Implementing a custom queue routing strategy by manipulating queue positions and agent availability through the Routing API using a Java client with optimistic locking

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Implementing a custom queue routing strategy by manipulating queue positions and agent availability through the Routing API using a Java client with optimistic locking

What You Will Build

  • This tutorial builds a Java service that programmatically updates agent availability states and routing skills to enforce a custom queue routing strategy.
  • It uses the Genesys Cloud CX Routing API (/api/v2/routing/users/{userId}/availability) and the official platform-client-java SDK.
  • The implementation demonstrates optimistic locking using the diversion field to prevent race conditions during concurrent routing updates.

Prerequisites

  • OAuth 2.0 Client Credentials flow configured in Genesys Cloud Admin with routing:availability:write and routing:availability:read scopes.
  • Genesys Cloud CX Java SDK version 19.5.0 or higher.
  • Java 17+ runtime environment.
  • Maven dependencies for platform-client-java and jackson-databind for JSON processing.
<dependency>
    <groupId>com.mendix.core.client</groupId>
    <artifactId>platform-client-java</artifactId>
    <version>19.5.0</version>
</dependency>
<dependency>
    <groupId>com.fasterxml.jackson.core</groupId>
    <artifactId>jackson-databind</artifactId>
    <version>2.15.2</version>
</dependency>

Authentication Setup

Genesys Cloud CX uses OAuth 2.0 for all API authentication. The Java SDK does not manage token lifecycles automatically, so you must implement a token fetcher and inject the access token into the ApiClient instance. The following code demonstrates a production-ready token acquisition method using Java 17 HttpClient.

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URLEncoder;
import java.nio.charset.StandardCharsets;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;

public class GenesysAuth {
    private static final String TOKEN_URL = "https://api.myspotinstance.com/api/v2/oauth/token";
    private static final ObjectMapper MAPPER = new ObjectMapper();

    public static String fetchAccessToken(String clientId, String clientSecret, String grantType) throws Exception {
        String body = String.format(
            "client_id=%s&client_secret=%s&grant_type=%s",
            URLEncoder.encode(clientId, StandardCharsets.UTF_8),
            URLEncoder.encode(clientSecret, StandardCharsets.UTF_8),
            URLEncoder.encode(grantType, StandardCharsets.UTF_8)
        );

        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(TOKEN_URL))
            .header("Content-Type", "application/x-www-form-urlencoded")
            .POST(HttpRequest.BodyPublishers.ofString(body))
            .build();

        HttpResponse<String> response = HttpClient.newHttpClient().send(request, HttpResponse.BodyHandlers.ofString());
        
        if (response.statusCode() != 200) {
            throw new RuntimeException("OAuth token request failed with status: " + response.statusCode());
        }

        JsonNode json = MAPPER.readTree(response.body());
        return json.get("access_token").asText();
    }
}

Implementation

Step 1: Initialize Client and Fetch Current Availability

Before manipulating routing behavior, you must retrieve the current availability state to obtain the diversion value. The diversion field acts as a version stamp for optimistic locking. Genesys Cloud rejects any availability update that does not include the current diversion value, preventing lost updates when multiple systems modify the same agent state simultaneously.

Required OAuth scope: routing:availability:read

import com.mendix.core.client.gen.client.ApiClient;
import com.mendix.core.client.gen.client.ApiException;
import com.mendix.core.client.gen.client.RoutingApi;
import com.mendix.core.client.gen.model.UserAvailability;

public class AvailabilityFetcher {
    private final RoutingApi routingApi;

    public AvailabilityFetcher(ApiClient apiClient) {
        this.routingApi = new RoutingApi(apiClient);
    }

    public UserAvailability getCurrentAvailability(String userId) throws ApiException {
        try {
            // GET /api/v2/routing/users/{userId}/availability
            UserAvailability current = routingApi.getRoutingUserAvailability(userId);
            
            if (current.getDiversion() == null) {
                throw new IllegalStateException("Diversion field is null. The user may not be provisioned for routing.");
            }
            return current;
        } catch (ApiException e) {
            if (e.getCode() == 404) {
                throw new RuntimeException("User " + userId + " not found in routing system.", e);
            }
            throw e;
        }
    }
}

Step 2: Apply Custom Routing Logic with Optimistic Locking

To enforce a custom routing strategy, you modify the state and wrapUpCode fields. For example, setting a specific wrap code can trigger post-interaction routing rules, while changing the state to Available or Busy directly impacts queue position calculations. You must copy the diversion value from Step 1 into the payload before submission.

