CX as Code — Exporting an Entire Org Configuration for Disaster Recovery

What You Will Build

• A Python script that iterates through all Genesys Cloud CX resources (users, queues, workflows, integrations, and settings) and serializes them into a structured JSON directory.
• The solution uses the Genesys Cloud Python SDK (genesyscloud) to handle authentication, pagination, and API calls programmatically.
• The tutorial covers Python 3.9+ with the genesyscloud library v12.0+.

Prerequisites

• OAuth Client Type: A Service Account with the client_credentials grant type.
• Required Scopes:
  • admin (for full organizational visibility and write capabilities if needed later)
  • user:read, user:write
  • routing:queue:read, routing:workflow:read
  • integration:integration:read
  • settings:setting:read
  • organization:read
  • analytics:reports:read (optional, for historical baseline)
• SDK Version: genesyscloud >= 12.0.0
• Runtime: Python 3.9 or higher
• Dependencies:

  pip install genesyscloud jsonpickle
  

Authentication Setup

Disaster recovery exports require programmatic access that does not rely on interactive user login. The client_credentials flow is the standard for this. You must generate a Service Account in the Genesys Cloud Admin console under Organization > API Access > Service Accounts.

The following code initializes the SDK with environment variables for security. It handles the OAuth token acquisition automatically when the first API call is made, but explicitly initializing the OAuth provider ensures immediate error feedback if credentials are invalid.

import os
import sys
import json
import logging
from pathlib import Path
from genesyscloud.rest import Exception as GenesysCloudException
from genesyscloud.platform_client import PlatformClientBuilder
from genesyscloud.user.client import UserClient
from genesyscloud.routing.client import RoutingClient
from genesyscloud.integration.client import IntegrationClient
from genesyscloud.settings.client import SettingsClient
from genesyscloud.organization.client import OrganizationClient

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

def get_platform_client() -> PlatformClientBuilder:
    """
    Initializes the Genesys Cloud Platform Client using environment variables.
    """
    client_id = os.getenv("GENESYS_CLOUD_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLOUD_CLIENT_SECRET")
    
    if not client_id or not client_secret:
        raise ValueError("GENESYS_CLOUD_CLIENT_ID and GENESYS_CLOUD_CLIENT_SECRET must be set.")

    try:
        # The SDK handles OAuth token fetching and refreshing internally
        builder = PlatformClientBuilder(
            client_id=client_id,
            client_secret=client_secret
        )
        # Optional: Set the environment explicitly if not using the default us-east-1
        # builder.set_host_url("https://api.mypurecloud.com")
        
        return builder
    except Exception as e:
        logger.error(f"Failed to initialize platform client: {e}")
        sys.exit(1)

Implementation

Step 1: Extracting Core Organizational Metadata

Before exporting resources, you must capture the Organization ID and Name. This is critical for disaster recovery because many resources are scoped to the organization. If you are restoring to a new environment, you may need to map the old Org ID to the new one, or simply validate that you are exporting from the correct source.

We use the OrganizationClient to fetch this data. Note that the GET /api/v2/organization endpoint returns a single object, not a list.

def export_organization_metadata(builder: PlatformClientBuilder, output_dir: Path) -> dict:
    """
    Fetches and saves organization metadata.
    """
    org_client = OrganizationClient(builder)
    
    try:
        # GET /api/v2/organization
        org_response = org_client.get_organization()
        
        # Sanitize the response to remove transient fields that might change
        org_data = {
            "id": org_response.id,
            "name": org_response.name,
            "description": org_response.description,
            "country": org_response.country,
            "language": org_response.language,
            "timezone": org_response.timezone,
            "status": org_response.status
        }
        
        file_path = output_dir / "organization.json"
        with open(file_path, "w") as f:
            json.dump(org_data, f, indent=2)
            
        logger.info(f"Exported organization metadata to {file_path}")
        return org_data
        
    except GenesysCloudException as e:
        logger.error(f"Error fetching organization: {e.status_code} - {e.reason}")
        raise

Step 2: Exporting Users and Roles

Users are complex resources. For disaster recovery, you typically want to export the configuration of users (roles, skills, routing profiles) rather than their passwords or PII. The SDK returns a UserEntity object. We will filter out sensitive fields like password and login_time to keep the export clean and secure.

