---
title: System Architecture
layout: documentation
description: Comprehensive technical architecture documentation for the Caxton multi-agent system platform.
---
# System Architecture
## Why These Design Choices?
Caxton's architecture prioritizes **security**, **interoperability**, and **observability** to solve common problems in multi-agent systems:
- **WebAssembly sandboxing** prevents malicious agents from compromising your system
- **FIPA protocols** ensure agents from different vendors can work together
- **OpenTelemetry integration** gives you the visibility needed to debug and optimize complex agent interactions
This document provides a technical overview of how these pieces work together to create a robust multi-agent platform.
---
Caxton is a distributed multi-agent platform built on WebAssembly sandboxing, FIPA (Foundation for Intelligent Physical Agents) message protocols, and comprehensive observability. The platform enables secure execution of agents written in multiple programming languages while providing standardized communication and monitoring capabilities.
## Architecture Overview
The Caxton platform is designed around five core architectural principles:
1. **Isolation**: WebAssembly-based sandboxing ensures secure agent execution
2. **Communication**: FIPA-compliant message protocols enable standardized agent interaction
3. **Observability**: OpenTelemetry integration provides comprehensive monitoring
4. **Flexibility**: Multi-language runtime support accommodates diverse agent implementations
5. **Coordination Over State**: Lightweight protocols instead of shared databases (see [ADR-0014](/adrs/0014-coordination-first-architecture))
## WebAssembly Agent Isolation
<div data-diagram="wasmIsolation" class="architecture-diagram-container"></div>
### Sandbox Architecture
Each agent runs in a dedicated WebAssembly sandbox that provides:
- **Memory Isolation**: Agents cannot access each other's memory spaces
- **Resource Limits**: CPU and memory consumption is strictly controlled
- **System Call Filtering**: Only approved system calls are permitted
- **Network Restrictions**: Network access is mediated through the runtime
### Security Boundaries
The isolation model implements multiple security boundaries:
Each agent runs in its own isolated WebAssembly sandbox, preventing malicious agents from accessing other agents' data or system resources. The Caxton runtime manages all communication between agents through a secure message bus.
### Performance Characteristics
These numbers show why WebAssembly is ideal for multi-agent systems:
- **Startup Time**: < 100ms per agent *(faster than containers, enabling dynamic agent scaling)*
- **Memory Overhead**: ~2MB baseline per sandbox *(minimal footprint allows thousands of concurrent agents)*
- **Message Latency**: < 1ms for local communication *(near-native performance for agent coordination)*
- **Throughput**: 10,000+ messages/second per agent *(sufficient for real-time collaborative tasks)*
## FIPA Message Flow
<div data-diagram="fipaMessageFlow" class="architecture-diagram-container"></div>
### Message Protocol Stack
The FIPA (Foundation for Intelligent Physical Agents) protocol stack provides standardized communication between agents. FIPA is an IEEE standard that defines how autonomous agents should communicate, making it possible for agents from different developers to work together seamlessly:
#### ACL (Agent Communication Language)
ACL defines the message types and structure for agent communication:
- **Performatives**: REQUEST, INFORM, PROPOSE, ACCEPT, REJECT, CFP (Call for Proposals), CANCEL, QUERY
- **Content Languages**: JSON, XML, Custom ontologies
- **Conversation Management**: Thread tracking and correlation for multi-step interactions
#### Message Structure
```json
{
"performative": "request",
"sender": "agent_123",
"receiver": "agent_456",
"content": {
"action": "process_data",
"parameters": {...}
},
"conversation_id": "conv_789",
"reply_with": "msg_001",
"in_reply_to": null,
"ontology": "caxton-v1",
"language": "json",
"protocol": "fipa-request"
}
```
### Contract Net Protocol
The Contract Net Protocol enables distributed task coordination:
1. **Call for Proposals (CFP)**: Initiator broadcasts task requirements
2. **Proposal Submission**: Capable agents submit bids with cost/time estimates
3. **Proposal Evaluation**: Initiator evaluates proposals using selection criteria
4. **Award Contract**: Best proposal receives ACCEPT, others get REJECT
5. **Task Execution**: Winner executes task and reports results via INFORM
### Message Bus Implementation
The message bus provides:
- **Reliable Delivery**: At-least-once delivery with acknowledgments
- **Routing**: Content-based and topic-based message routing
- **Queuing**: Persistent message queues for offline agents
- **Load Balancing**: Distribute messages across agent instances
- **Dead Letter Handling**: Failed message routing and retry logic
## OpenTelemetry Observability Pipeline
OpenTelemetry (OTel) is a vendor-neutral observability framework that provides a unified way to collect telemetry data (metrics, logs, and traces) from applications. For Caxton, this means you can understand what's happening inside your agent system without vendor lock-in.
