Automating real-time queue metric aggregation and CSV report generation using the Genesys Cloud Analytics API and a Node.js scheduled task

What You Will Build

This script polls the Genesys Cloud real-time queue metrics endpoint, aggregates the results across paginated responses, transforms the nested JSON structure into flat rows, and writes the output to a timestamped CSV file. The solution relies on the Genesys Cloud Analytics API and the official Node.js SDK for authentication and query execution. The implementation is written in Node.js using modern async syntax and production-ready error handling.

Prerequisites

• OAuth 2.0 client credentials (Client ID and Client Secret) with the analytics:query scope
• Genesys Cloud Node.js SDK versions: @genesyscloud/api-auth >= 3.0.0, @genesyscloud/api-analytics >= 3.0.0
• Node.js runtime version 18.0.0 or higher
• External dependencies: json2csv for data transformation, node-cron for task scheduling

Authentication Setup

Genesys Cloud uses OAuth 2.0 client credentials flow for server-to-server integrations. The official SDK abstracts the token exchange and handles automatic refresh before expiration. You must initialize the AuthClient with your environment region, client ID, client secret, and the required scopes.

import { AuthClient } from '@genesyscloud/api-auth';

const envName = 'mypurecloud'; // Replace with your environment name
const clientId = process.env.GENESYS_CLIENT_ID;
const clientSecret = process.env.GENESYS_CLIENT_SECRET;

const authClient = new AuthClient({
  envName: envName,
  clientId: clientId,
  clientSecret: clientSecret,
  scopes: ['analytics:query']
});

// Initialize and cache the token. The SDK automatically manages refresh cycles.
await authClient.init();

The SDK stores the access token in memory and attaches it to subsequent requests. You do not need to implement manual refresh logic because the SDK intercepts 401 Unauthorized responses, rotates the token, and retries the original request transparently.

Implementation

Step 1: Construct the Real-Time Query Payload

The real-time queue metrics endpoint requires a POST request to /api/v2/analytics/queues/details/query. The request body defines the time interval, grouping dimensions, selected metrics, and optional filters. Genesys Cloud designs this endpoint as a POST rather than a GET because query parameters can become excessively large when specifying multiple filters, date ranges, and metric selections. The API also validates the JSON schema server-side before executing the aggregation.

const buildQueryPayload = (queueIds, intervalStart, intervalEnd) => {
  const filter = queueIds.length > 0 
    ? [{ type: 'eq', dimension: 'queue.id', value: queueIds }] 
    : [];

  return {
    query: {
      interval: `${intervalStart}/${intervalEnd}`,
      type: 'queue',
      groupBy: ['queue.id'],
      select: [
        { name: 'queue.handleCount' },
        { name: 'queue.abandonedCount' },
        { name: 'queue.answeredCount' },
        { name: 'queue.avgHandleTime' },
        { name: 'queue.serviceLevelPercent' },
        { name: 'queue.waitTime' }
      ],
      filter: filter
    },
    pageSize: 25
  };
};

The interval field uses ISO 8601 date-time format. Real-time data is typically available with a 15 to 30 second delay, so you should query a window that ends a few minutes in the past to guarantee data availability. The pageSize parameter controls pagination. The API returns a maximum of 100 entities per page, and you must iterate through pageToken values until the response returns null.

Step 2: Execute Query with Pagination and Retry Logic

Rate limiting is enforced at the tenant level for analytics endpoints. The API returns a 429 Too Many Requests response when you exceed the threshold. The response includes a Retry-After header indicating the number of seconds to wait before the next request. You must implement exponential backoff with jitter to prevent cascading failures.