Required OAuth scope: routing:availability:write

Raw HTTP equivalent:

POST /api/v2/routing/users/12345678-1234-1234-1234-123456789012/availability HTTP/1.1
Host: api.myspotinstance.com
Content-Type: application/json
Authorization: Bearer <access_token>

{
  "diversion": "3",
  "state": "Available",
  "wrapUpCode": "routing:wrapupcode:custom_routing_trigger",
  "reason": "System-driven routing adjustment"
}

public class RoutingStrategyApplier {
    private final RoutingApi routingApi;

    public RoutingStrategyApplier(ApiClient apiClient) {
        this.routingApi = new RoutingApi(apiClient);
    }

    public UserAvailability applyCustomStrategy(String userId, UserAvailability baseAvailability, String targetState, String targetWrapCode) throws ApiException {
        // Clone or create new availability object to preserve diversion
        UserAvailability updated = new UserAvailability();
        updated.setDiversion(baseAvailability.getDiversion()); // Critical for optimistic locking
        updated.setState(targetState);
        updated.setWrapUpCode(targetWrapCode);
        updated.setReason("Automated routing strategy adjustment");

        // POST /api/v2/routing/users/{userId}/availability
        UserAvailability result = routingApi.postRoutingUserAvailability(userId, updated);
        return result;
    }
}

Step 3: Handle 409 Conflicts and Implement Retry Logic

When two processes update the same agent availability concurrently, the second submission receives a 409 Conflict response because the diversion value has changed. You must implement a retry loop that re-fetches the latest state, recalculates the routing strategy, and resubmits. The following implementation caps retries at three attempts to prevent infinite loops during network partitions.

import java.time.Instant;
import java.util.concurrent.TimeUnit;

public class OptimisticLockHandler {
    private final AvailabilityFetcher fetcher;
    private final RoutingStrategyApplier applier;
    private static final int MAX_RETRIES = 3;
    private static final long RETRY_DELAY_MS = 500;

    public OptimisticLockHandler(ApiClient apiClient) {
        this.fetcher = new AvailabilityFetcher(apiClient);
        this.applier = new RoutingStrategyApplier(apiClient);
    }

    public UserAvailability updateWithLocking(String userId, String targetState, String targetWrapCode) throws Exception {
        int attempts = 0;
        
        while (attempts < MAX_RETRIES) {
            try {
                UserAvailability current = fetcher.getCurrentAvailability(userId);
                UserAvailability result = applier.applyCustomStrategy(userId, current, targetState, targetWrapCode);
                return result;
            } catch (ApiException e) {
                if (e.getCode() == 409 && attempts < MAX_RETRIES - 1) {
                    attempts++;
                    System.out.println("Optimistic lock conflict detected. Retry " + attempts + " after backoff.");
                    TimeUnit.MILLISECONDS.sleep(RETRY_DELAY_MS * attempts); // Linear backoff
                } else {
                    throw e;
                }
            }
        }
        throw new RuntimeException("Max retries exceeded for user " + userId);
    }
}

Complete Working Example

The following class integrates authentication, optimistic locking, and error handling into a single executable service. Replace the placeholder credentials and instance URL before execution.

import com.mendix.core.client.gen.client.ApiClient;
import com.mendix.core.client.gen.client.ApiException;
import com.mendix.core.client.gen.model.UserAvailability;
import java.util.concurrent.TimeUnit;

public class CustomRoutingStrategyService {
    private static final String INSTANCE_URL = "https://api.myspotinstance.com";
    private static final String CLIENT_ID = "your_client_id";
    private static final String CLIENT_SECRET = "your_client_secret";
    private static final String TARGET_USER_ID = "12345678-1234-1234-1234-123456789012";
    private static final int MAX_RETRIES = 3;
    private static final long RETRY_DELAY_MS = 500;

    public static void main(String[] args) {
        try {
            String accessToken = GenesysAuth.fetchAccessToken(CLIENT_ID, CLIENT_SECRET, "client_credentials");
            
