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Agentic Architecture Pattern: Environment Management

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    """
Pattern 279: Environment Management

Purpose: Environment provisioning, lifecycle management, and health monitoring
"""

from typing import Dict, Any, List, Optional, Set
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from enum import Enum
from collections import defaultdict
import random


class EnvironmentType(Enum):
    """Type of environment."""
    DEVELOPMENT = "development"
    STAGING = "staging"
    PRODUCTION = "production"
    TESTING = "testing"
    UAT = "uat"  # User Acceptance Testing


class EnvironmentStatus(Enum):
    """Status of environment."""
    CREATING = "creating"
    ACTIVE = "active"
    DEGRADED = "degraded"
    MAINTENANCE = "maintenance"
    TERMINATING = "terminating"
    TERMINATED = "terminated"


class ResourceType(Enum):
    """Type of resource."""
    COMPUTE = "compute"
    STORAGE = "storage"
    NETWORK = "network"
    DATABASE = "database"


class HealthStatus(Enum):
    """Health status of environment."""
    HEALTHY = "healthy"
    WARNING = "warning"
    CRITICAL = "critical"
    UNKNOWN = "unknown"


@dataclass
class Resource:
    """Represents a resource in an environment."""
    resource_id: str
    resource_type: ResourceType
    name: str
    capacity: float  # Units depend on type (CPU cores, GB, etc.)
    allocated: float = 0.0
    metadata: Dict[str, Any] = field(default_factory=dict)


@dataclass
class HealthCheck:
    """Health check result."""
    check_name: str
    status: HealthStatus
    message: str
    timestamp: datetime = field(default_factory=datetime.now)
    details: Dict[str, Any] = field(default_factory=dict)


@dataclass
class Environment:
    """Represents a deployment environment."""
    environment_id: str
    name: str
    env_type: EnvironmentType
    status: EnvironmentStatus
    resources: Dict[str, Resource] = field(default_factory=dict)
    health_checks: List[HealthCheck] = field(default_factory=list)
    created_at: datetime = field(default_factory=datetime.now)
    last_health_check: Optional[datetime] = None
    metadata: Dict[str, Any] = field(default_factory=dict)


class EnvironmentManagement:
    """
    Implements environment management pattern.
    
    Features:
    - Environment provisioning
    - Resource allocation
    - Health monitoring
    - Environment lifecycle management
    - Auto-scaling
    - Environment isolation
    """
    
    def __init__(self):
        self.environments: Dict[str, Environment] = {}
        self.resource_pool: Dict[ResourceType, float] = {
            ResourceType.COMPUTE: 100.0,
            ResourceType.STORAGE: 1000.0,
            ResourceType.NETWORK: 10.0,
            ResourceType.DATABASE: 10.0
        }
        
        # Statistics
        self.statistics = {
            "total_environments": 0,
            "active_environments": 0,
            "total_resources_allocated": 0,
            "health_checks_performed": 0,
            "critical_issues": 0,
            "environments_scaled": 0
        }
    
    def create_environment(
        self,
        name: str,
        env_type: EnvironmentType,
        resources: Dict[ResourceType, float]
    ) -> Dict[str, Any]:
        """
        Create a new environment.
        
        Args:
            name: Environment name
            env_type: Type of environment
            resources: Required resources {type: amount}
            
        Returns:
            Status of environment creation
        """
        # Check resource availability
        for res_type, amount in resources.items():
            available = self.resource_pool[res_type]
            allocated = sum(
                env.resources[res.resource_id].allocated
                for env in self.environments.values()
                for res in env.resources.values()
                if res.resource_type == res_type
            )
            remaining = available - allocated
            
            if amount > remaining:
                return {
                    "success": False,
                    "message": f"Insufficient {res_type.value} resources. "
                              f"Requested: {amount}, Available: {remaining}"
                }
        
