Architecture Mapping
Multi-Agent Orchestration — Microservices Analogy
🟦 Microservices
🟪 Agents
💡
Message:
Agents are microservices with cognition — same patterns, new intelligence.
| Microservices Concept | Agentic AI Equivalent | Tools (AWS / Azure / OSS) | Key Patterns |
|---|---|---|---|
|
🟦 API Gateway / BFF Single entrypoint for clients |
🟪 Orchestrator + Entry Agent Front-door agent + routing logic |
AWS API Gateway, ALB Azure API Management Kong, NGINX, Traefik |
Central entrypoint Task routing & policy enforcement |
|
🔄 Workflow Engine Step Functions, Durable Functions |
🤖 Multi-Agent Orchestration LangGraph, AutoGen, Swarm |
AWS Step Functions Azure Durable Functions, Logic Apps Temporal.io, Camunda |
Agent DAGs & flows Multi-step reasoning, retries, fallbacks |
|
🧩 Microservice Single bounded-context service |
🧠 Individual Agent Planner, Researcher, Executor, Reviewer |
ECS/EKS/Lambda AKS/Container Apps/Functions Any language runtime |
Single-responsibility cognition Specialized roles per domain |
|
🔌 REST / gRPC Call Service-to-service invocation |
🛠️ Agent-Tool or Agent-Agent Call Tool calling & agent APIs |
HTTP/JSON, gRPC OpenAI/Azure function calling LangChain tools |
Contract-driven calls JSON schemas & structured outputs |
|
📡 Message Bus Kafka, SQS, Service Bus |
🛰️ Agent Event Bus / Conversation Backbone Shared async message fabric |
AWS SQS/SNS/EventBridge Azure Service Bus/Event Grid Kafka, NATS, Redis Streams |
Event-driven agents Async coordination & replayable traces |
|
🗄️ Database / Cache Service state & caching |
📚 Agent Memory Store / Knowledge Base Short/long-term memory, RAG |
DynamoDB, RDS, Redis Cosmos DB, SQL, Redis Vector DBs: Azure AI Search, Pinecone, OpenSearch |
Episodic + semantic memory RAG pipelines over enterprise data |
|
🕸️ Service Mesh Discovery, retries, mTLS, policies |
🧬 Agent Mesh / Routing Fabric Dynamic agent & model routing |
Istio, Linkerd, AWS App Mesh OPA/Rego policy engine LangGraph routing logic |
Policy-driven routing Task- and capability-based agent selection |
|
⚡ Circuit Breakers / Retries Protect against cascading failure |
🛡️ Guardrails, Fallback, Agent Reassignment Safety & resilience strategies |
AWS Bedrock Guardrails Azure AI Content Filters Guardrails AI, NeMo Guardrails |
Safe outputs & constraints Backup agents, multi-model fallback |
|
📊 Logging / Tracing / Metrics Observability stack |
🔍 Agent Telemetry Thoughts, tool calls, cost & latency |
CloudWatch, X-Ray App Insights, Log Analytics OpenTelemetry, Prometheus, Grafana |
Conversation traces Cost tracking & tool-call metrics |
|
📃 API Contracts (OpenAPI) Schema-first API design |
🧾 Tool Schemas / Function Definitions Contract-first tool design |
OpenAPI, JSON Schema Pydantic models OpenAI/Azure tool schemas |
Schema-first prompts Strict validation & re-ask on violation |
Architecture Mapping
Multi-Agent Orchestration — Microservices Analogy
🟦 Microservices
🟪 Agents
💡
Message:
Agents are microservices with cognition — same patterns, new intelligence.
| Microservices Concept | Agentic AI Equivalent | Tools (AWS / Azure / OSS) | Key Patterns |
|---|---|---|---|
|
🟦 API Gateway / BFF Single entrypoint for clients |
🟪 Orchestrator + Entry Agent Front-door agent + routing logic |
AWS API Gateway, ALB Azure API Management Kong, NGINX, Traefik |
Central entrypoint Task routing & policy enforcement |
|
🔄 Workflow Engine Step Functions, Durable Functions |
🤖 Multi-Agent Orchestration LangGraph, AutoGen, Swarm |
AWS Step Functions Azure Durable Functions, Logic Apps Temporal.io, Camunda |
Agent DAGs & flows Multi-step reasoning, retries, fallbacks |
|
🧩 Microservice Single bounded-context service |
🧠 Individual Agent Planner, Researcher, Executor, Reviewer |
ECS/EKS/Lambda AKS/Container Apps/Functions Any language runtime |
Single-responsibility cognition Specialized roles per domain |
|
🔌 REST / gRPC Call Service-to-service invocation |
🛠️ Agent-Tool or Agent-Agent Call Tool calling & agent APIs |
HTTP/JSON, gRPC OpenAI/Azure function calling LangChain tools |
Contract-driven calls JSON schemas & structured outputs |
|
📡 Message Bus Kafka, SQS, Service Bus |
🛰️ Agent Event Bus / Conversation Backbone Shared async message fabric |
AWS SQS/SNS/EventBridge Azure Service Bus/Event Grid Kafka, NATS, Redis Streams |
Event-driven agents Async coordination & replayable traces |
|
🗄️ Database / Cache Service state & caching |
📚 Agent Memory Store / Knowledge Base Short/long-term memory, RAG |
DynamoDB, RDS, Redis Cosmos DB, SQL, Redis Vector DBs: Azure AI Search, Pinecone, OpenSearch |
Episodic + semantic memory RAG pipelines over enterprise data |
|
🕸️ Service Mesh Discovery, retries, mTLS, policies |
🧬 Agent Mesh / Routing Fabric Dynamic agent & model routing |
Istio, Linkerd, AWS App Mesh OPA/Rego policy engine LangGraph routing logic |
Policy-driven routing Task- and capability-based agent selection |
|
⚡ Circuit Breakers / Retries Protect against cascading failure |
🛡️ Guardrails, Fallback, Agent Reassignment Safety & resilience strategies |
AWS Bedrock Guardrails Azure AI Content Filters Guardrails AI, NeMo Guardrails |
Safe outputs & constraints Backup agents, multi-model fallback |
|
📊 Logging / Tracing / Metrics Observability stack |
🔍 Agent Telemetry Thoughts, tool calls, cost & latency |
CloudWatch, X-Ray App Insights, Log Analytics OpenTelemetry, Prometheus, Grafana |
Conversation traces Cost tracking & tool-call metrics |
|
📃 API Contracts (OpenAPI) Schema-first API design |
🧾 Tool Schemas / Function Definitions Contract-first tool design |
OpenAPI, JSON Schema Pydantic models OpenAI/Azure tool schemas |
Schema-first prompts Strict validation & re-ask on violation |