Architecture
An event-driven agent mesh architecture using a Kafka-style event broker. Multiple agents subscribe to topics (orders, alerts, analytics), process events independently, and publish results back to the bus. Best for real-time event processing and decoupled service architectures.
Source { # Event Sources
n1: circle label="Start"
n2: rectangle label="User action event"
n3: rectangle label="System alert event"
n1.handle(right) -> n2.handle(left)
n2.handle(bottom) -> Broker.n4.handle(top) [label="Publish event"]
n3.handle(bottom) -> Broker.n4.handle(top) [label="Publish event"]
}
Broker { # Event Broker (Kafka / Pub-Sub)
n4: rectangle label="Event bus receives event"
n5: rectangle label="Route to subscribers"
n4.handle(right) -> n5.handle(left)
n5.handle(bottom) -> Orders.n6.handle(top) [label="topic: orders"]
n5.handle(bottom) -> Alerts.n8.handle(top) [label="topic: alerts"]
n5.handle(bottom) -> Analytics.n10.handle(top) [label="topic: analytics"]
}
Orders { # Order Processing Agent
n6: rectangle label="Parse order event"
n7: rectangle label="Execute fulfillment"
n6.handle(right) -> n7.handle(left)
n7.handle(bottom) -> Broker.n4.handle(top) [label="Publish: order.completed"]
}
Alerts { # Alert Triage Agent
n8: rectangle label="Classify severity"
n9: rectangle label="Route to on-call or auto-resolve"
n8.handle(right) -> n9.handle(left)
n9.handle(bottom) -> Broker.n4.handle(top) [label="Publish: alert.resolved"]
}
Analytics { # Analytics Agent
n10: rectangle label="Aggregate metrics"
n11: rectangle label="Update dashboard"
n12: circle label="Stored"
n10.handle(right) -> n11.handle(left)
n11.handle(right) -> n12.handle(left)
}
Architecture
An event-driven agentic AI architecture that replaces the central orchestrator with Kafka/PubSub topics: agents subscribe, react, and publish new events. This aligns multi-agent systems with proven microservices choreography and is ideal for real-time, high-throughput systems and 'agent mesh' setups.
Architecture
A database-per-service architecture diagram where each microservice owns its dedicated data store, with event-driven synchronization via Kafka for cross-service data consistency. This template demonstrates the core microservices data isolation principle, showing how PostgreSQL and MongoDB coexist in a polyglot persistence strategy. Critical for architects enforcing service autonomy while maintaining eventual consistency.
Architecture
An event-driven publish-subscribe architecture diagram with Kafka or RabbitMQ message broker, event serialization, topic partitioning, fan-out delivery to multiple consumers, and dead letter queue error handling. This template models the foundational async messaging pattern where producers and consumers are fully decoupled through a message broker. Essential for architects building loosely coupled, scalable event-driven systems.
Architecture
An event-driven choreography architecture diagram where microservices coordinate through events without a central orchestrator, with Order, Payment, Inventory, and Shipping services reacting to each other's domain events. This template models the decentralized coordination pattern where each service knows only its own responsibilities and publishes events for others to consume. Best for teams favoring autonomous services over centralized workflow control.
Architecture
The simplest AI-native architecture — a single agent that receives user input, reasons, plans, decides on tool calls, processes results, and generates responses. Direct MCP connection over stdio or HTTP. Best for MVPs and when low latency matters.
Architecture
An assembly-line architecture where agents are arranged in a strict sequence. Each agent transforms or enriches the output of the previous one, then passes it forward. Best for tasks with clear sequential dependencies — document processing, content production pipelines, compliance workflows.