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26 changes: 26 additions & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -289,6 +289,24 @@ All operations can be run in "dry-run" mode first:
- Maintains accurate infrastructure state
- Detects drift from expected configuration

### v2.0 Enhanced Safety Layer
- **Simulation Modes**: Full simulation, validation-only, or disabled
- **Validation Framework**: Parameter validation, dependency validation, quota checks
- **Audit Logging**: Complete operation audit trail
- **Dry-Run Decorator**: Transparent operation wrapping for safety

### v2.0 Plugin Architecture
- **Dynamic Registration**: Register and unregister resource handlers at runtime
- **Middleware Chain**: Cross-cutting concerns (logging, recovery, metrics, timeouts)
- **Hook System**: Before/after execution callbacks
- **Lifecycle Management**: Dependency-aware initialization and health monitoring

### v2.0 Enhanced Reasoning
- **Multi-Step Verification**: Pre-flight, dependency, safety, and impact phases
- **Risk Assessment**: Automatic risk level evaluation with mitigations
- **Rollback Planning**: Each operation includes rollback strategies
- **Cost Estimation**: Automatic cost calculation for planned resources

### Contributing

1. Fork the repository
Expand Down Expand Up @@ -402,6 +420,14 @@ agent:
- ✅ ReAct Agent
- ✅ Better UX/UI

### v2.0 Enhancements (Latest)
- ✅ Plugin Architecture for resource handlers
- ✅ Safety Layer with simulation mode and validation
- ✅ Enhanced reasoning with multi-step verification
- ✅ Dry-run decorator pattern
- ✅ Audit logging framework
- ✅ Cost estimation integration

### Upcoming Features (v0.1.*)
- 🔄 Cost optimization recommendations
- 🔄 Enhanced conflict resolution
Expand Down
291 changes: 291 additions & 0 deletions docs/architecture/architecture-overview.md
Original file line number Diff line number Diff line change
Expand Up @@ -345,6 +345,291 @@ The testing architecture includes a sophisticated mock system that provides real
- Secure state file storage with restricted access
- Comprehensive audit logging for compliance requirements

## Plugin Architecture (v2.0)

### Overview

The Plugin Architecture provides a modular, extensible system for managing AWS resource handlers. It enables dynamic registration, lifecycle management, and middleware chaining for all resource operations.

### Core Components

#### Plugin Registry

The central registry manages all resource handlers:

```go
type PluginRegistry struct {
handlers map[string]ResourceHandler
metadata map[string]PluginMetadata
hooks map[string][]PluginHook
middlewares map[string][]Middleware
}
```

**Key Features:**
- Dynamic plugin registration and unregistration
- Thread-safe operations with RWMutex
- Hook system for before/after execution callbacks
- Middleware chaining for cross-cutting concerns

#### Resource Handler Interface

All resource handlers implement a unified interface:

```go
type ResourceHandler interface {
Plugin
Create(ctx context.Context, params interface{}) (*types.AWSResource, error)
List(ctx context.Context) ([]*types.AWSResource, error)
Get(ctx context.Context, id string) (*types.AWSResource, error)
Update(ctx context.Context, id string, params interface{}) (*types.AWSResource, error)
Delete(ctx context.Context, id string) error
ExecuteSpecial(ctx context.Context, operation string, params interface{}) (*types.AWSResource, error)
ValidateParams(operation string, params interface{}) error
}
```

#### Lifecycle Management

The LifecycleManager handles plugin initialization order based on dependencies:

```go
type LifecycleManager struct {
registry *PluginRegistry
statuses map[string]*PluginStatus
healthTick time.Duration
}
```

**Features:**
- Topological sorting for dependency-aware initialization
- Continuous health monitoring
- Graceful shutdown with error handling
- Hot reload support for development

### Built-in Middleware

| Middleware | Purpose |
|------------|---------|
| `LoggingMiddleware` | Operation logging with duration tracking |
| `RecoveryMiddleware` | Panic recovery with stack traces |
| `MetricsMiddleware` | Performance metrics collection |
| `TimeoutMiddleware` | Configurable operation timeouts |

### Usage Example

```go
registry := plugins.NewPluginRegistry(logger)
lifecycle := plugins.NewLifecycleManager(registry, logger)

// Register plugin with middleware
registry.Register(ec2Handler, &PluginConfig{
AWSClient: awsClient,
Logger: logger,
})

registry.AddMiddleware("ec2-instance", plugins.LoggingMiddleware(logger))
registry.AddMiddleware("ec2-instance", plugins.TimeoutMiddleware(30*time.Second))

// Execute with hooks and middleware
result, err := registry.ExecuteWithHooks(ctx, "ec2-instance", "create", params)
```

## Safety Layer Architecture (v2.0)

### Overview

The Safety Layer provides comprehensive protection mechanisms including simulation mode, validation, and dry-run capabilities. It ensures safe infrastructure operations through multiple validation checkpoints.

