Agent Mesh for Enterprise Agents

a year ago

Enterprises have evolved software architectures from mainframes to microservices to meet scalability, flexibility, and adaptability demands.
Agentic systems require dynamic networking that supports intelligent adaptive policies and semantic context, unlike legacy deterministic workflows.
An agent mesh provides security, observability, discovery, and governance for agent interactions, solving AI-specific networking challenges.
Key properties of an agent mesh include secure by default, fine-grained access control, end-to-end observability, and modern ops models.
Agent to LLM communication requires policies like guardrails, caching, and failover, with tracing and metrics for enterprise observability.
Agents need access to tools via the Model Context Protocol (MCP), which lacks enterprise readiness in security, discovery, and observability.
Multi-agent workflows benefit from smaller, focused agents, with protocols like A2A for secure, observable, and traceable interactions.
Agent identity and zero-trust architecture are crucial, using frameworks like SPIFFE and mTLS for secure communication.
The agent mesh supports diverse agents across any cloud, avoiding vendor lock-in and enabling flexible integration.
Composable architecture allows tailored infrastructure with unified access, policy enforcement, and semantic understanding at every layer.

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