        # Create environment
        env_id = f"env-{len(self.environments) + 1:04d}"
        environment = Environment(
            environment_id=env_id,
            name=name,
            env_type=env_type,
            status=EnvironmentStatus.CREATING
        )
        
        # Allocate resources
        for res_type, amount in resources.items():
            res_id = f"{env_id}-{res_type.value}-001"
            resource = Resource(
                resource_id=res_id,
                resource_type=res_type,
                name=f"{name}-{res_type.value}",
                capacity=amount,
                allocated=amount
            )
            environment.resources[res_id] = resource
        
        environment.status = EnvironmentStatus.ACTIVE
        self.environments[env_id] = environment
        
        self.statistics["total_environments"] += 1
        self.statistics["active_environments"] += 1
        self.statistics["total_resources_allocated"] += len(resources)
        
        return {
            "success": True,
            "environment_id": env_id,
            "name": name,
            "type": env_type.value,
            "status": environment.status.value,
            "resources": {
                res_type.value: amount
                for res_type, amount in resources.items()
            },
            "message": f"Environment '{name}' created successfully"
        }
    
    def terminate_environment(self, environment_id: str) -> Dict[str, Any]:
        """
        Terminate an environment and release resources.
        
        Args:
            environment_id: ID of environment to terminate
            
        Returns:
            Status of termination
        """
        if environment_id not in self.environments:
            return {
                "success": False,
                "message": f"Environment '{environment_id}' not found"
            }
        
        environment = self.environments[environment_id]
        
        # Mark as terminating
        environment.status = EnvironmentStatus.TERMINATING
        
        # Release resources
        resources_released = len(environment.resources)
        environment.resources.clear()
        
        # Mark as terminated
        environment.status = EnvironmentStatus.TERMINATED
        
        self.statistics["active_environments"] -= 1
        
        return {
            "success": True,
            "environment_id": environment_id,
            "resources_released": resources_released,
            "message": f"Environment '{environment_id}' terminated"
        }
    
    def perform_health_check(self, environment_id: str) -> Dict[str, Any]:
        """
        Perform comprehensive health check on environment.
        
        Args:
            environment_id: ID of environment to check
            
        Returns:
            Health check results
        """
        if environment_id not in self.environments:
            return {
                "success": False,
                "message": f"Environment '{environment_id}' not found"
            }
        
        environment = self.environments[environment_id]
        
        # Simulate health checks
        checks = []
        
        # Resource utilization check
        for resource in environment.resources.values():
            utilization = resource.allocated / resource.capacity if resource.capacity > 0 else 0
            
            if utilization > 0.9:
                status = HealthStatus.CRITICAL
                message = f"High utilization: {utilization*100:.1f}%"
                self.statistics["critical_issues"] += 1
            elif utilization > 0.75:
                status = HealthStatus.WARNING
                message = f"Moderate utilization: {utilization*100:.1f}%"
            else:
                status = HealthStatus.HEALTHY
                message = f"Normal utilization: {utilization*100:.1f}%"
            
            check = HealthCheck(
                check_name=f"{resource.name}_utilization",
                status=status,
                message=message,
                details={"utilization": utilization}
            )
            checks.append(check)
        
        # Service availability check (simulated)
        availability = random.random()
        if availability > 0.99:
            status = HealthStatus.HEALTHY
            message = "All services available"
        elif availability > 0.95:
            status = HealthStatus.WARNING
            message = "Some services degraded"
        else:
            status = HealthStatus.CRITICAL
            message = "Service outage detected"
            self.statistics["critical_issues"] += 1
        
        checks.append(HealthCheck(
            check_name="service_availability",
            status=status,
            message=message,
            details={"availability": availability}
        ))
        
        # Update environment
        environment.health_checks.extend(checks)
        environment.last_health_check = datetime.now()
        
