Distributed AI Agent Coordination & Task Queue Sync
A distributed system architecture and orchestrator that coordinates local AI agents across multiple devices with real-time state synchronization.
Running AI agents on single devices hits hardware walls, while cloud deployments create high running costs and compromise data privacy.
Enables teams to coordinate local consumer hardware to run complex AI workflows, reducing cloud costs and protecting data.
Interactive dashboard orchestrating task assignments and agent capacities.
Tracks status updates and resources across connected hardware nodes.
Protects communication between devices utilizing local encryption.
Distributed orchestration system. Master hubs coordinate queues and assign workloads to local node devices using private local connections.
User Task ──> Orchestration Master (Rust) ──> Task Queue Manager
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┌────────────────────────────────────────────┘
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Local Node A (Tauri) <──[Encrypted RPC Stream]── Local Node B (Mobile App)harizeon-congent/ ├── src-tauri/ # Rust core code │ ├── src/ │ │ ├── main.rs # Orchestrator entry │ │ └── queue.rs # Task queue logic ├── src/ # Frontend application │ ├── components/ │ │ └── Dispatcher.tsx # Queue controller │ └── App.tsx
Run active operations audits utilizing the custom sandbox telemetry receiver widget below.
Dispatch tasks dynamically across synchronized hardware node networks.
Devices connect and disconnect unpredictably on local networks, needing automatic sync.
Raft-based master consensus
Accepted high consensus network traffic to ensure total consistency and prevent duplicate task assignments.
Integrate gossip protocols to manage node listings and lower consensus traffic overhead.
Intruders on local networks could spoof nodes and steal agent instructions.
Optim:Using binary serialization patterns and lightweight local UDP connection streams.
Nodes frequently dropped offline mid-execution, causing tasks to get stuck in processing states indefinitely.
Root Cause:Platform lacked active heartbeat checks to monitor node health and handle task reassignments.
Monitored logs under high node churn, confirming that dead nodes remained assigned to active tasks.
Implemented heartbeat monitors. If a node fails to check in for 15 seconds, the master marks it offline and returns tasks to the queue.
Slightly increased local network traffic due to continuous check-in signals.
Distributed systems must assume failures are normal and implement active checks to verify node health.
Rust is excellent for building memory-safe and predictable orchestrator components.
Event-driven queues are critical to prevent packet blockages when nodes disconnect.
Utilizing local hardware resources reduces enterprise running costs and increases data privacy.
I would convert the state sync to run over WebRTC to support browser nodes without local installation.
Audit raw repository script configurations directly inside the active terminal workspace.
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