ASAN's current implementation approach (Section 7.4) relies on Kubernetes/Istio for agent orchestration. This requires centralized infrastructure.
Alternative: P2P distributed deployment
SynapseNetAI (https://github.com/KeplerSynapseNet/SynapseNetAI) demonstrates a working P2P infrastructure layer that could solve ASAN's deployment challenges:
- Tor-routed P2P mesh (no central servers)
- Distributed consensus for agent registration (replaces Redis Directory)
- Built-in agent lifecycle management (spawn/kill across network nodes)
- NAT traversal for home/mobile nodes
- Gossip protocol for agent discovery
Technical fit:
- ASAN's Directory Service → Distributed hash table (DHT) on P2P overlay
- Agent containers → Distributed across peer nodes
- gRPC/Protobuf communication → Already implemented in P2P transport layer
Advantage:
No Kubernetes cluster needed. Individual contributors can join the network from consumer hardware. Aligns with decentralized-ai approach.
P.S. If you're working on ASAN implementation yourself, integrating an existing P2P infrastructure layer could accelerate deployment testing vs building distributed orchestration from scratch.
ASAN's current implementation approach (Section 7.4) relies on Kubernetes/Istio for agent orchestration. This requires centralized infrastructure.
Alternative: P2P distributed deployment
SynapseNetAI (https://github.com/KeplerSynapseNet/SynapseNetAI) demonstrates a working P2P infrastructure layer that could solve ASAN's deployment challenges:
Technical fit:
Advantage:
No Kubernetes cluster needed. Individual contributors can join the network from consumer hardware. Aligns with decentralized-ai approach.
P.S. If you're working on ASAN implementation yourself, integrating an existing P2P infrastructure layer could accelerate deployment testing vs building distributed orchestration from scratch.