Implementing Overflow Routing Logic in Genesys Cloud with a TypeScript Webhook

How-To-Articles
1

Implementing Overflow Routing Logic in Genesys Cloud with a TypeScript Webhook

What You Will Build

  • A TypeScript webhook handler that polls realtime queue metrics, calculates sliding window wait-time averages, triggers priority-based queue transfers when thresholds are breached, and preserves customer context by updating interaction attributes via the Routing API.
  • This tutorial uses the Genesys Cloud JavaScript SDK (@genesys/cloud-purecloud-api-client) and the REST Routing endpoints.
  • Language: TypeScript (Node.js 18+).

Prerequisites

  • OAuth client type: Confidential Client (Client Credentials Grant) or JWT Grant.
  • Required scopes: routing:queue:read, routing:interaction:read, routing:interaction:write, routing:transfer
  • SDK version: @genesys/cloud-purecloud-api-client v8.0 or later
  • Runtime: Node.js 18+ with ts-node or compiled to JavaScript
  • External dependencies: dotenv, express, uuid

Authentication Setup

Genesys Cloud requires OAuth 2.0 bearer tokens for all API calls. The JavaScript SDK handles token acquisition and automatic refresh when configured correctly. You must set three environment variables before initialization.

import { PlatformClient } from '@genesys/cloud-purecloud-api-client';
import dotenv from 'dotenv';

dotenv.config();

export function initializeGenesysClient(): PlatformClient {
  const client = PlatformClient.create();
  
  client.loginClientCredentials(
    process.env.GENESYS_CLIENT_ID!,
    process.env.GENESYS_CLIENT_SECRET!,
    process.env.GENESYS_ENVIRONMENT! // Example: 'mypurecloud.ie' or 'usw2.pure.cloud'
  );
  
  return client;
}

The SDK caches the access token internally and attaches the Authorization: Bearer <token> header to every request. If the token expires during execution, the SDK automatically triggers a refresh grant before retrying the failed call.

Implementation

Step 1: Build the Sliding Window Calculator

Queue wait times fluctuate rapidly. A single metric snapshot triggers false positives. You must implement a sliding window calculator that aggregates wait times over a configurable duration and calculates the moving average.

interface WaitSample {
  timestamp: number;
  waitTimeMs: number;
}

export class SlidingWindowCalculator {
  private windowSeconds: number;
  private samples: WaitSample[] = [];

  constructor(windowSeconds: number) {
    this.windowSeconds = windowSeconds;
  }

  public addSample(waitTimeMs: number): void {
    const now = Date.now();
    this.samples.push({ timestamp: now, waitTimeMs });
    this.pruneExpired(now);
  }

  private pruneExpired(now: number): void {
    const cutoff = now - (this.windowSeconds * 1000);
    this.samples = this.samples.filter(sample => sample.timestamp >= cutoff);
  }

  public getAverageWaitMs(): number {
    if (this.samples.length === 0) return 0;
    const total = this.samples.reduce((sum, sample) => sum + sample.waitTimeMs, 0);
    return total / this.samples.length;
  }

  public getSampleCount(): number {
    return this.samples.length;
  }
}

The calculator maintains an array of timestamped samples. On each addition, it removes entries older than the window duration. The average calculation divides the sum of active samples by the count. This prevents memory leaks and ensures the threshold check always reflects recent traffic patterns.