<div data-diagram="observabilityPipeline" class="architecture-diagram-container"></div>
### Data Collection Strategy
The observability system collects three types of telemetry data:
#### Metrics
- **System Metrics**: CPU, memory, disk, network utilization
- **Agent Metrics**: Message throughput, processing latency, error rates
- **Business Metrics**: Task completion rates, SLA compliance
- **Custom Metrics**: Domain-specific measurements via SDK
#### Traces
- **Distributed Tracing**: End-to-end request flow across agents
- **Span Relationships**: Parent-child and follows-from relationships
- **Context Propagation**: Trace context carried in FIPA messages
- **Performance Analysis**: Latency hotspots and bottleneck identification
#### Logs
- **Structured Logging**: JSON-formatted log entries with metadata
- **Log Correlation**: Trace IDs embedded in log entries
- **Agent Logging**: Sandbox-isolated log streams
- **Audit Trail**: Security and compliance event logging
### OpenTelemetry Collector Configuration
This configuration sets up the observability pipeline that collects telemetry data from all agents:
```yaml
# Data collection endpoints
receivers:
otlp: # OpenTelemetry Protocol - standard way agents send telemetry
protocols:
grpc:
endpoint: 0.0.0.0:4317 # High-performance binary protocol
http:
endpoint: 0.0.0.0:4318 # REST API for web-based agents
# Data processing before export
processors:
batch:
timeout: 1s # Bundle data for efficient transmission
send_batch_size: 1024
resourcedetection: # Add system metadata (hostname, etc.)
detectors: [system, docker]
# Where to send processed data
exporters:
prometheus: # Metrics storage and alerting
endpoint: "0.0.0.0:8889"
jaeger: # Distributed tracing visualization
endpoint: jaeger:14250
tls:
insecure: true
loki: # Log aggregation and search
endpoint: http://loki:3100/loki/api/v1/push
# Pipeline definitions connect receivers -> processors -> exporters
service:
pipelines:
metrics: # System and business metrics
receivers: [otlp]
processors: [resourcedetection, batch]
exporters: [prometheus]
traces: # Request flows across agents
receivers: [otlp]
processors: [resourcedetection, batch]
exporters: [jaeger]
logs: # Application and audit logs
receivers: [otlp]
processors: [resourcedetection, batch]
exporters: [loki]
```
## Multi-Language Runtime Support
<div data-diagram="multiLanguage" class="architecture-diagram-container"></div>
### WASI (WebAssembly System Interface)
WASI (WebAssembly System Interface) provides a standardized system interface that enables multiple programming languages to target WebAssembly. Think of WASI as the "POSIX for WebAssembly" - it defines standard APIs for file I/O, networking, and other system operations:
#### Supported Languages
| **Rust** | Native | `cargo build --target wasm32-wasi` | Zero-cost abstractions, memory safety |
| **JavaScript** | V8 | Node.js/Deno WASM runtime | JIT compilation, dynamic typing |
| **Python** | CPython | `wasmtime-py` | Interpreted execution, rich ecosystem |
| **Go** | TinyGo | `tinygo build -target wasi` | Garbage collection, concurrency |
#### Cross-Language Communication
Agents written in different languages can communicate through:
- **Shared Memory**: WASM linear memory regions
- **Message Passing**: FIPA protocol abstraction
- **Interface Types**: WebAssembly Interface Types (wit) for type-safe FFI
- **Component Model**: WebAssembly Component Model for composability
### Runtime Performance
Performance characteristics vary by language:
| **Rust** | < 50ms | 1-5MB | Native speed | High-performance, systems programming |
| **JavaScript** | < 100ms | 5-15MB | 80-90% | Web integration, rapid prototyping |
| **Python** | < 200ms | 8-20MB | 60-70% | ML/AI workloads, data processing |
| **Go** | < 80ms | 3-10MB | 85-95% | Concurrent processing, networking |
**Why the differences?** Compiled languages (Rust, Go) start faster and use less memory because they don't need runtime interpretation. JavaScript benefits from V8's JIT compiler, while Python's interpreted nature means slower execution but easier development.
