Get Real-Time Queue Observation Data via the Statistics API

What You Will Build

• One sentence: The code queries the Genesys Cloud Statistics API to retrieve live metrics for specific routing queues, including waiting call counts and available agent headcounts.
• One sentence: This tutorial uses the Genesys Cloud CX Statistics API (/api/v2/analytics/queues/currentmetrics/query).
• One sentence: The programming languages covered are Python (using requests) and JavaScript (using axios).

Prerequisites

• OAuth Client Type: Machine-to-Machine (M2M) OAuth 2.0 client.
• Required Scopes: analytics:report:read is required to access current metrics.
• SDK/API Version: Genesys Cloud API v2.
• Language/Runtime Requirements:
  • Python 3.8+ with requests and python-dotenv.
  • Node.js 16+ with axios and dotenv.
• External Dependencies:
  • pip install requests python-dotenv
  • npm install axios dotenv

Authentication Setup

Genesys Cloud uses OAuth 2.0 for authentication. For server-side integrations like real-time monitoring, the Client Credentials grant type is standard. You must exchange your client ID and client secret for an access token. The token expires after one hour, so production code should cache the token and refresh it before expiration.

Python Authentication

import requests
import os
from typing import Optional

class GenesysAuth:
    def __init__(self, environment: str, client_id: str, client_secret: str):
        self.client_id = client_id
        self.client_secret = client_secret
        # Determine the base URL based on environment (us, eu, au, etc.)
        if environment == 'us':
            self.base_url = 'https://api.mypurecloud.com'
        elif environment == 'eu':
            self.base_url = 'https://api.eu.mypurecloud.com'
        else:
            raise ValueError("Unsupported environment")
            
        self.token_url = f'{self.base_url}/oauth/token'
        self.access_token: Optional[str] = None

    def get_access_token(self) -> str:
        """
        Retrieves a fresh OAuth 2.0 access token using Client Credentials flow.
        """
        if self.access_token:
            return self.access_token

        payload = {
            'grant_type': 'client_credentials',
            'client_id': self.client_id,
            'client_secret': self.client_secret
        }

        try:
            response = requests.post(self.token_url, data=payload)
            response.raise_for_status()
            data = response.json()
            self.access_token = data['access_token']
            return self.access_token
        except requests.exceptions.HTTPError as e:
            print(f"Authentication failed: {e.response.status_code} - {e.response.text}")
            raise
        except requests.exceptions.RequestException as e:
            print(f"Network error during authentication: {e}")
            raise

# Usage
# auth = GenesysAuth('us', os.getenv('GENESYS_CLIENT_ID'), os.getenv('GENESYS_CLIENT_SECRET'))
# token = auth.get_access_token()

JavaScript Authentication

const axios = require('axios');

class GenesysAuth {
    constructor(environment, clientId, clientSecret) {
        this.clientId = clientId;
        this.clientSecret = clientSecret;
        
        if (environment === 'us') {
            this.baseUrl = 'https://api.mypurecloud.com';
        } else if (environment === 'eu') {
            this.baseUrl = 'https://api.eu.mypurecloud.com';
        } else {
            throw new Error('Unsupported environment');
        }

        this.tokenUrl = `${this.baseUrl}/oauth/token`;
        this.accessToken = null;
    }

    async getAccessToken() {
        if (this.accessToken) {
            return this.accessToken;
        }

        const payload = new URLSearchParams({
            grant_type: 'client_credentials',
            client_id: this.clientId,
            client_secret: this.clientSecret
        });

        try {
            const response = await axios.post(this.tokenUrl, payload, {
                headers: {
                    'Content-Type': 'application/x-www-form-urlencoded'
                }
            });

            this.accessToken = response.data.access_token;
            return this.accessToken;
        } catch (error) {
            if (error.response) {
                console.error(`Authentication failed: ${error.response.status} - ${error.response.data}`);
            } else {
                console.error(`Network error during authentication: ${error.message}`);
            }
            throw error;
        }
    }
}

// Usage
// const auth = new GenesysAuth('us', process.env.GENESYS_CLIENT_ID, process.env.GENESYS_CLIENT_SECRET);
// const token = await auth.getAccessToken();

Implementation

Step 1: Construct the Current Metrics Query

The endpoint /api/v2/analytics/queues/currentmetrics/query accepts a JSON body that defines which queues to query and what metrics to return. Unlike historical reports, “current metrics” are snapshots of the system state at the moment of the request.