Step 2: Monitor Queue Metrics and Detect Breaches

The Routing API exposes realtime queue metrics at GET /api/v2/routing/queues/{queueId}/metrics/realtime. You will poll this endpoint, feed the waitTime field into the sliding window calculator, and compare the average against your overflow threshold.

import { PlatformClient } from '@genesys/cloud-purecloud-api-client';

export async function fetchQueueWaitTime(client: PlatformClient, queueId: string): Promise<number> {
  const routingApi = client.getRoutingApi();
  const metrics = await routingApi.getRoutingQueueMetricsRealtime(queueId);
  
  // The realtime response contains an array of queue metrics
  if (!metrics.body || metrics.body.length === 0) {
    throw new Error('No realtime metrics returned for queue');
  }
  
  // waitTime is provided in milliseconds
  return metrics.body[0].waitTime ?? 0;
}

export function evaluateBreach(
  calculator: SlidingWindowCalculator, 
  thresholdSeconds: number, 
  minSamples: number
): boolean {
  if (calculator.getSampleCount() < minSamples) return false;
  
  const avgWaitMs = calculator.getAverageWaitMs();
  const thresholdMs = thresholdSeconds * 1000;
  
  console.log(`[Monitor] Average wait: ${avgWaitMs}ms | Threshold: ${thresholdMs}ms`);
  return avgWaitMs > thresholdMs;
}

HTTP Request/Response Cycle for Realtime Metrics:

  • Method: GET
  • Path: /api/v2/routing/queues/{queueId}/metrics/realtime
  • Headers: Authorization: Bearer <token>, Content-Type: application/json
  • Request Body: None
  • Response Body:
{
  "queueMetrics": [
    {
      "queueId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "waitTime": 45000,
      "queueSize": 12,
      "agentCount": 5,
      "utilization": 0.82
    }
  ]
}

The waitTime field represents the average wait time of interactions currently in the queue. You must pass this value to calculator.addSample() on every poll cycle.

Step 3: Construct Transfer Requests and Update Attributes

When the sliding window average exceeds the threshold, you must identify interactions eligible for overflow, update their attributes to preserve context, and initiate the transfer. Genesys Cloud requires two sequential API calls for a context-preserving handoff.

First, update the interaction attributes using PUT /api/v2/routing/interactions/{interactionId}. This step attaches routing metadata before the transfer executes.

export async function updateInteractionAttributes(
  client: PlatformClient, 
  interactionId: string, 
  originalQueueId: string,
  overflowTargetQueueId: string
): Promise<void> {
  const routingApi = client.getRoutingApi();
  
  const payload = {
    attributes: {
      routing: {
        overflowContext: {
          triggeredBy: 'waitTimeThresholdBreach',
          originalQueueId: originalQueueId,
          targetQueueId: overflowTargetQueueId,
          handoffTimestamp: new Date().toISOString(),
          preserveWrapUp: true
        }
      }
    }
  };

  try {
    await routingApi.putRoutingInteraction(interactionId, payload);
    console.log(`[Context] Updated attributes for interaction ${interactionId}`);
  } catch (error: any) {
    if (error.status === 403) {
      throw new Error('Insufficient permissions to update interaction attributes. Verify routing:interaction:write scope.');
    }
    if (error.status === 404) {
      throw new Error(`Interaction ${interactionId} not found or already completed.`);
    }
    throw error;
  }
}

Second, construct the transfer request using POST /api/v2/routing/interactions/{interactionId}/transfers. The payload must specify QUEUE as the transfer type and reference the target queue identifier.

export async function executeQueueTransfer(
  client: PlatformClient, 
  interactionId: string, 
  targetQueueId: string, 
  priority: number
): Promise<void> {
  const routingApi = client.getRoutingApi();
  
  const transferPayload = {
    transferType: 'QUEUE',
    target: {
      id: targetQueueId,
      type: 'queue'
    },
    priority: priority, // Higher numbers indicate higher priority in the target queue
    reason: 'Overflow routing triggered by sliding window threshold breach'
  };

  try {
    await routingApi.postRoutingInteractionsInteractionIdTransfers(interactionId, transferPayload);
    console.log(`[Transfer] Initiated queue transfer for interaction ${interactionId} to ${targetQueueId}`);
  } catch (error: any) {
    if (error.status === 409) {
      throw new Error('Interaction is already in a transfer state or cannot be routed to the target queue.');
    }
    if (error.status === 422) {
      throw new Error('Invalid transfer payload. Verify queue accessibility and interaction status.');
    }
    throw error;
  }
}