const executeRealTimeQuery = async (authClient, payload, maxRetries = 3) => {
  const baseUrl = `https://${process.env.GENESYS_ENV_NAME}.mypurecloud.com/api/v2/analytics/queues/details/query`;
  const allEntities = [];
  let pageToken = null;
  let retryCount = 0;

  do {
    if (pageToken) {
      payload.query.pageToken = pageToken;
    }

    try {
      const token = await authClient.getAccessToken();
      const response = await fetch(baseUrl, {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${token}`,
          'Accept': 'application/json'
        },
        body: JSON.stringify(payload)
      });

      if (response.status === 429) {
        retryCount++;
        if (retryCount > maxRetries) throw new Error('Max retry limit exceeded for 429 response');
        const retryAfter = parseInt(response.headers.get('Retry-After') || '5', 10);
        const jitter = Math.floor(Math.random() * 1000);
        console.warn(`Rate limited. Retrying after ${retryAfter}s + ${jitter}ms jitter`);
        await new Promise(resolve => setTimeout(resolve, retryAfter * 1000 + jitter));
        continue;
      }

      if (!response.ok) {
        const errorBody = await response.text();
        throw new Error(`API Error ${response.status}: ${errorBody}`);
      }

      const data = await response.json();
      if (data.entities && Array.isArray(data.entities)) {
        allEntities.push(...data.entities);
      }
      pageToken = data.pageToken || null;

    } catch (error) {
      if (error.message.includes('429')) throw error;
      console.error('Query execution failed:', error);
      throw error;
    }
  } while (pageToken && retryCount <= maxRetries);

  return allEntities;
};

The function handles pagination by appending pageToken to the query payload on subsequent iterations. It also implements the required retry logic for 429 responses using the Retry-After header and adds random jitter to prevent thundering herd scenarios when multiple scheduled tasks wake simultaneously.

Step 3: Flatten Response and Generate CSV

The API returns a nested structure where each entity contains an id, name, and a metrics object. CSV files require flat rows. You must extract the metric values into a single-level object per queue. The json2csv library handles type coercion and escaping automatically.

import { Parser } from 'json2csv';

const transformToCsvRows = (entities) => {
  return entities.map(entity => ({
    QueueId: entity.id,
    QueueName: entity.name,
    HandleCount: entity.metrics?.handleCount?.value ?? 0,
    AbandonedCount: entity.metrics?.abandonedCount?.value ?? 0,
    AnsweredCount: entity.metrics?.answeredCount?.value ?? 0,
    AvgHandleTimeMs: entity.metrics?.avgHandleTime?.value ?? 0,
    ServiceLevelPercent: entity.metrics?.serviceLevelPercent?.value ?? 0,
    WaitTimeMs: entity.metrics?.waitTime?.value ?? 0,
    IntervalStart: entity.metrics?.intervalStart ?? '',
    IntervalEnd: entity.metrics?.intervalEnd ?? ''
  }));
};

const writeCsvReport = async (rows, outputPath) => {
  const parser = new Parser({
    fields: Object.keys(rows[0]),
    quote: '"',
    delimiter: ','
  });
  const csv = parser.parse(rows);
  await import('fs').then(fs => fs.promises.writeFile(outputPath, csv));
  console.log(`CSV report written to ${outputPath}`);
};

The transformation uses optional chaining and nullish coalescing to handle missing metric values safely. Genesys Cloud returns null or omits metric objects when no data exists for the interval. The json2csv parser enforces consistent column ordering and handles special characters in queue names.

Step 4: Schedule the Task with Cron

You use node-cron to trigger the aggregation at fixed intervals. The scheduler runs independently of the query execution, so you must handle concurrent execution prevention. The cron expression 0 */5 * * * * runs every 5 minutes.

import cron from 'node-cron';
import { format } from 'date-fns';

let isRunning = false;

const runAggregation = async () => {
  if (isRunning) {
    console.warn('Previous aggregation is still running. Skipping schedule.');
    return;
  }
  isRunning = true;
  try {
    const now = new Date();
    const intervalEnd = format(now, 'yyyy-MM-ddTHH:mm:ssXXX');
    const intervalStart = new Date(now.getTime() - 5 * 60 * 1000);
    const intervalStartStr = format(intervalStart, 'yyyy-MM-ddTHH:mm:ssXXX');
    
    const payload = buildQueryPayload([], intervalStartStr, intervalEnd);
    const entities = await executeRealTimeQuery(authClient, payload);
    const rows = transformToCsvRows(entities);
    const outputPath = `reports/queue_metrics_${format(now, 'yyyyMMdd_HHmmss')}.csv`;
    await writeCsvReport(rows, outputPath);
  } catch (error) {
    console.error('Aggregation failed:', error);
  } finally {
    isRunning = false;
  }
};

cron.schedule('0 */5 * * * *', runAggregation);
console.log('Scheduler initialized. Running every 5 minutes.');