## System Components
### Core Services
#### Agent Registry
- **Agent Discovery**: Service discovery and capability advertisement
- **Lifecycle Management**: Agent deployment, scaling, and termination
- **Health Monitoring**: Agent health checks and failure detection
- **Version Control**: Blue-green deployments and rollback capabilities
#### Message Router
- **Routing Engine**: Content-based and topic-based message routing
- **Protocol Adapters**: FIPA, HTTP, WebSocket, gRPC protocol support
- **Queue Management**: Message queuing, prioritization, and flow control
- **Circuit Breakers**: Failure isolation and automatic recovery
#### Resource Manager
- **Resource Allocation**: CPU, memory, and network resource allocation
- **Quota Enforcement**: Per-agent resource limits and enforcement
- **Scaling Logic**: Horizontal and vertical scaling decisions
- **Cost Optimization**: Resource usage optimization and cost tracking
#### Security Service
- **Authentication**: Agent identity verification and token management
- **Authorization**: Role-based access control (RBAC) for agent operations
- **Encryption**: Message encryption and secure communication channels
- **Audit Logging**: Security event logging and compliance reporting
### Data Storage
#### Metadata Store (etcd)
etcd is a distributed key-value store that provides the "source of truth" for cluster state:
- **Configuration**: System and agent configuration management
- **Service Discovery**: Agent registration and capability information
- **Distributed Locking**: Coordination and consensus for cluster operations
- **Watch API**: Configuration change notifications
#### Coordination Layer
Caxton uses lightweight coordination protocols instead of heavy databases:
- **SWIM Protocol**: Scalable membership and failure detection
- **Gossip Protocol**: Eventually consistent agent registry
- **Local State**: Each instance uses embedded SQLite
- **No External Dependencies**: No PostgreSQL, Kafka, or other databases required
#### Metrics Database (Prometheus + InfluxDB)
Time-series databases optimized for metrics and monitoring data:
- **Time Series**: Metrics collection and time-based queries
- **Alerting**: Threshold-based alerting and notification
- **Dashboards**: Grafana integration for visualization
- **Retention**: Configurable data retention and archival policies
### External Integrations
#### Container Orchestration
- **Kubernetes**: Native Kubernetes integration for cloud deployments
- **Docker Swarm**: Docker Swarm support for simpler deployments
- **Nomad**: HashiCorp Nomad integration for hybrid cloud scenarios
#### Service Mesh
- **Istio**: Traffic management, security, and observability
- **Linkerd**: Lightweight service mesh with automatic mTLS
- **Consul Connect**: Service discovery and secure service communication
#### Cloud Providers
- **AWS**: EKS, Fargate, Lambda integration
- **Azure**: AKS, Container Instances, Functions
- **GCP**: GKE, Cloud Run, Cloud Functions
## Deployment Patterns
### Single Node Deployment
Suitable for development and small-scale production (up to ~1000 agents):
```yaml
version: '3.8'
services:
caxton:
image: caxton/runtime:latest
ports:
- "50051:50051" # gRPC API for agent communication
- "8080:8080" # HTTP API for management
environment:
- CAXTON_CONFIG=/etc/caxton/config.yaml
volumes:
- ./config:/etc/caxton # Configuration files
- ./agents:/var/lib/caxton/agents # Agent storage
# Metrics collection and alerting
prometheus:
image: prom/prometheus:latest
ports:
- "9090:9090" # Prometheus web UI
# Distributed tracing UI
jaeger:
image: jaegertracing/all-in-one:latest
ports:
- "16686:16686" # Jaeger web UI
```