Key parameters in the request body:

• view: Must be set to "QueueCurrentMetricsView" to specify that we want queue-level data.
• entities: An array of queue IDs. If omitted, the API returns metrics for all queues in the organization. For performance, always specify specific IDs if you only need a subset.
• metrics: An array of metric names. Common metrics for real-time observation include:
  • abandonedCalls: Number of calls abandoned in the queue.
  • availableAgents: Number of agents currently available to take work.
  • waitingCalls: Number of calls currently waiting in the queue.
  • inProgressCalls: Number of calls currently being handled by agents.

Python Implementation

import json
import requests
from typing import List, Dict, Any

class QueueMetricsClient:
    def __init__(self, base_url: str, access_token: str):
        self.base_url = base_url
        self.access_token = access_token
        self.metrics_endpoint = f'{base_url}/api/v2/analytics/queues/currentmetrics/query'
        self.headers = {
            'Authorization': f'Bearer {access_token}',
            'Content-Type': 'application/json'
        }

    def get_queue_metrics(self, queue_ids: List[str], metrics: List[str]) -> Dict[str, Any]:
        """
        Queries real-time metrics for specific queues.
        
        Args:
            queue_ids: List of Genesys Cloud Queue IDs (UUIDs).
            metrics: List of metric names to retrieve (e.g., ['waitingCalls', 'availableAgents']).
            
        Returns:
            Dictionary containing the query result.
        """
        # Construct the query body
        query_body = {
            "view": "QueueCurrentMetricsView",
            "entities": queue_ids,
            "metrics": metrics
        }

        try:
            response = requests.post(
                self.metrics_endpoint,
                headers=self.headers,
                data=json.dumps(query_body)
            )
            
            # Handle HTTP errors explicitly
            if response.status_code == 401:
                raise Exception("Unauthorized: Token may be expired or invalid.")
            elif response.status_code == 403:
                raise Exception("Forbidden: Check if 'analytics:report:read' scope is granted.")
            elif response.status_code == 429:
                raise Exception("Rate Limited: Too many requests. Implement exponential backoff.")
            
            response.raise_for_status()
            return response.json()

        except requests.exceptions.HTTPError as e:
            print(f"HTTP Error: {e.response.status_code} - {e.response.text}")
            raise
        except requests.exceptions.ConnectionError:
            print("Connection Error: Unable to reach Genesys Cloud API.")
            raise
        except json.JSONDecodeError:
            print("JSON Decode Error: Response was not valid JSON.")
            raise

# Example Usage
# queue_ids = ["12345678-1234-1234-1234-1234567890ab"] # Replace with actual Queue ID
# metrics_to_fetch = ["waitingCalls", "availableAgents", "inProgressCalls"]
# client = QueueMetricsClient(auth.base_url, auth.get_access_token())
# result = client.get_queue_metrics(queue_ids, metrics_to_fetch)

JavaScript Implementation

class QueueMetricsClient {
    constructor(baseUrl, accessToken) {
        this.baseUrl = baseUrl;
        this.accessToken = accessToken;
        this.metricsEndpoint = `${baseUrl}/api/v2/analytics/queues/currentmetrics/query`;
        this.headers = {
            'Authorization': `Bearer ${accessToken}`,
            'Content-Type': 'application/json'
        };
    }

    async getQueueMetrics(queueIds, metrics) {
        const queryBody = {
            view: "QueueCurrentMetricsView",
            entities: queueIds,
            metrics: metrics
        };

        try {
            const response = await axios.post(
                this.metricsEndpoint,
                queryBody,
                { headers: this.headers }
            );

            return response.data;
        } catch (error) {
            if (error.response) {
                const status = error.response.status;
                if (status === 401) {
                    throw new Error("Unauthorized: Token may be expired or invalid.");
                } else if (status === 403) {
                    throw new Error("Forbidden: Check if 'analytics:report:read' scope is granted.");
                } else if (status === 429) {
                    throw new Error("Rate Limited: Too many requests. Implement exponential backoff.");
                }
                console.error(`HTTP Error ${status}: ${error.response.data}`);
            } else {
                console.error(`Network Error: ${error.message}`);
            }
            throw error;
        }
    }
}

// Example Usage
// const queueIds = ["12345678-1234-1234-1234-1234567890ab"]; // Replace with actual Queue ID
// const metricsToFetch = ["waitingCalls", "availableAgents", "inProgressCalls"];
// const client = new QueueMetricsClient(auth.baseUrl, await auth.getAccessToken());
// const result = await client.getQueueMetrics(queueIds, metricsToFetch);

Step 2: Process the Response Structure

The API returns a wrapper object containing a results array. Each item in results corresponds to one queue entity requested. The actual metric values are nested under the metrics key within each result object.