The concurrency guard prevents overlapping executions if a query takes longer than the scheduled interval. The interval window shifts backward by 5 minutes to align with the scheduler frequency.

Complete Working Example

import { AuthClient } from '@genesyscloud/api-auth';
import { Parser } from 'json2csv';
import cron from 'node-cron';
import { format } from 'date-fns';
import fs from 'fs';
import path from 'path';
import { fileURLToPath } from 'url';

const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);

// Configuration
const ENV_NAME = process.env.GENESYS_ENV_NAME || 'mypurecloud';
const CLIENT_ID = process.env.GENESYS_CLIENT_ID;
const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET;

if (!CLIENT_ID || !CLIENT_SECRET) {
  throw new Error('GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET environment variables are required');
}

// Authentication
const authClient = new AuthClient({
  envName: ENV_NAME,
  clientId: CLIENT_ID,
  clientSecret: CLIENT_SECRET,
  scopes: ['analytics:query']
});

await authClient.init();

// Query Builder
const buildQueryPayload = (queueIds, intervalStart, intervalEnd) => {
  const filter = queueIds.length > 0 
    ? [{ type: 'eq', dimension: 'queue.id', value: queueIds }] 
    : [];

  return {
    query: {
      interval: `${intervalStart}/${intervalEnd}`,
      type: 'queue',
      groupBy: ['queue.id'],
      select: [
        { name: 'queue.handleCount' },
        { name: 'queue.abandonedCount' },
        { name: 'queue.answeredCount' },
        { name: 'queue.avgHandleTime' },
        { name: 'queue.serviceLevelPercent' },
        { name: 'queue.waitTime' }
      ],
      filter: filter
    },
    pageSize: 25
  };
};

// API Execution with Pagination and Retry
const executeRealTimeQuery = async (payload, maxRetries = 3) => {
  const baseUrl = `https://${ENV_NAME}.mypurecloud.com/api/v2/analytics/queues/details/query`;
  const allEntities = [];
  let pageToken = null;
  let retryCount = 0;

  do {
    if (pageToken) {
      payload.query.pageToken = pageToken;
    }

    try {
      const token = await authClient.getAccessToken();
      const response = await fetch(baseUrl, {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${token}`,
          'Accept': 'application/json'
        },
        body: JSON.stringify(payload)
      });

      if (response.status === 429) {
        retryCount++;
        if (retryCount > maxRetries) throw new Error('Max retry limit exceeded for 429 response');
        const retryAfter = parseInt(response.headers.get('Retry-After') || '5', 10);
        const jitter = Math.floor(Math.random() * 1000);
        console.warn(`Rate limited. Retrying after ${retryAfter}s + ${jitter}ms jitter`);
        await new Promise(resolve => setTimeout(resolve, retryAfter * 1000 + jitter));
        continue;
      }

      if (!response.ok) {
        const errorBody = await response.text();
        throw new Error(`API Error ${response.status}: ${errorBody}`);
      }

      const data = await response.json();
      if (data.entities && Array.isArray(data.entities)) {
        allEntities.push(...data.entities);
      }
      pageToken = data.pageToken || null;

    } catch (error) {
      if (error.message.includes('429')) throw error;
      console.error('Query execution failed:', error);
      throw error;
    }
  } while (pageToken && retryCount <= maxRetries);

  return allEntities;
};