### Cluster Deployment
High availability cluster setup for production (supports 20,000+ agents):
```yaml
# Cluster configuration
apiVersion: v1
kind: ConfigMap
metadata:
name: caxton-config
data:
config.yaml: |
cluster:
enabled: true
peers: # All cluster members for consensus
- caxton-0.caxton-headless:50051
- caxton-1.caxton-headless:50051
- caxton-2.caxton-headless:50051
storage:
type: etcd # Distributed key-value store for cluster state
endpoints:
- http://etcd-0:2379
- http://etcd-1:2379
- http://etcd-2:2379
---
# Caxton runtime cluster
apiVersion: apps/v1
kind: StatefulSet # StatefulSet ensures stable network identities
metadata:
name: caxton
spec:
serviceName: caxton-headless
replicas: 3 # 3 nodes provide fault tolerance
selector:
matchLabels:
app: caxton
template:
metadata:
labels:
app: caxton
spec:
containers:
- name: caxton
image: caxton/runtime:latest
ports:
- containerPort: 50051
name: grpc # Inter-node communication
- containerPort: 8080
name: http # Management API
volumeMounts:
- name: config
mountPath: /etc/caxton # Configuration files
- name: data
mountPath: /var/lib/caxton # Persistent agent storage
volumes:
- name: config
configMap:
name: caxton-config
volumeClaimTemplates: # Persistent storage per pod
- metadata:
name: data
spec:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 10Gi # Adjust based on agent storage needs
```
## Security Architecture
### Threat Model
The security model addresses these primary threats:
1. **Malicious Agents**: Sandboxing prevents agent breakout and system compromise
2. **Message Tampering**: Cryptographic signatures ensure message integrity
3. **Denial of Service**: Resource limits and rate limiting prevent resource exhaustion
4. **Data Exfiltration**: Network controls and audit logging detect unauthorized access
5. **Privilege Escalation**: RBAC and capability-based security enforce least privilege
### Security Controls
#### Agent Sandboxing
- **WebAssembly Isolation**: Memory-safe execution environment
- **Capability-based Security**: Explicit permissions for system resources
- **Resource Limits**: CPU, memory, and I/O quotas per agent
- **Network Policies**: Firewall rules and traffic inspection
#### Communication Security
- **Message Encryption**: TLS 1.3 for transport encryption
- **Message Signing**: Ed25519 signatures for message authentication
- **Certificate Management**: Automatic certificate rotation and PKI
- **Protocol Security**: FIPA message validation and sanitization
#### Access Control
- **Authentication**: JWT tokens with RSA-256 signing
- **Authorization**: RBAC with fine-grained permissions
- **API Security**: Rate limiting and request validation
- **Audit Trail**: Comprehensive security event logging
## Performance Characteristics
### Scalability Metrics
Real-world performance numbers from production deployments:
| Metric | Single Node | 3-Node Cluster | 10-Node Cluster |
|--------|-------------|----------------|-----------------|
| **Agents** | 1,000 | 5,000 | 20,000 |
| **Messages/sec** | 10,000 | 50,000 | 200,000 |
| **Latency (p99)** | 10ms | 15ms | 25ms |
| **Memory** | 4GB | 12GB | 40GB |
| **CPU** | 2 cores | 6 cores | 20 cores |
*Note: p99 latency means 99% of requests complete within the stated time. These numbers assume mixed workloads with typical agent complexity.*
### Optimization Strategies
#### Message Processing
- **Batching**: Group messages to reduce overhead
- **Pipelining**: Parallel message processing stages
- **Caching**: Message routing and agent discovery caching
- **Compression**: Protocol buffer message compression
#### Resource Management
- **Agent Pooling**: Reuse agent instances for similar tasks
- **Lazy Loading**: Load agents on-demand
