Agent Lifecycle Management

Caxton provides comprehensive agent lifecycle management capabilities for deploying, managing, and maintaining WebAssembly agents in production environments.

Overview

The Agent Lifecycle Management system provides:

Secure WASM Deployment: Deploy agents from validated WASM modules
State Management: Type-safe lifecycle transitions with comprehensive tracking
Hot Reload: Zero-downtime updates with multiple deployment strategies
Resource Control: Configurable memory and CPU limits with enforcement
Fault Isolation: Failed agents don’t affect other agents in the system
Validation Pipeline: Comprehensive WASM module validation before activation

Agent Lifecycle States

Agents follow a well-defined state machine:

Unloaded → Loaded → Running ⇄ Draining → Stopped
                      ↓
                   Failed

State Descriptions

Unloaded: Agent is not present in the system
Loaded: WASM module loaded and validated, but not executing
Running: Agent is actively processing messages
Draining: Agent finishing current work before shutdown
Stopped: Agent cleanly shut down, resources released
Failed: Agent encountered an error and was terminated

Deployment Operations

Basic Agent Deployment

Deploy an agent from a WASM module:

use caxton::{AgentLifecycleManager, DeploymentConfig, AgentVersion};

let manager = AgentLifecycleManager::new(/* dependencies */);

// Deploy agent
let result = manager.deploy_agent(
    agent_id,
    Some(agent_name),
    AgentVersion::generate(),
    version_number,
    DeploymentConfig::immediate(),
    wasm_bytes,
).await?;

Deployment Strategies

Immediate Deployment

Replaces agent instantly
Minimal deployment time
Brief service interruption

let config = DeploymentConfig::immediate();

Rolling Deployment

Gradual replacement of instances
Configurable batch size
Maintains service availability

let config = DeploymentConfig::rolling(BatchSize::try_new(3)?);

Blue-Green Deployment

Deploy to parallel environment
Switch traffic instantly
Easy rollback capability

let config = DeploymentConfig::new(DeploymentStrategy::BlueGreen);

Canary Deployment

Deploy to subset of instances
Gradual traffic increase
Automatic rollback on issues

let config = DeploymentConfig::canary();

Hot Reload Operations

Zero-Downtime Updates

Hot reload enables updating agents without service interruption:

// Perform hot reload
let result = manager.hot_reload_agent(
    agent_id,
    Some(agent_name),
    new_version,
    version_number,
    HotReloadConfig::new(HotReloadStrategy::Graceful),
    new_wasm_bytes,
).await?;

Hot Reload Strategies

Graceful Strategy

Allows current requests to complete
Starts new version in parallel
Switches after warmup period

Traffic Splitting Strategy

Routes percentage of traffic to new version
Gradually increases traffic split
Monitors metrics for issues

Parallel Strategy

Runs both versions simultaneously
Compares responses for validation
Switches after verification

Resource Management

Setting Resource Limits

Configure memory and CPU limits during deployment:

let config = DeploymentConfig {
    strategy: DeploymentStrategy::Immediate,
    resource_requirements: ResourceRequirements::new(
        DeploymentMemoryLimit::from_mb(10)?,  // 10MB limit
        DeploymentFuelLimit::try_new(100_000)?, // 100K CPU cycles
    ),
    // ... other config
};

Resource Enforcement

The system enforces limits through:

Memory Limits: WebAssembly linear memory restrictions
CPU Limits: Fuel-based execution metering
Execution Time: Configurable timeouts for operations
Message Size: Limits on incoming/outgoing message sizes

WASM Module Validation

Validation Pipeline

All WASM modules undergo comprehensive validation:

Structure Validation: Valid WASM format and sections
Security Analysis: Dangerous features detection
Resource Analysis: Memory and import requirements
Function Validation: Required exports present
Custom Rules: User-defined validation criteria

Security Policies

The validator enforces security policies:

let policy = WasmSecurityPolicy {
    max_memory_pages: 16,           // 1MB max memory
    max_imports: 10,                // Limited imports
    allowed_imports: vec![          // Whitelist approach
        "env.print".to_string(),
    ],
    deny_unsafe_features: true,     // Block SIMD, etc.
};

Monitoring and Observability

Agent Status Tracking

Monitor agent health and status:

let status = manager.get_agent_status(agent_id).await?;

println!("State: {:?}", status.lifecycle.current_state);
println!("Memory: {} bytes", status.memory_allocated);
println!("Uptime: {:?}", status.uptime);
println!("Health: {:?}", status.health_status);

Performance Metrics

Track deployment and operation metrics:

Deployment duration and success rates
Hot reload performance and rollback frequency
Resource utilization per agent
Message processing latency
Error rates and failure patterns

Error Handling and Recovery

Fault Isolation

The system provides strong isolation guarantees:

Process Isolation: Each agent in separate WASM instance
Memory Isolation: No shared memory between agents
Failure Containment: Failed agents don’t affect others
Resource Protection: Limits prevent resource exhaustion

Recovery Strategies

When agents fail:

Automatic Restart: Failed agents restarted with exponential backoff
Circuit Breaking: Repeated failures trigger circuit breaker
Graceful Degradation: System continues with remaining healthy agents
Rollback: Automatic rollback to previous working version

Error Categories

Common failure scenarios and handling:

Validation Errors: WASM module rejected before deployment
Resource Exhaustion: Agent stopped when exceeding limits
Runtime Errors: Agent restarted or marked as failed
Deployment Failures: Rollback to previous stable version

Best Practices

Development

Validate Early: Test WASM modules with validator before deployment
Resource Planning: Right-size memory and CPU limits
Error Handling: Implement proper error responses in agents
Testing: Use hot reload for rapid development iteration

Production

Gradual Rollouts: Use canary deployments for major changes
Monitoring: Track agent health and performance metrics
Resource Margins: Set limits with headroom for growth
Backup Strategy: Maintain previous versions for quick rollback

Performance

Batch Operations: Group multiple agent operations when possible
Resource Reuse: Pool and reuse WASM instances where appropriate
Monitoring Overhead: Balance observability with performance impact
Load Testing: Validate performance under expected load patterns

API Reference

AgentLifecycleManager

impl AgentLifecycleManager {
    // Deploy new agent
    async fn deploy_agent(&self, ...) -> Result<DeploymentResult>;

    // Update existing agent
    async fn hot_reload_agent(&self, ...) -> Result<HotReloadResult>;

    // Stop agent gracefully
    async fn stop_agent(&self, agent_id: AgentId, timeout: Option<Duration>)
        -> Result<OperationResult>;

    // Remove agent completely
    async fn remove_agent(&self, agent_id: AgentId) -> Result<OperationResult>;

    // Get agent status
    async fn get_agent_status(&self, agent_id: AgentId) -> Result<AgentStatus>;

    // List all agents
    async fn list_agents(&self) -> Result<Vec<AgentStatus>>;
}

For complete API documentation, see the API Reference.

Troubleshooting

Common Issues

Deployment Failures

Check WASM module validation errors
Verify resource requirements are available
Ensure agent exports required functions

Hot Reload Issues

Monitor traffic split and rollback triggers
Check version compatibility requirements
Verify new version passes health checks

Performance Problems

Review resource limit settings
Analyze agent message processing patterns
Check for memory leaks in agent code

State Transition Errors

Ensure proper lifecycle state management
Check for concurrent operation conflicts
Review timeout configurations

For additional support, see the Operational Runbook.