Agent Fabric & Agent Network Governance (Course #agent-fabric)

For solution architects, platform engineers, AI integration leads.

Ref#agent-fabric
Duration2 days
Formats4 ways
Cert prep—
Prerequisites1

By the end, you can

By the end of this course, you will be able to operate a governed agent network on MuleSoft Agent Fabric — a registered agent catalog, a versioned agent-network.yaml, Omni Gateway agent policies and Agent Visualizer traces — so that every agent-to-agent call has an owner, a budget and a record.

Running case study

Solvane Health Group runs 6 country operations on 130 Mule APIs and has accumulated 38 agents across Agentforce, Amazon Bedrock and Microsoft Copilot — none registered, none behind a gateway, and three of them already chained into a triage assistant by hand-written glue. Clinical data may not leave the EU, the agent budget is capped at €18k/month, and the platform team must stand up a governed agent network under hard targets: 100% of production agents fronted by Omni Gateway, broker routing under 400 ms p95, and every delegated task traceable from broker to tool.

Programme every line is something you do

5 modules · 15 topics · in course-flow order

  1. Module 1

    Inventory the agent estate

    Objective. Diagnose the unregistered agent estate and produce a Portfolio catalog entry for every agent, MCP server and model proxy in scope.

    • Register agents, MCP servers and LLM proxies in the Anypoint Exchange portfolio, each entry carrying owner, environment and tier metadata
    • Run agent scanners against Amazon Bedrock, Google Vertex AI and Microsoft Copilot, reconciling what they discover against a declared inventory of 38 agents
    • Gate the catalog before any orchestration starts: ≥ 95% of production entries name an owner and state a data-residency zone
  2. Module 2

    Agent networks as code

    Objective. Construct an agent network from a versioned agent-network.yaml and deploy it to CloudHub 2.0 as a reviewable artefact.

    • Declare the registry and context sections of agent-network.yaml — agents, agent brokers, LLMs, MCP servers, policies — in Anypoint Code Builder
    • Split reasoning from control flow in Agent Script: orchestrator and subagent nodes for judgement, executor, router and echo nodes for everything else (target: ≥ 60% of graph nodes deterministic)
    • Publish assets to Exchange and deploy to a CloudHub 2.0 private space through the Anypoint CLI Agent Fabric plugin (target: reproducible rebuild in ≤ 15 min)
  3. Module 3

    Speak A2A, expose MCP

    Objective. Construct the protocol surface of the network — A2A-compliant Mule apps and MCP servers — and measure the context cost of every tool exposed.

    • Make Mule applications A2A-compliant with the A2A Connector and publish one accurate agent card per agent, pinned to A2A 1.0
    • Turn existing APIs into MCP servers with the MCP Bridge, exposing only the tools an agent actually needs (ceiling: 12 tools per server)
    • Cut context spend with MCP Tool Mapping and MCP Tools Progressive Disclosure (target: −30% prompt tokens per task versus a full tool listing)
  4. Module 4

    Policy on every agent hop

    Objective. Design the Omni Gateway policy set for agent traffic and prove enforcement on both A2A and MCP hops.

    • Front every A2A agent and MCP server with an Agent and Tool Instance in API Manager (target: 100% of production agents, 0 direct upstream routes)
    • Chain A2A PII Detector, A2A Schema Validation and MCP PII Detector, then prove each with negative tests carrying seeded patient identifiers across 5 PII categories
    • Bound blast radius with MCP Global Access allow/block rules and MCP Attribute-Based Access Control: every write tool blocked by default, at most 3 exceptions per network, each with a named approver
  5. Module 5

    Bound the runaway network

    Objective. Evaluate agent-network behaviour against its failure modes and set the limit that stops each one.

    • Trace a failed task from broker to subagent to MCP tool in Agent Visualizer and Anypoint Monitoring (lookback 30 minutes to 30 days, default 24 hours)
    • Cap runaway reasoning in the network spec — max_number_of_loops (default 25), max_consecutive_errors, task_timeout_secs — sized against a 400 ms p95 routing budget
    • Alert on what Agent Visualizer actually exposes: agents outside policy coverage and failed-request rate above 2%, with a runbook entry written for each

References & Official Documentation every claim above has a source

Module 1

Module 2

Module 3

Module 5

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