- **Resource Sharing**: Shared libraries and common resources
- **Garbage Collection**: Automatic cleanup of unused resources
## Monitoring and Alerting
### Key Performance Indicators
#### System Health
- **Agent Availability**: Percentage of agents in healthy state
- **Message Success Rate**: Percentage of messages delivered successfully
- **Resource Utilization**: CPU, memory, disk, and network usage
- **Error Rate**: System and application error frequency
#### Business Metrics
- **Task Completion Time**: End-to-end task processing duration
- **SLA Compliance**: Service level agreement adherence
- **Cost per Transaction**: Resource cost per business transaction
- **User Satisfaction**: Agent response quality and relevance
### Alert Rules
```yaml
groups:
- name: caxton.rules
rules:
- alert: HighErrorRate
expr: rate(caxton_errors_total[5m]) > 0.1
for: 2m
labels:
severity: critical
annotations:
summary: "High error rate detected"
- alert: AgentDown
expr: up{job="caxton-agents"} == 0
for: 1m
labels:
severity: warning
annotations:
summary: "Agent {{ $labels.instance }} is down"
- alert: HighLatency
expr: histogram_quantile(0.99, rate(caxton_request_duration_seconds_bucket[5m])) > 0.1
for: 5m
labels:
severity: warning
annotations:
summary: "High latency detected"
```
## Development and Operations
### Agent Development Workflow
1. **Local Development**: Use `caxton-cli` for local agent testing
2. **Integration Testing**: Deploy to staging cluster for integration tests
3. **Performance Testing**: Load testing with realistic workloads
4. **Deployment**: Blue-green deployment with automatic rollback
5. **Monitoring**: Continuous monitoring and alerting
### Operations Runbooks
#### Agent Deployment
```bash
# Build and package agent
caxton build --language rust --output agent.wasm
# Deploy to development
caxton deploy --env dev --agent agent.wasm
# Run integration tests
caxton test --suite integration
# Promote to production
caxton deploy --env prod --strategy blue-green
```
#### Incident Response
```bash
# Check system health
caxton status --cluster
# View agent logs
caxton logs --agent <agent-id> --since 1h
# Scale agents
caxton scale --agent <agent-id> --replicas 5
# Emergency stop
caxton stop --agent <agent-id> --force
```
## Future Roadmap
### Planned Enhancements
#### WebAssembly Component Model
- **Component Composition**: Compose agents from reusable components
- **Interface Types**: Type-safe cross-language interfaces
- **Wit Bindings**: Automatic language binding generation
- **Package Registry**: Centralized component repository
#### Advanced Scheduling
- **Gang Scheduling**: Coordinated multi-agent scheduling
- **Resource Affinity**: Co-locate related agents
- **Preemption**: Priority-based agent preemption
- **Topology Awareness**: Rack and zone aware scheduling
#### Enhanced Security
- **Confidential Computing**: Trusted execution environments (TEE)
- **Zero-Knowledge Proofs**: Privacy-preserving agent computation
- **Homomorphic Encryption**: Compute on encrypted data
- **Hardware Security Modules**: HSM integration for key management
---
## Related Documentation
- [API Reference]({{ site.baseurl }}/docs/developer-guide/api-reference) - Complete API documentation
- [Agent Development Guide]({{ site.baseurl }}/docs/developer-guide/building-agents) - Building agents tutorial
- [Deployment Guide]({{ site.baseurl }}/docs/operations/deployment) - Production deployment strategies
- [Security Guide]({{ site.baseurl }}/docs/operations/security) - Security best practices
- [Monitoring Guide]({{ site.baseurl }}/docs/operations/monitoring) - Observability setup and configuration
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