HTTP Request/Response Cycle for Attribute Update:

  • Method: PUT
  • Path: /api/v2/routing/interactions/{interactionId}
  • Headers: Authorization: Bearer <token>, Content-Type: application/json
  • Request Body:
{
  "attributes": {
    "routing": {
      "overflowContext": {
        "triggeredBy": "waitTimeThresholdBreach",
        "originalQueueId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
        "targetQueueId": "f9e8d7c6-b5a4-3210-fedc-ba9876543210",
        "handoffTimestamp": "2024-05-15T14:32:00.000Z",
        "preserveWrapUp": true
      }
    }
  }
}
  • Response: 204 No Content (Success)

HTTP Request/Response Cycle for Transfer:

  • Method: POST
  • Path: /api/v2/routing/interactions/{interactionId}/transfers
  • Headers: Authorization: Bearer <token>, Content-Type: application/json
  • Request Body:
{
  "transferType": "QUEUE",
  "target": {
    "id": "f9e8d7c6-b5a4-3210-fedc-ba9876543210",
    "type": "queue"
  },
  "priority": 8,
  "reason": "Overflow routing triggered by sliding window threshold breach"
}
  • Response: 202 Accepted with a transfer initiation confirmation.

Step 4: Implement Rate Limit Protection

Genesys Cloud enforces strict API rate limits. A polling webhook must handle 429 Too Many Requests gracefully. Wrap your API calls in a retry function with exponential backoff.

export async function retryOnRateLimit<T>(fn: () => Promise<T>, maxRetries = 3, baseDelayMs = 1000): Promise<T> {
  let attempt = 0;
  
  while (true) {
    try {
      return await fn();
    } catch (error: any) {
      attempt++;
      if (error.status === 429 && attempt < maxRetries) {
        const retryAfter = error.headers?.['retry-after'] ? parseInt(error.headers['retry-after']) : baseDelayMs * Math.pow(2, attempt);
        console.warn(`[RateLimit] 429 received. Retrying in ${retryAfter}ms (attempt ${attempt}/${maxRetries})`);
        await new Promise(resolve => setTimeout(resolve, retryAfter));
        continue;
      }
      throw error;
    }
  }
}

Use this wrapper around every SDK method call. The function reads the Retry-After header when present, falls back to exponential backoff, and aborts after the maximum retry count.

Complete Working Example

The following script combines all components into a production-ready webhook handler. It polls a source queue every 30 seconds, maintains a 5-minute sliding window, and routes interactions to a target queue when the average wait exceeds 90 seconds.

import { PlatformClient } from '@genesys/cloud-purecloud-api-client';
import dotenv from 'dotenv';
import { SlidingWindowCalculator } from './calculator';
import { fetchQueueWaitTime, evaluateBreach } from './monitor';
import { updateInteractionAttributes, executeQueueTransfer } from './transfer';
import { retryOnRateLimit } from './retry';

dotenv.config();

async function main() {
  const client = PlatformClient.create();
  await retryOnRateLimit(() => client.loginClientCredentials(
    process.env.GENESYS_CLIENT_ID!,
    process.env.GENESYS_CLIENT_SECRET!,
    process.env.GENESYS_ENVIRONMENT!
  ));

  const SOURCE_QUEUE_ID = process.env.SOURCE_QUEUE_ID!;
  const TARGET_QUEUE_ID = process.env.TARGET_QUEUE_ID!;
  const WINDOW_SECONDS = 300; // 5 minutes
  const THRESHOLD_SECONDS = 90;
  const POLL_INTERVAL_MS = 30000;

  const calculator = new SlidingWindowCalculator(WINDOW_SECONDS);
  const monitoredInteractions = new Set<string>();

  console.log('[Webhook] Overflow routing monitor initialized.');

  setInterval(async () => {
    try {
      // 1. Fetch current wait time
      const currentWait = await retryOnRateLimit(() => fetchQueueWaitTime(client, SOURCE_QUEUE_ID));
      calculator.addSample(currentWait);