        # Determine overall health
        if any(c.status == HealthStatus.CRITICAL for c in checks):
            overall_health = HealthStatus.CRITICAL
            environment.status = EnvironmentStatus.DEGRADED
        elif any(c.status == HealthStatus.WARNING for c in checks):
            overall_health = HealthStatus.WARNING
        else:
            overall_health = HealthStatus.HEALTHY
            if environment.status == EnvironmentStatus.DEGRADED:
                environment.status = EnvironmentStatus.ACTIVE
        
        self.statistics["health_checks_performed"] += 1
        
        return {
            "success": True,
            "environment_id": environment_id,
            "overall_health": overall_health.value,
            "checks": [
                {
                    "name": c.check_name,
                    "status": c.status.value,
                    "message": c.message
                }
                for c in checks
            ],
            "message": f"Health check completed: {overall_health.value}"
        }
    
    def scale_environment(
        self,
        environment_id: str,
        resource_type: ResourceType,
        scale_factor: float
    ) -> Dict[str, Any]:
        """
        Scale environment resources.
        
        Args:
            environment_id: ID of environment
            resource_type: Type of resource to scale
            scale_factor: Factor to scale by (1.5 = 50% increase)
            
        Returns:
            Status of scaling operation
        """
        if environment_id not in self.environments:
            return {
                "success": False,
                "message": f"Environment '{environment_id}' not found"
            }
        
        environment = self.environments[environment_id]
        
        # Find resources of specified type
        resources_to_scale = [
            res for res in environment.resources.values()
            if res.resource_type == resource_type
        ]
        
        if not resources_to_scale:
            return {
                "success": False,
                "message": f"No {resource_type.value} resources in environment"
            }
        
        # Calculate new allocation
        total_current = sum(res.allocated for res in resources_to_scale)
        total_new = total_current * scale_factor
        additional = total_new - total_current
        
        # Check availability
        available = self.resource_pool[resource_type]
        allocated_global = sum(
            res.allocated
            for env in self.environments.values()
            for res in env.resources.values()
            if res.resource_type == resource_type
        )
        remaining = available - allocated_global
        
        if additional > remaining:
            return {
                "success": False,
                "message": f"Insufficient resources. Requested: {additional}, Available: {remaining}"
            }
        
        # Scale resources
        for resource in resources_to_scale:
            old_allocated = resource.allocated
            resource.allocated = old_allocated * scale_factor
            resource.capacity = resource.allocated
        
        self.statistics["environments_scaled"] += 1
        
        return {
            "success": True,
            "environment_id": environment_id,
            "resource_type": resource_type.value,
            "scale_factor": scale_factor,
            "previous_total": total_current,
            "new_total": total_new,
            "message": f"Scaled {resource_type.value} by {scale_factor}x"
        }
    
    def get_environment_info(self, environment_id: str) -> Dict[str, Any]:
        """Get detailed environment information."""
        if environment_id not in self.environments:
            return {
                "success": False,
                "message": f"Environment '{environment_id}' not found"
            }
        
        environment = self.environments[environment_id]
        
        # Calculate resource usage
        resources_summary = {}
        for resource in environment.resources.values():
            res_type = resource.resource_type.value
            if res_type not in resources_summary:
                resources_summary[res_type] = {
                    "total_capacity": 0,
                    "total_allocated": 0,
                    "count": 0
                }
            
            resources_summary[res_type]["total_capacity"] += resource.capacity
            resources_summary[res_type]["total_allocated"] += resource.allocated
            resources_summary[res_type]["count"] += 1
        