Realistic Response Example:

{
  "view": "QueueCurrentMetricsView",
  "results": [
    {
      "entityId": "12345678-1234-1234-1234-1234567890ab",
      "entityType": "queue",
      "entityName": "Customer Support",
      "metrics": {
        "abandonedCalls": {
          "value": 2
        },
        "availableAgents": {
          "value": 5
        },
        "waitingCalls": {
          "value": 12
        },
        "inProgressCalls": {
          "value": 8
        }
      }
    }
  ]
}

Python Processing Logic

def parse_queue_metrics(response_data: Dict[str, Any]) -> List[Dict[str, Any]]:
    """
    Parses the API response into a simplified list of dictionaries.
    
    Args:
        response_data: The JSON response from the API.
        
    Returns:
        A list of dictionaries with queue name and key metrics.
    """
    parsed_results = []
    
    if 'results' not in response_data:
        return []
        
    for queue_result in response_data['results']:
        queue_name = queue_result.get('entityName', 'Unknown Queue')
        metrics = queue_result.get('metrics', {})
        
        # Extract values safely, defaulting to 0 if metric is missing
        waiting = metrics.get('waitingCalls', {}).get('value', 0)
        available = metrics.get('availableAgents', {}).get('value', 0)
        in_progress = metrics.get('inProgressCalls', {}).get('value', 0)
        abandoned = metrics.get('abandonedCalls', {}).get('value', 0)
        
        parsed_results.append({
            'queue_name': queue_name,
            'waiting_calls': waiting,
            'available_agents': available,
            'in_progress_calls': in_progress,
            'abandoned_calls': abandoned
        })
        
    return parsed_results

JavaScript Processing Logic

function parseQueueMetrics(responseData) {
    if (!responseData || !responseData.results) {
        return [];
    }

    return responseData.results.map(queueResult => {
        const metrics = queueResult.metrics || {};
        
        const getValue = (metricName) => {
            return metrics[metricName] ? metrics[metricName].value : 0;
        };

        return {
            queueName: queueResult.entityName || 'Unknown Queue',
            waitingCalls: getValue('waitingCalls'),
            availableAgents: getValue('availableAgents'),
            inProgressCalls: getValue('inProgressCalls'),
            abandonedCalls: getValue('abandonedCalls')
        };
    });
}

Step 3: Handling Edge Cases and Pagination

The currentmetrics/query endpoint does not support traditional cursor-based pagination like historical report endpoints. However, if you query a large number of queues (e.g., 500+), the response time may increase.

Best Practice: If you need to monitor hundreds of queues, batch your requests. The API allows up to a reasonable number of entities in the entities array, but splitting them into chunks of 50-100 ensures faster response times and reduces the risk of timeout errors.

Python Batching Logic:

def get_metrics_in_batches(queue_ids: List[str], metrics: List[str], batch_size: int = 50) -> List[Dict[str, Any]]:
    """
    Splits queue IDs into batches to prevent timeouts and manage load.
    """
    all_results = []
    
    # Create batches
    for i in range(0, len(queue_ids), batch_size):
        batch = queue_ids[i:i + batch_size]
        # Assuming 'client' is an instance of QueueMetricsClient
        try:
            response_data = client.get_queue_metrics(batch, metrics)
            parsed = parse_queue_metrics(response_data)
            all_results.extend(parsed)
        except Exception as e:
            print(f"Error processing batch starting at index {i}: {e}")
            # Optionally implement retry logic here
            
    return all_results

Complete Working Example

Python: Full Script

import os
import requests
import json
from typing import List, Dict, Any

# --- Configuration ---
ENVIRONMENT = os.getenv('GENESYS_ENV', 'us')
CLIENT_ID = os.getenv('GENESYS_CLIENT_ID')
CLIENT_SECRET = os.getenv('GENESYS_CLIENT_SECRET')
QUEUE_ID = os.getenv('GENESYS_QUEUE_ID') # Single queue ID for demo

if not CLIENT_ID or not CLIENT_SECRET or not QUEUE_ID:
    raise ValueError("Missing required environment variables: GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, GENESYS_QUEUE_ID")