// Data Transformation
const transformToCsvRows = (entities) => {
  return entities.map(entity => ({
    QueueId: entity.id,
    QueueName: entity.name,
    HandleCount: entity.metrics?.handleCount?.value ?? 0,
    AbandonedCount: entity.metrics?.abandonedCount?.value ?? 0,
    AnsweredCount: entity.metrics?.answeredCount?.value ?? 0,
    AvgHandleTimeMs: entity.metrics?.avgHandleTime?.value ?? 0,
    ServiceLevelPercent: entity.metrics?.serviceLevelPercent?.value ?? 0,
    WaitTimeMs: entity.metrics?.waitTime?.value ?? 0,
    IntervalStart: entity.metrics?.intervalStart ?? '',
    IntervalEnd: entity.metrics?.intervalEnd ?? ''
  }));
};

// CSV Writer
const writeCsvReport = async (rows, outputPath) => {
  if (rows.length === 0) {
    console.log('No data returned. Skipping CSV generation.');
    return;
  }
  const parser = new Parser({
    fields: Object.keys(rows[0]),
    quote: '"',
    delimiter: ','
  });
  const csv = parser.parse(rows);
  const reportDir = path.join(__dirname, 'reports');
  if (!fs.existsSync(reportDir)) fs.mkdirSync(reportDir, { recursive: true });
  const fullPath = path.join(reportDir, outputPath);
  await fs.promises.writeFile(fullPath, csv);
  console.log(`CSV report written to ${fullPath}`);
};

// Scheduler
let isRunning = false;

const runAggregation = async () => {
  if (isRunning) {
    console.warn('Previous aggregation is still running. Skipping schedule.');
    return;
  }
  isRunning = true;
  try {
    const now = new Date();
    const intervalEnd = format(now, 'yyyy-MM-ddTHH:mm:ssXXX');
    const intervalStart = new Date(now.getTime() - 5 * 60 * 1000);
    const intervalStartStr = format(intervalStart, 'yyyy-MM-ddTHH:mm:ssXXX');
    
    const payload = buildQueryPayload([], intervalStartStr, intervalEnd);
    const entities = await executeRealTimeQuery(payload);
    const rows = transformToCsvRows(entities);
    const fileName = `queue_metrics_${format(now, 'yyyyMMdd_HHmmss')}.csv`;
    await writeCsvReport(rows, fileName);
  } catch (error) {
    console.error('Aggregation failed:', error);
  } finally {
    isRunning = false;
  }
};

// Run immediately on start, then schedule
await runAggregation();
cron.schedule('0 */5 * * * *', runAggregation);
console.log('Scheduler initialized. Running every 5 minutes.');

Common Errors & Debugging

Error: 401 Unauthorized

The OAuth token has expired or the client credentials are invalid. The SDK handles automatic rotation, but if the initial init() fails, verify your environment name matches your tenant URL exactly. Ensure the client credentials grant programmatic access.

Fix: Regenerate the client secret in the Genesys Cloud admin console under Organization > Developer Tools > API Credentials. Confirm the environment name matches your subdomain.

Error: 403 Forbidden

The OAuth token lacks the required scope. The real-time queue metrics endpoint requires analytics:query. If you only granted admin:all or user:all, the API will reject the request.

Fix: Update the OAuth client configuration to include analytics:query. Restart the application to force a token refresh with the new scope.

Error: 429 Too Many Requests

You have exceeded the tenant rate limit for analytics queries. Genesys Cloud enforces limits based on query complexity and tenant tier. The response includes a Retry-After header.

Fix: Implement the retry logic shown in Step 2. Reduce query frequency if you consistently hit limits. Increase the interval window to reduce the number of scheduled executions.

Error: 500 Internal Server Error

The query payload contains invalid syntax or unsupported metric names. The API validates the select array against available dimensions. Using deprecated metric names causes server-side parsing failures.

Fix: Verify metric names against the official Analytics API documentation. Remove unsupported filters. Log the full request payload before sending to identify malformed JSON.

Official References

• Real-Time Queue Metrics API Documentation
• Node.js SDK Authentication Reference
• Analytics Query Payload Schema
• OAuth 2.0 Client Credentials Flow