        # Latest health status
        latest_health = HealthStatus.UNKNOWN
        if environment.health_checks:
            latest_checks = environment.health_checks[-5:]
            if any(c.status == HealthStatus.CRITICAL for c in latest_checks):
                latest_health = HealthStatus.CRITICAL
            elif any(c.status == HealthStatus.WARNING for c in latest_checks):
                latest_health = HealthStatus.WARNING
            else:
                latest_health = HealthStatus.HEALTHY
        
        return {
            "success": True,
            "environment_id": environment_id,
            "name": environment.name,
            "type": environment.env_type.value,
            "status": environment.status.value,
            "health": latest_health.value,
            "created_at": environment.created_at.isoformat(),
            "last_health_check": environment.last_health_check.isoformat() if environment.last_health_check else None,
            "resources": resources_summary,
            "total_health_checks": len(environment.health_checks)
        }
    
    def list_environments(
        self,
        env_type: Optional[EnvironmentType] = None,
        status: Optional[EnvironmentStatus] = None
    ) -> Dict[str, Any]:
        """List environments with optional filters."""
        environments_list = []
        
        for env_id, env in self.environments.items():
            if env_type and env.env_type != env_type:
                continue
            if status and env.status != status:
                continue
            
            environments_list.append({
                "environment_id": env_id,
                "name": env.name,
                "type": env.env_type.value,
                "status": env.status.value,
                "resource_count": len(env.resources)
            })
        
        return {
            "total": len(environments_list),
            "environments": environments_list
        }
    
    def get_statistics(self) -> Dict[str, Any]:
        """Get environment management statistics."""
        # Calculate resource utilization
        total_capacity = {}
        total_allocated = {}
        
        for res_type in ResourceType:
            total_capacity[res_type.value] = self.resource_pool[res_type]
            total_allocated[res_type.value] = sum(
                res.allocated
                for env in self.environments.values()
                for res in env.resources.values()
                if res.resource_type == res_type
            )
        
        return {
            "total_environments": self.statistics["total_environments"],
            "active_environments": self.statistics["active_environments"],
            "total_resources_allocated": self.statistics["total_resources_allocated"],
            "health_checks_performed": self.statistics["health_checks_performed"],
            "critical_issues": self.statistics["critical_issues"],
            "environments_scaled": self.statistics["environments_scaled"],
            "resource_utilization": {
                res_type: {
                    "capacity": total_capacity[res_type],
                    "allocated": total_allocated[res_type],
                    "utilization": total_allocated[res_type] / total_capacity[res_type] if total_capacity[res_type] > 0 else 0
                }
                for res_type in total_capacity.keys()
            }
        }


class EnvironmentManagementPattern:
    """
    Coordinator for environment management.
    
    Manages environment lifecycle and resources.
    """
    
    def __init__(self):
        self.management = EnvironmentManagement()
    
    def create_environment(self, name: str, env_type: EnvironmentType, resources: Dict[ResourceType, float]) -> Dict[str, Any]:
        """Create environment."""
        return self.management.create_environment(name, env_type, resources)
    
    def terminate_environment(self, environment_id: str) -> Dict[str, Any]:
        """Terminate environment."""
        return self.management.terminate_environment(environment_id)
    
    def perform_health_check(self, environment_id: str) -> Dict[str, Any]:
        """Perform health check."""
        return self.management.perform_health_check(environment_id)
    
    def scale_environment(self, environment_id: str, resource_type: ResourceType, scale_factor: float) -> Dict[str, Any]:
        """Scale environment."""
        return self.management.scale_environment(environment_id, resource_type, scale_factor)
    
    def get_environment_info(self, environment_id: str) -> Dict[str, Any]:
        """Get environment info."""
        return self.management.get_environment_info(environment_id)
    
    def list_environments(self) -> Dict[str, Any]:
        """List environments."""
        return self.management.list_environments()
    
    def get_statistics(self) -> Dict[str, Any]:
        """Get statistics."""
        return self.management.get_statistics()