      // 2. Evaluate threshold breach
      if (!evaluateBreach(calculator, THRESHOLD_SECONDS, 3)) {
        console.log('[Monitor] Below threshold. Continuing poll cycle.');
        return;
      }

      console.log('[Breach] Threshold exceeded. Searching for overflow candidates.');

      // 3. Retrieve interactions in queue
      const routingApi = client.getRoutingApi();
      const interactions = await retryOnRateLimit(() => 
        routingApi.getRoutingInteractions({ queueIds: SOURCE_QUEUE_ID, status: 'queued' })
      );

      if (!interactions.body?.items?.length) {
        console.log('[Monitor] No queued interactions found.');
        return;
      }

      // 4. Process up to 5 interactions per cycle to avoid cascading transfers
      const candidates = interactions.body.items.slice(0, 5);
      
      for (const interaction of candidates) {
        const interactionId = interaction.id!;
        if (monitoredInteractions.has(interactionId)) continue;
        
        monitoredInteractions.add(interactionId);

        try {
          // Update context first
          await retryOnRateLimit(() => 
            updateInteractionAttributes(client, interactionId, SOURCE_QUEUE_ID, TARGET_QUEUE_ID)
          );

          // Execute transfer with priority 7
          await retryOnRateLimit(() => 
            executeQueueTransfer(client, interactionId, TARGET_QUEUE_ID, 7)
          );
        } catch (err: any) {
          console.error(`[Error] Failed to process interaction ${interactionId}:`, err.message);
        }
      }

    } catch (error: any) {
      console.error('[Critical] Poll cycle failed:', error.message);
    }
  }, POLL_INTERVAL_MS);
}

main().catch(console.error);

Common Errors & Debugging

Error: 401 Unauthorized

  • What causes it: The OAuth client credentials are incorrect, the token expired, or the SDK failed to refresh.
  • How to fix it: Verify GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, and GENESYS_ENVIRONMENT match your Genesys Cloud admin console. Ensure the client is enabled and not revoked.
  • Code showing the fix: The SDK handles refresh automatically. If you see persistent 401s, add a token validation check before polling:
const token = await client.getAccessToken();
if (!token) throw new Error('Token acquisition failed. Check credentials.');

Error: 403 Forbidden

  • What causes it: The OAuth token lacks required scopes, or the client does not have permission to access the specified queues.
  • How to fix it: Navigate to Admin > Security > API Security. Edit your OAuth client and add routing:queue:read, routing:interaction:read, routing:interaction:write, and routing:transfer. Save and regenerate tokens.
  • Code showing the fix: Explicitly declare scopes during client initialization if using custom grant flows:
client.loginClientCredentials(clientId, clientSecret, environment, ['routing:queue:read', 'routing:interaction:write', 'routing:transfer']);

Error: 429 Too Many Requests

  • What causes it: The polling interval is too aggressive, or concurrent webhooks exceed the tenant API quota.
  • How to fix it: Increase POLL_INTERVAL_MS to at least 30000. Implement the retryOnRateLimit wrapper shown in Step 4. Monitor the X-RateLimit-Remaining response header to adjust frequency dynamically.
  • Code showing the fix: The retry wrapper already handles this. Add header logging for visibility:
console.log(`[RateLimit] Remaining: ${error.headers['x-ratelimit-remaining']}`);

Error: 409 Conflict on Transfer

  • What causes it: The interaction is already transferring, has been answered, or the target queue has incompatible skill requirements.
  • How to fix it: Filter interactions by status: 'queued' before transfer. Validate that the target queue accepts the same channel type and skill group. Wrap the transfer call in a try-catch and skip interactions that fail with 409.
  • Code showing the fix: The complete example already filters by status: 'queued' and catches 409 errors. Add a deduplication check using monitoredInteractions to prevent reprocessing.

Official References