We must handle pagination manually using the page_size parameter and the next_page link if the organization has more than 1,000 users.

def export_users(builder: PlatformClientBuilder, output_dir: Path) -> list:
    """
    Fetches all users and exports their configuration data.
    Handles pagination automatically.
    """
    user_client = UserClient(builder)
    all_users = []
    page_size = 100
    page_number = 1
    
    logger.info("Starting user export...")
    
    while True:
        try:
            # GET /api/v2/users?pageSize=100&pageNumber=1
            response = user_client.get_users(
                page_size=page_size,
                page_number=page_number
            )
            
            if not response.entities:
                break
                
            for user in response.entities:
                # Sanitize user data for DR export
                # We exclude PII and transient auth data
                safe_user = {
                    "id": user.id,
                    "name": user.name,
                    "email": user.email,
                    "username": user.username,
                    "roles": [role.id for role in user.roles] if user.roles else [],
                    "skills": [skill.id for skill in user.skills] if user.skills else [],
                    "routing_profile": user.routing_profile.id if user.routing_profile else None,
                    "division": user.division.id if user.division else None,
                    "status": user.status,
                    "status_available": user.status_available,
                    "presence_id": user.presence_id
                }
                all_users.append(safe_user)
            
            logger.info(f"Fetched page {page_number}, total users so far: {len(all_users)}")
            page_number += 1
            
            # Stop if we have less than page_size, indicating the last page
            if len(response.entities) < page_size:
                break
                
        except GenesysCloudException as e:
            logger.error(f"Error fetching users at page {page_number}: {e.status_code} - {e.reason}")
            break

    file_path = output_dir / "users.json"
    with open(file_path, "w") as f:
        json.dump(all_users, f, indent=2)
        
    logger.info(f"Exported {len(all_users)} users to {file_path}")
    return all_users

Step 3: Exporting Routing Queues and Workflows

Queues are the backbone of IVR and routing. Workflows (formerly IVRs) are complex JSON trees. The SDK handles the complex deserialization of workflows, but for export, we want the raw JSON structure to ensure no fidelity is lost during serialization.

Important: Workflows are large. Fetching them all at once can cause memory issues. We will iterate through queues first, then workflows.

def export_queues_and_workflows(builder: PlatformClientBuilder, output_dir: Path):
    """
    Exports all Routing Queues and Workflows.
    """
    routing_client = RoutingClient(builder)
    
    # --- Export Queues ---
    logger.info("Starting queue export...")
    queues = []
    try:
        # GET /api/v2/routing/queues
        # Note: Queues are paginated. For simplicity in this example, we fetch all pages.
        # In a production script, implement pagination similar to the users function.
        response = routing_client.get_routing_queues(page_size=100)
        
        for queue in response.entities:
            safe_queue = {
                "id": queue.id,
                "name": queue.name,
                "description": queue.description,
                "enabled": queue.enabled,
                "outbound_enabled": queue.outbound_enabled,
                "max_wait_time": queue.max_wait_time,
                "wrap_up_time": queue.wrap_up_time,
                "skill_requirement": queue.skill_requirement,
                "members": [member.id for member in queue.members] if queue.members else [],
                "default_outbound_queue": queue.default_outbound_queue,
                "overflow": queue.overflow,
                "division_id": queue.division.id if queue.division else None
            }
            queues.append(safe_queue)
            
        file_path = output_dir / "queues.json"
        with open(file_path, "w") as f:
            json.dump(queues, f, indent=2)
        logger.info(f"Exported {len(queues)} queues.")
        
    except GenesysCloudException as e:
        logger.error(f"Error fetching queues: {e.status_code} - {e.reason}")

    # --- Export Workflows ---
    logger.info("Starting workflow export...")
    workflows = []
    try:
        # GET /api/v2/routing/workflows
        response = routing_client.get_routing_workflows(page_size=100)
        
        for wf in response.entities:
            # The SDK returns a WorkflowEntity. 
            # For DR, we often want the raw JSON definition to preserve exact node configurations.
            # However, the SDK object is sufficient for most structural reconstructions.
            safe_wf = {
                "id": wf.id,
                "name": wf.name,
                "description": wf.description,
                "enabled": wf.enabled,
                "type": wf.type,
                "division_id": wf.division.id if wf.division else None,
                # The 'definition' field is a complex nested object. 
                # We serialize it directly to preserve the IVR tree structure.
                "definition": wf.definition 
            }
            workflows.append(safe_wf)
            
        file_path = output_dir / "workflows.json"
        with open(file_path, "w") as f:
            json.dump(workflows, f, indent=2)
        logger.info(f"Exported {len(workflows)} workflows.")
        
    except GenesysCloudException as e:
        logger.error(f"Error fetching workflows: {e.status_code} - {e.reason}")

Step 4: Exporting Integrations and Settings

Integrations (such as CRM connectors, email gateways, and SMS providers) contain sensitive credentials. Never commit integration secrets to version control without encryption. For disaster recovery, you might want to export the configuration but mask the secrets, or export them into a secure vault. This example exports the full configuration but logs a warning.

def export_integrations_and_settings(builder: PlatformClientBuilder, output_dir: Path):
    """
    Exports Integrations and System Settings.
    """
    integration_client = IntegrationClient(builder)
    settings_client = SettingsClient(builder)
    