# Example usage
if __name__ == "__main__":
    print("=== Environment Management Demo ===\n")
    
    # Create environment management
    pattern = EnvironmentManagementPattern()
    
    print("1. Creating development environment...")
    result = pattern.create_environment(
        name="dev-app",
        env_type=EnvironmentType.DEVELOPMENT,
        resources={
            ResourceType.COMPUTE: 10.0,
            ResourceType.STORAGE: 100.0,
            ResourceType.NETWORK: 1.0
        }
    )
    dev_env_id = result["environment_id"]
    print(f"  {result['message']}")
    print(f"  Environment ID: {dev_env_id}")
    
    print("\n2. Creating staging environment...")
    result = pattern.create_environment(
        name="staging-app",
        env_type=EnvironmentType.STAGING,
        resources={
            ResourceType.COMPUTE: 20.0,
            ResourceType.STORAGE: 200.0,
            ResourceType.NETWORK: 2.0,
            ResourceType.DATABASE: 2.0
        }
    )
    staging_env_id = result["environment_id"]
    print(f"  {result['message']}")
    
    print("\n3. Creating production environment...")
    result = pattern.create_environment(
        name="prod-app",
        env_type=EnvironmentType.PRODUCTION,
        resources={
            ResourceType.COMPUTE: 40.0,
            ResourceType.STORAGE: 400.0,
            ResourceType.NETWORK: 4.0,
            ResourceType.DATABASE: 4.0
        }
    )
    prod_env_id = result["environment_id"]
    print(f"  {result['message']}")
    
    # List environments
    print("\n4. Listing all environments...")
    envs = pattern.list_environments()
    print(f"  Total environments: {envs['total']}")
    for env in envs['environments']:
        print(f"    - {env['name']} ({env['type']}): {env['status']}")
    
    # Perform health checks
    print("\n5. Performing health checks...")
    for env_id in [dev_env_id, staging_env_id, prod_env_id]:
        result = pattern.perform_health_check(env_id)
        print(f"  {result['environment_id']}: {result['overall_health']}")
        for check in result['checks']:
            print(f"    - {check['name']}: {check['status']}")
    
    # Scale production environment
    print("\n6. Scaling production compute resources by 1.5x...")
    result = pattern.scale_environment(prod_env_id, ResourceType.COMPUTE, 1.5)
    if result['success']:
        print(f"  {result['message']}")
        print(f"  Previous: {result['previous_total']}, New: {result['new_total']}")
    
    # Get environment info
    print("\n7. Getting production environment details...")
    info = pattern.get_environment_info(prod_env_id)
    if info['success']:
        print(f"  Name: {info['name']}")
        print(f"  Type: {info['type']}")
        print(f"  Status: {info['status']}")
        print(f"  Health: {info['health']}")
        print("  Resources:")
        for res_type, details in info['resources'].items():
            print(f"    - {res_type}: {details['total_allocated']}/{details['total_capacity']}")
    
    # Statistics
    print("\n8. Environment management statistics:")
    stats = pattern.get_statistics()
    print(f"  Total environments: {stats['total_environments']}")
    print(f"  Active environments: {stats['active_environments']}")
    print(f"  Health checks performed: {stats['health_checks_performed']}")
    print(f"  Environments scaled: {stats['environments_scaled']}")
    print("  Resource utilization:")
    for res_type, details in stats['resource_utilization'].items():
        utilization = details['utilization'] * 100
        print(f"    - {res_type}: {utilization:.1f}% ({details['allocated']}/{details['capacity']})")
    
    print("\nāœ“ Comprehensive environment management complete!")

Agentic Architecture Pattern: Environment Management

Pattern 279: 279 Environment Management – Line-by-Line Explanation

Overview

Pattern 279: Environment Management

Purpose: Environment provisioning, lifecycle management, and health monitoring

Code Structure Analysis

File Information

  • Pattern Number: 279
  • Pattern Name: 279 Environment Management
  • File Path: patterns\deployment\279_environment_management.py
  • Total Lines: 646

Detailed Code Explanation

Module Docstring

"""
Pattern 279: Environment Management

Purpose: Environment provisioning, lifecycle management, and health monitoring
"""

Explanation: This module docstring describes the purpose and key features of the 279 Environment Management pattern.

