functions as a local-first, background orchestration layer. Data flows through an MCP-based protocol to establish connectivity before being validated by the Governance layer using Open Policy Agent (OPA) and Zero Trust principles.
Sources: README.md:3-8, README.md:12-18
Agent Identity and State Management
Nexus maintains a registry of known agents and their specific trust levels. This information is critical for the lifecycle as it determines the permissions granted during the Governance phase.
Agent Tracking Schema
Data regarding interacting agents is persisted in the context/AGENTS.md file using the following structure:
| Field | Description | Relevance to Lifecycle |
|---|---|---|
| Agent ID | Unique identifier for the AI agent | Used for state mapping and logging |
| Description | Human-readable role of the agent | Contextual awareness for orchestrator |
| Trust Level | Assigned security tier | Dictates OPA policy application |
Sources: context/AGENTS.md:1-8
Sequence of Interaction
This sequence diagram shows the interaction between a new agent and the Nexus Orchestrator state:
Sources: README.md:5-18, context/AGENTS.md:3-8
Governance and Security Enforcement
The lifecycle integrates a Zero Trust security model specifically designed for non-human identities. Every data packet or instruction sent through the Connectivity Layer is subjected to governance checks.
- Autonomous Infrastructure Daemon: The system operates in the background to manage SSH connectivity and context files autonomously.
- Zero Trust: No agent is inherently trusted; identity must be verified against the state tracked in the Context Layer.
- OPA Governance: Policies are applied to ensure that the "infrastructure gap" is bridged without compromising the host environment.
Sources: README.md:5-10, README.md:18
Summary
The Data Flow Lifecycle in Nexus Orchestrator transforms high-level AI agent intents into secure infrastructure operations. By utilizing MCP for connectivity and LangGraph for workflow management, the system ensures that data remains contextualized and governed. The persistence of agent metadata in the Context Layer allows for a continuous, secure "nervous system" that supports autonomous AI development.