# --- Authentication ---
class GenesysAuth:
    def __init__(self, env, client_id, client_secret):
        self.client_id = client_id
        self.client_secret = client_secret
        if env == 'us':
            self.base_url = 'https://api.mypurecloud.com'
        elif env == 'eu':
            self.base_url = 'https://api.eu.mypurecloud.com'
        else:
            raise ValueError("Unsupported environment")
        self.token_url = f'{self.base_url}/oauth/token'
        self.access_token = None

    def get_access_token(self) -> str:
        if self.access_token:
            return self.access_token
        payload = {
            'grant_type': 'client_credentials',
            'client_id': self.client_id,
            'client_secret': self.client_secret
        }
        response = requests.post(self.token_url, data=payload)
        response.raise_for_status()
        self.access_token = response.json()['access_token']
        return self.access_token

# --- API Client ---
class QueueMetricsClient:
    def __init__(self, base_url, access_token):
        self.base_url = base_url
        self.access_token = access_token
        self.metrics_endpoint = f'{base_url}/api/v2/analytics/queues/currentmetrics/query'
        self.headers = {
            'Authorization': f'Bearer {access_token}',
            'Content-Type': 'application/json'
        }

    def get_queue_metrics(self, queue_ids: List[str], metrics: List[str]) -> Dict[str, Any]:
        query_body = {
            "view": "QueueCurrentMetricsView",
            "entities": queue_ids,
            "metrics": metrics
        }
        response = requests.post(self.metrics_endpoint, headers=self.headers, data=json.dumps(query_body))
        response.raise_for_status()
        return response.json()

# --- Processing ---
def parse_metrics(data: Dict[str, Any]) -> List[Dict[str, Any]]:
    results = []
    for item in data.get('results', []):
        metrics = item.get('metrics', {})
        results.append({
            'name': item.get('entityName'),
            'waiting': metrics.get('waitingCalls', {}).get('value', 0),
            'available': metrics.get('availableAgents', {}).get('value', 0),
            'in_progress': metrics.get('inProgressCalls', {}).get('value', 0)
        })
    return results

# --- Main Execution ---
def main():
    try:
        auth = GenesysAuth(ENVIRONMENT, CLIENT_ID, CLIENT_SECRET)
        token = auth.get_access_token()
        
        client = QueueMetricsClient(auth.base_url, token)
        
        # Define metrics to fetch
        metrics_list = ["waitingCalls", "availableAgents", "inProgressCalls"]
        
        # Fetch data
        print(f"Fetching metrics for Queue ID: {QUEUE_ID}")
        response_data = client.get_queue_metrics([QUEUE_ID], metrics_list)
        
        # Parse and Display
        parsed = parse_metrics(response_data)
        for queue_data in parsed:
            print(f"Queue: {queue_data['name']}")
            print(f"  Waiting Calls: {queue_data['waiting']}")
            print(f"  Available Agents: {queue_data['available']}")
            print(f"  In Progress: {queue_data['in_progress']}")
            
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    main()

JavaScript: Full Script

require('dotenv').config();
const axios = require('axios');

// --- Configuration ---
const ENVIRONMENT = process.env.GENESYS_ENV || 'us';
const CLIENT_ID = process.env.GENESYS_CLIENT_ID;
const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET;
const QUEUE_ID = process.env.GENESYS_QUEUE_ID;

if (!CLIENT_ID || !CLIENT_SECRET || !QUEUE_ID) {
    throw new Error("Missing required environment variables");
}

// --- Authentication ---
class GenesysAuth {
    constructor(env, clientId, clientSecret) {
        this.clientId = clientId;
        this.clientSecret = clientSecret;
        if (env === 'us') {
            this.baseUrl = 'https://api.mypurecloud.com';
        } else if (env === 'eu') {
            this.baseUrl = 'https://api.eu.mypurecloud.com';
        } else {
            throw new Error('Unsupported environment');
        }
        this.tokenUrl = `${this.baseUrl}/oauth/token`;
        this.accessToken = null;
    }

    async getAccessToken() {
        if (this.accessToken) return this.accessToken;
        const payload = new URLSearchParams({
            grant_type: 'client_credentials',
            client_id: this.clientId,
            client_secret: this.clientSecret
        });
        const response = await axios.post(this.tokenUrl, payload, {
            headers: { 'Content-Type': 'application/x-www-form-urlencoded' }
        });
        this.accessToken = response.data.access_token;
        return this.accessToken;
    }
}