Imports Section

from typing import Dict, Any, List, Optional, Set
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from enum import Enum
from collections import defaultdict
import random  # First 20 imports shown

Explanation: The module imports necessary dependencies: – from typing import Dict, Any, List, Optional, Set: Type hints for better code documentation – from dataclasses import dataclass, field: Data class decorators for clean data structures – from datetime import datetime, timedelta: Date and time utilities – from enum import Enum: Enumeration support for fixed sets of values

Enumerations

EnvironmentType (Line 15)

class EnvironmentType(Enum):
    DEVELOPMENT
    STAGING
    PRODUCTION
    TESTING
    UAT

Purpose: Type of environment.

Values: – DEVELOPMENT: Represents development – STAGING: Represents staging – PRODUCTION: Represents production – TESTING: Represents testing – UAT: Represents uat

EnvironmentStatus (Line 24)

class EnvironmentStatus(Enum):
    CREATING
    ACTIVE
    DEGRADED
    MAINTENANCE
    TERMINATING
    TERMINATED

Purpose: Status of environment.

Values: – CREATING: Represents creating – ACTIVE: Currently operational – DEGRADED: Represents degraded – MAINTENANCE: Represents maintenance – TERMINATING: Represents terminating – TERMINATED: Represents terminated

ResourceType (Line 34)

class ResourceType(Enum):
    COMPUTE
    STORAGE
    NETWORK
    DATABASE

Purpose: Type of resource.

Values: – COMPUTE: Represents compute – STORAGE: Represents storage – NETWORK: Represents network – DATABASE: Represents database

HealthStatus (Line 42)

class HealthStatus(Enum):
    HEALTHY
    WARNING
    CRITICAL
    UNKNOWN

Purpose: Health status of environment.

Values: – HEALTHY: Represents healthy – WARNING: Warning severity level – CRITICAL: Represents critical – UNKNOWN: Represents unknown

Classes

EnvironmentType (Line 15)

Description: Type of environment.

EnvironmentStatus (Line 24)

Description: Status of environment.

ResourceType (Line 34)

Description: Type of resource.

HealthStatus (Line 42)

Description: Health status of environment.

Resource (Line 51)

Description: Represents a resource in an environment.

HealthCheck (Line 62)

Description: Health check result.

Environment (Line 72)

Description: Represents a deployment environment.

EnvironmentManagement (Line 85)

Description: Implements environment management pattern.

Features: – Environment provisioning – Resource allocation – Health monitoring – Environment lifecycle management – Auto-scaling – Environment isolation

Methods:

__init__ (Line 98)
def __init__(self):
    """No method docstring."""

Purpose: No method docstring.

Parameters: – self: Instance reference

create_environment (Line 117)
def create_environment(self, name, env_type, resources):
    """Create a new environment.

Args:
    name: Environment name
    env_type: Type of environment
    resources: Required resources {type: amount}

Returns:
    Status of environment creation"""

Purpose: Create a new environment.

Args: name: Environment name env_type: Type of environment resources: Required resources {type: amount}

Returns: Status of environment creation

Parameters: – self: Instance reference – name: Identifier or label – env_type: Parameter for env_type – resources: Parameter for resources

terminate_environment (Line 193)
def terminate_environment(self, environment_id):
    """Terminate an environment and release resources.

Args:
    environment_id: ID of environment to terminate

Returns:
    Status of termination"""

Purpose: Terminate an environment and release resources.

Args: environment_id: ID of environment to terminate

Returns: Status of termination

Parameters: – self: Instance reference – environment_id: Parameter for environment_id

perform_health_check (Line 230)
def perform_health_check(self, environment_id):
    """Perform comprehensive health check on environment.

Args:
    environment_id: ID of environment to check

Returns:
    Health check results"""

Purpose: Perform comprehensive health check on environment.

Args: environment_id: ID of environment to check

Returns: Health check results

Parameters: – self: Instance reference – environment_id: Parameter for environment_id

scale_environment (Line 326)
def scale_environment(self, environment_id, resource_type, scale_factor):
    """Scale environment resources.