### Core Components

#### Simulator

The Simulator enables safe testing of infrastructure operations:

```go
type Simulator struct {
config SimulationConfig
validators map[string]SafetyValidator
rules map[string][]ValidationRule
}
```

**Simulation Modes:**
| Mode | Description |
|------|-------------|
| `SimulationDisabled` | Normal execution without simulation |
| `SimulationDryRun` | Full simulation with no actual changes |
| `SimulationValidate` | Validation only, no resource changes |

**Simulation Results:**
```go
type SimulationResult struct {
Success bool
WouldCreate []*types.AWSResource
WouldModify []*types.AWSResource
WouldDelete []string
ValidationErrors []ValidationError
Warnings []string
EstimatedCost *CostEstimate
}
```

#### Dry-Run Decorator

The decorator pattern wraps operations for safety:

```go
type DryRunDecorator struct {
simulator *Simulator
auditLog *AuditLog
config DryRunConfig
}
```

**Features:**
- Transparent dry-run mode activation
- Pre-execution validation
- Audit trail generation
- Blocked operation enforcement

#### Validation Layer

Multi-level validation for infrastructure operations:

```go
type ValidationLayer struct {
validators map[string]ResourceValidator
rules map[string][]ValidationRule
}
```

**Validation Levels:**
- **Error**: Blocks execution
- **Warning**: Logs but allows execution
- **Info**: Informational only

**Built-in Validators:**
| Validator | Scope |
|-----------|-------|
| `ValidatorRegistry` | Parameter validation with rules |
| `DependencyValidator` | Dependency order verification |
| `QuotaValidator` | Resource quota enforcement |

### Validation Rules

Pre-configured rules for common AWS resources:

```yaml
ec2-instance:
- imageId: required
- instanceType: required, pattern("^[a-z][0-9][a-z]?\\.[a-z0-9]+$")

rds-instance:
- engine: required
- dbInstanceClass: required
- allocatedStorage: min(20)

vpc:
- cidrBlock: required, cidr
```

### Usage Example

```go
simulator := safety.NewSimulator(logger, safety.SimulationConfig{
Mode: safety.SimulationDryRun,
EnableCostEstimate: true,
EnableQuotaCheck: true,
})

decorator := safety.NewDryRunDecorator(logger, simulator, safety.DryRunConfig{
EnabledByDefault: true,
RequireConfirmation: true,
AuditEnabled: true,
})

// Wrap operation with dry-run support
safeOperation := decorator.Decorate(createInstance, &safety.ExecutionContext{
Operation: "create",
ResourceType: "ec2-instance",
DryRun: true,
})

result, err := safeOperation(ctx, params)
```

## Enhanced Reasoning System (v2.0)

### Overview

The reasoning system has been enhanced with multi-step verification protocols, providing structured safety checks at every stage of infrastructure planning.

### Verification Phases

#### Phase 1: Pre-Flight Validation
1. Parse and validate user intent
2. Identify all required AWS resources
3. Check MANAGED RESOURCES section
4. Verify tool availability
5. Assess operation risk level

#### Phase 2: Dependency Resolution
1. Map resource dependencies
2. Identify cross-service dependencies
3. Verify prerequisite resources
4. Detect circular dependencies
5. Generate execution order

#### Phase 3: Safety Validation
1. Validate parameter completeness
2. Check naming conflicts
3. Verify CIDR availability
4. Validate security group rules
5. Check IAM requirements

#### Phase 4: Impact Assessment
1. Identify resources to be created
2. Identify resources to be modified
3. Identify affected resources
4. Estimate cost implications
5. Assess rollback complexity

### Enhanced Output Format

```json
{
"action": "create_infrastructure",
"reasoning": "Explanation with verification approach",
"riskAssessment": {
"level": "medium",
"factors": ["New VPC creation", "Multiple subnets"],
"mitigations": ["Rollback plan included"]
},
"verificationSummary": {
"preFlightChecks": ["VPC exists", "Subnet available"],
"dependencyOrder": ["VPC", "Subnet", "SecurityGroup", "Instance"],
"postFlightChecks": ["Instance running", "Correct subnet"]
},
"executionPlan": [{
"id": "step-create-instance",
"verification": {
"preConditions": ["subnetId exists"],
"postConditions": ["instanceId returned", "state is running"],
"rollbackStrategy": "terminate-instance"
}
}]
}
```

### Rollback Considerations

Each operation includes rollback planning:
- Can this operation be easily undone?
- What resources depend on this resource?
- Is there a rollback path if subsequent steps fail?
- Should this be split into multiple plans?

## Conclusion

The AI Infrastructure Agent represents a sophisticated approach to infrastructure automation, combining the power of Large Language Models with robust engineering practices. The system's layered architecture provides separation of concerns while maintaining flexibility and extensibility.
Expand All @@ -358,4 +643,10 @@ Key architectural strengths include:
- **Performance**: Optimized for concurrent operations and resource efficiency
- **Security**: Multiple security layers with defense-in-depth approach

The v2.0 enhancements add:

- **Plugin Architecture**: Dynamic, middleware-enabled resource handlers
- **Safety Layer**: Comprehensive simulation and validation framework
- **Enhanced Reasoning**: Multi-step verification with rollback planning

The system is designed to scale from proof-of-concept deployments to production environments while maintaining the simplicity of natural language infrastructure management.
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