// --- API Client ---
class QueueMetricsClient {
    constructor(baseUrl, accessToken) {
        this.baseUrl = baseUrl;
        this.accessToken = accessToken;
        this.metricsEndpoint = `${baseUrl}/api/v2/analytics/queues/currentmetrics/query`;
        this.headers = {
            'Authorization': `Bearer ${accessToken}`,
            'Content-Type': 'application/json'
        };
    }

    async getQueueMetrics(queueIds, metrics) {
        const queryBody = {
            view: "QueueCurrentMetricsView",
            entities: queueIds,
            metrics: metrics
        };
        const response = await axios.post(this.metricsEndpoint, queryBody, { headers: this.headers });
        return response.data;
    }
}

// --- Processing ---
function parseMetrics(data) {
    if (!data || !data.results) return [];
    return data.results.map(item => {
        const metrics = item.metrics || {};
        return {
            name: item.entityName,
            waiting: metrics.waitingCalls ? metrics.waitingCalls.value : 0,
            available: metrics.availableAgents ? metrics.availableAgents.value : 0,
            inProgress: metrics.inProgressCalls ? metrics.inProgressCalls.value : 0
        };
    });
}

// --- Main Execution ---
async function main() {
    try {
        const auth = new GenesysAuth(ENVIRONMENT, CLIENT_ID, CLIENT_SECRET);
        const token = await auth.getAccessToken();
        
        const client = new QueueMetricsClient(auth.baseUrl, token);
        const metricsList = ["waitingCalls", "availableAgents", "inProgressCalls"];
        
        console.log(`Fetching metrics for Queue ID: ${QUEUE_ID}`);
        const responseData = await client.getQueueMetrics([QUEUE_ID], metricsList);
        
        const parsed = parseMetrics(responseData);
        parsed.forEach(queueData => {
            console.log(`Queue: ${queueData.name}`);
            console.log(`  Waiting Calls: ${queueData.waiting}`);
            console.log(`  Available Agents: ${queueData.available}`);
            console.log(`  In Progress: ${queueData.inProgress}`);
        });
    } catch (error) {
        console.error("Error:", error.message);
    }
}

main();

Common Errors & Debugging

Error: 401 Unauthorized

• What causes it: The access token is expired, invalid, or missing.
• How to fix it: Ensure your OAuth client has the correct client_id and client_secret. Check that the token was retrieved successfully before making the API call. If using a cached token, verify it has not exceeded its 1-hour TTL.
• Code Fix: Implement a retry mechanism that refreshes the token upon receiving a 401.

Error: 403 Forbidden

• What causes it: The OAuth client does not have the required scope.
• How to fix it: Go to the Genesys Cloud Admin UI > Platform > Applications > OAuth 2.0 Clients. Select your client and ensure analytics:report:read is checked under Scopes.
• Code Fix: None required in code, but log the error clearly to guide the administrator.

Error: 429 Too Many Requests

• What causes it: You have exceeded the API rate limit (requests per second or per minute).
• How to fix it: Implement exponential backoff. If you receive a 429, wait for the duration specified in the Retry-After header (if present) or wait 1-5 seconds before retrying.
• Code Fix: Add a retry loop with delay.

import time

def fetch_with_retry(client, queue_ids, metrics, max_retries=3):
    for attempt in range(max_retries):
        try:
            return client.get_queue_metrics(queue_ids, metrics)
        except requests.exceptions.HTTPError as e:
            if e.response.status_code == 429:
                wait_time = 2 ** attempt # Exponential backoff: 1s, 2s, 4s
                print(f"Rate limited. Waiting {wait_time} seconds...")
                time.sleep(wait_time)
            else:
                raise
    raise Exception("Max retries exceeded")

Error: Empty Results

• What causes it: The entities array contained invalid Queue IDs or queues that do not exist in the current organization.
• How to fix it: Verify the Queue ID using the /api/v2/routing/queues/{queueId} endpoint. Ensure the ID matches the format of a UUID.

Official References

• Genesys Cloud Analytics Queue Current Metrics API Documentation
• Genesys Cloud OAuth 2.0 Documentation
• Genesys Cloud Metrics Reference