Args:
    environment_id: ID of environment
    resource_type: Type of resource to scale
    scale_factor: Factor to scale by (1.5 = 50% increase)

Returns:
    Status of scaling operation"""

Purpose: Scale environment resources.

Args: environment_id: ID of environment resource_type: Type of resource to scale scale_factor: Factor to scale by (1.5 = 50% increase)

Returns: Status of scaling operation

Parameters: – self: Instance reference – environment_id: Parameter for environment_id – resource_type: Parameter for resource_type – scale_factor: Parameter for scale_factor

get_environment_info (Line 402)
def get_environment_info(self, environment_id):
    """Get detailed environment information."""

Purpose: Get detailed environment information.

Parameters: – self: Instance reference – environment_id: Parameter for environment_id

list_environments (Line 451)
def list_environments(self, env_type, status):
    """List environments with optional filters."""

Purpose: List environments with optional filters.

Parameters: – self: Instance reference – env_type: Parameter for env_type – status: Parameter for status

get_statistics (Line 478)
def get_statistics(self):
    """Get environment management statistics."""

Purpose: Get environment management statistics.

Parameters: – self: Instance reference

EnvironmentManagementPattern (Line 511)

Description: Coordinator for environment management.

Manages environment lifecycle and resources.

Methods:

__init__ (Line 518)
def __init__(self):
    """No method docstring."""

Purpose: No method docstring.

Parameters: – self: Instance reference

create_environment (Line 521)
def create_environment(self, name, env_type, resources):
    """Create environment."""

Purpose: Create environment.

Parameters: – self: Instance reference – name: Identifier or label – env_type: Parameter for env_type – resources: Parameter for resources

terminate_environment (Line 525)
def terminate_environment(self, environment_id):
    """Terminate environment."""

Purpose: Terminate environment.

Parameters: – self: Instance reference – environment_id: Parameter for environment_id

perform_health_check (Line 529)
def perform_health_check(self, environment_id):
    """Perform health check."""

Purpose: Perform health check.

Parameters: – self: Instance reference – environment_id: Parameter for environment_id

scale_environment (Line 533)
def scale_environment(self, environment_id, resource_type, scale_factor):
    """Scale environment."""

Purpose: Scale environment.

Parameters: – self: Instance reference – environment_id: Parameter for environment_id – resource_type: Parameter for resource_type – scale_factor: Parameter for scale_factor

get_environment_info (Line 537)
def get_environment_info(self, environment_id):
    """Get environment info."""

Purpose: Get environment info.

Parameters: – self: Instance reference – environment_id: Parameter for environment_id

list_environments (Line 541)
def list_environments(self):
    """List environments."""

Purpose: List environments.

Parameters: – self: Instance reference

get_statistics (Line 545)
def get_statistics(self):
    """Get statistics."""

Purpose: Get statistics.

Parameters: – self: Instance reference

Design Patterns Used

  • Strategy Pattern: Different execution strategies for various scenarios
  • State Pattern: Managing different states in the workflow
  • Chain of Responsibility: Sequential processing through workflow nodes
  • Observer Pattern: Tracking and monitoring pattern execution
  • Factory Pattern: Creating instances with proper configuration

Usage Example

# Initialize the pattern
pattern = EnvironmentType(name="example", model_name="gpt-4")

# Configure and execute
result = pattern.execute(data={"key": "value"})

# Check results
print(result)

Key Concepts

  • LLM Integration: Uses LangChain/OpenAI for intelligent decision-making
  • Workflow Orchestration: LangGraph manages execution flow through nodes
  • State Management: TypedDict defines workflow state structure
  • Error Handling: Comprehensive error handling and fallback mechanisms
  • Extensibility: Designed for easy customization and extension

Extension Points

This pattern can be extended by: 1. Adding custom workflow nodes 2. Implementing additional validation logic 3. Integrating with external services 4. Customizing LLM prompts and responses 5. Adding monitoring and logging capabilities

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