            ApiClient apiClient = new ApiClient();
            apiClient.setBasePath(INSTANCE_URL);
            apiClient.setAccessToken(accessToken);
            
            CustomRoutingStrategyService service = new CustomRoutingStrategyService(apiClient);
            service.executeRoutingUpdate(TARGET_USER_ID, "Available", "routing:wrapupcode:priority_queue_access");
            
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    private final ApiClient apiClient;

    public CustomRoutingStrategyService(ApiClient apiClient) {
        this.apiClient = apiClient;
    }

    public void executeRoutingUpdate(String userId, String targetState, String targetWrapCode) throws Exception {
        int attempts = 0;
        
        while (attempts < MAX_RETRIES) {
            try {
                // Step 1: Fetch current availability to retrieve diversion
                UserAvailability current = apiClient.getApiClient().getApiClient() 
                    .getRoutingApi().getRoutingUserAvailability(userId);
                
                if (current.getDiversion() == null) {
                    throw new IllegalStateException("User availability diversion is null. Routing system not initialized.");
                }

                // Step 2: Prepare update payload with optimistic lock
                UserAvailability updated = new UserAvailability();
                updated.setDiversion(current.getDiversion());
                updated.setState(targetState);
                updated.setWrapUpCode(targetWrapCode);
                updated.setReason("Custom routing strategy enforcement");

                // Step 3: Submit update
                UserAvailability result = apiClient.getApiClient().getRoutingApi()
                    .postRoutingUserAvailability(userId, updated);
                
                System.out.println("Routing update successful. New diversion: " + result.getDiversion());
                return;
                
            } catch (ApiException e) {
                if (e.getCode() == 409 && attempts < MAX_RETRIES - 1) {
                    attempts++;
                    System.out.println("409 Conflict: Diversion mismatch. Retry " + attempts + " in " + (RETRY_DELAY_MS * attempts) + "ms");
                    TimeUnit.MILLISECONDS.sleep(RETRY_DELAY_MS * attempts);
                } else if (e.getCode() == 429) {
                    String retryAfter = e.getResponseHeaders().getOrDefault("Retry-After", "5");
                    long delay = Long.parseLong(retryAfter) * 1000;
                    System.out.println("429 Rate Limited. Waiting " + delay + "ms");
                    TimeUnit.MILLISECONDS.sleep(delay);
                } else {
                    throw e;
                }
            }
        }
        throw new RuntimeException("Failed to update routing strategy after " + MAX_RETRIES + " attempts.");
    }
}

Common Errors & Debugging

Error: 401 Unauthorized

  • Cause: The access token has expired, been revoked, or contains incorrect scopes. Genesys Cloud OAuth tokens expire after one hour.
  • Fix: Implement token caching with a TTL buffer (e.g., refresh at 55 minutes). Verify the OAuth client in Genesys Cloud Admin has the routing:availability:write scope enabled.
  • Code Fix: Wrap the token fetcher in a scheduler or use a token provider interface that checks Instant.now().isBefore(tokenExpiry.minusSeconds(300)) before reuse.

Error: 403 Forbidden

  • Cause: The authenticated OAuth client lacks permission to modify routing states, or the target user ID belongs to a different organization.
  • Fix: Confirm the client credentials match the organization hosting the target user. Check the OAuth client settings for the routing:availability:write scope. Verify the user ID format matches UUID standards.

Error: 409 Conflict

  • Cause: Optimistic locking failure. The diversion value submitted does not match the current server state. This occurs when Genesys Cloud internal processes, the admin console, or another integration updates the agent state concurrently.
  • Fix: Always re-fetch the availability state before retrying. Never reuse a cached diversion value across multiple update attempts. The retry loop in the complete example handles this by fetching fresh state on each attempt.

Error: 429 Too Many Requests

  • Cause: Exceeding the Genesys Cloud CX rate limits. The Routing API enforces per-organization and per-endpoint throttling.
  • Fix: Read the Retry-After header from the response. Implement exponential backoff with jitter. For bulk routing updates, queue requests and process them at a controlled throughput (e.g., 10 requests per second per user batch).

Official References