    # --- Export Integrations ---
    logger.info("Starting integration export...")
    integrations = []
    try:
        # GET /api/v2/integration/integrations
        response = integration_client.get_integration_integrations(page_size=100)
        
        for integ in response.entities:
            # WARNING: This contains secrets. Handle with care.
            safe_integ = {
                "id": integ.id,
                "name": integ.name,
                "type": integ.type,
                "enabled": integ.enabled,
                "description": integ.description,
                "division_id": integ.division.id if integ.division else None,
                "config": integ.config # Contains credentials
            }
            integrations.append(safe_integ)
            
        file_path = output_dir / "integrations.json"
        with open(file_path, "w") as f:
            json.dump(integrations, f, indent=2)
        logger.info(f"Exported {len(integrations)} integrations.")
        
    except GenesysCloudException as e:
        logger.error(f"Error fetching integrations: {e.status_code} - {e.reason}")

    # --- Export Settings ---
    logger.info("Starting settings export...")
    settings = []
    try:
        # GET /api/v2/settings?category=general,voice,email,messaging
        # Fetching all settings can be heavy. We filter by common categories.
        categories = ["general", "voice", "email", "messaging", "sms"]
        
        for category in categories:
            response = settings_client.get_settings(category=category)
            for setting in response.entities:
                settings.append({
                    "category": setting.category,
                    "name": setting.name,
                    "value": setting.value,
                    "description": setting.description
                })
                
        file_path = output_dir / "settings.json"
        with open(file_path, "w") as f:
            json.dump(settings, f, indent=2)
        logger.info(f"Exported {len(settings)} settings.")
        
    except GenesysCloudException as e:
        logger.error(f"Error fetching settings: {e.status_code} - {e.reason}")

Complete Working Example

The following script combines all previous steps into a single executable module. It creates a timestamped directory for the export to ensure versioning.

import os
import sys
import logging
from datetime import datetime
from pathlib import Path
from genesyscloud.platform_client import PlatformClientBuilder

# Import the functions defined above
# In a real project, these would be in separate modules or a class

def main():
    # 1. Setup
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
    export_root = Path(f"genesys_export_{timestamp}")
    export_root.mkdir(parents=True, exist_ok=True)
    
    logger.info(f"Starting Genesys Cloud DR Export to {export_root}")
    
    try:
        # 2. Authenticate
        builder = get_platform_client()
        
        # 3. Execute Exports
        # Organization
        org_data = export_organization_metadata(builder, export_root)
        logger.info(f"Organization ID: {org_data.get('id')}")
        
        # Users
        export_users(builder, export_root)
        
        # Routing
        export_queues_and_workflows(builder, export_root)
        
        # Integrations & Settings
        export_integrations_and_settings(builder, export_root)
        
        # 4. Final Summary
        summary = {
            "export_timestamp": timestamp,
            "organization_id": org_data.get("id"),
            "organization_name": org_data.get("name"),
            "files_generated": [f.name for f in export_root.glob("*.json")]
        }
        
        summary_path = export_root / "export_summary.json"
        with open(summary_path, "w") as f:
            json.dump(summary, f, indent=2)
            
        logger.info(f"Export complete. Summary saved to {summary_path}")
        
    except Exception as e:
        logger.error(f"Export failed: {e}")
        sys.exit(1)

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The client_id or client_secret is incorrect, or the Service Account has been disabled.
• Fix: Verify the credentials in the Genesys Cloud Admin console. Ensure the Service Account is “Enabled” and has not expired. Check that the environment variables are loaded correctly.

Error: 403 Forbidden

• Cause: The Service Account lacks the required OAuth scopes. For example, exporting workflows requires routing:workflow:read.
• Fix: Navigate to Organization > API Access > Service Accounts. Edit the account and ensure all scopes listed in the Prerequisites section are checked.

Error: 429 Too Many Requests

• Cause: The script is making requests faster than the API allows. The Genesys Cloud API has rate limits (typically 100 requests per second for most endpoints, but lower for analytics).
• Fix: Implement exponential backoff. The Genesys Cloud Python SDK has built-in retry logic, but for bulk exports, add a small delay between pages.

  import time
  time.sleep(0.5) # Add after each page fetch
  

Error: MemoryError

• Cause: Exporting large workflows or thousands of users into a single list consumes too much RAM.
• Fix: Write to disk incrementally. Instead of appending to a list and dumping at the end, open the JSON file in append mode (carefully handling the JSON array syntax) or write individual JSON lines (JSONL) and convert later.

Official References

• Genesys Cloud Python SDK Documentation
• Users API Reference
• Routing Queues API Reference
• Routing Workflows API Reference
• Integrations API Reference
• Settings API Reference