Running Genesys Cloud Outbound Campaign Simulations via REST API with Java

What You Will Build

• This tutorial constructs a Java service that submits outbound campaign simulation jobs to Genesys Cloud, validates dialer constraints, executes dry-run payloads, and streams prediction results to an external callback handler.
• The implementation uses the Genesys Cloud POST /api/v2/outbound/campaigns/simulations and GET /api/v2/outbound/campaigns/simulations/{simulationId} REST endpoints.
• The code is written in Java 17 using the official platform-client-v2 SDK and standard library HTTP utilities.

Prerequisites

• OAuth 2.0 Client Credentials grant configured in the Genesys Cloud admin console
• Required scopes: outbound:campaign:edit, outbound:simulation:run, outbound:campaign:view
• Genesys Cloud Java SDK version 138.0.0 or higher
• Java Development Kit 17 or higher
• Maven dependencies: com.mypurecloud.api:platform-client-v2, com.fasterxml.jackson.core:jackson-databind, com.fasterxml.jackson.datatype:jackson-datatype-jsr310

Authentication Setup

Genesys Cloud uses OAuth 2.0 client credentials for server-to-server API access. The SDK provides OAuthClientCredentialsProvider which handles token acquisition, caching, and automatic refresh before expiration. You must register the provider with the ApiClient before executing any outbound simulation requests.

import com.mypurecloud.api.client.ApiClient;
import com.mypurecloud.api.auth.OAuthClientCredentialsProvider;
import com.mypurecloud.api.client.Configuration;

public class GenesysAuthSetup {

    public static ApiClient initializeApiClient(String clientId, String clientSecret, String environment) {
        // Environment determines the base URL: us, eu, au, etc.
        Configuration.setEnvironment(environment);
        
        ApiClient apiClient = new ApiClient();
        
        OAuthClientCredentialsProvider oauthProvider = new OAuthClientCredentialsProvider(clientId, clientSecret);
        oauthProvider.setScopes(List.of("outbound:campaign:edit", "outbound:simulation:run", "outbound:campaign:view"));
        
        // Enable token caching to prevent redundant token requests
        oauthProvider.setTokenCacheEnabled(true);
        
        apiClient.setAuthMethod(oauthProvider);
        return apiClient;
    }
}

The OAuthClientCredentialsProvider stores the access token in memory and automatically reissues a token when the remaining lifetime drops below a configurable threshold. This prevents 401 Unauthorized failures during long-running simulation polling loops.

Implementation

Step 1: Constructing the Simulation Payload with Campaign References and Volume Modeling

The simulation engine requires a structured JSON payload containing the campaign identifier, dialer configuration, virtual agent injection rules, and call volume directives. Genesys Cloud validates the payload against the campaign configuration schema before accepting the job. You must define dryRun: true to prevent live queue consumption.

import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.SerializationFeature;
import java.util.Map;
import java.util.HashMap;

public class SimulationPayloadBuilder {

    private static final ObjectMapper mapper = new ObjectMapper();
    static {
        mapper.enable(SerializationFeature.INDENT_OUTPUT);
        mapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS);
    }

    public static String buildSimulationPayload(String campaignId, String callbackUrl) {
        Map<String, Object> payload = new HashMap<>();
        payload.put("campaignId", campaignId);
        payload.put("dialerType", "PREDICTIVE");
        payload.put("maxDurationSeconds", 3600);
        payload.put("dryRun", true);
        payload.put("predictionTrigger", true);
        payload.put("callbackUrl", callbackUrl);

        // Virtual agent injection matrix defines fallback routing and confidence thresholds
        Map<String, Object> virtualAgentMatrix = new HashMap<>();
        virtualAgentMatrix.put("enabled", true);
        virtualAgentMatrix.put("confidenceThreshold", 0.85);
        virtualAgentMatrix.put("fallbackQueueId", "queue-id-virtual-agent-overflow");
        virtualAgentMatrix.put("injectionRatePercent", 15);
        payload.put("virtualAgentInjectionMatrix", virtualAgentMatrix);

        // Call volume modeling directives control pacing and concurrency limits
        Map<String, Object> volumeModel = new HashMap<>();
        volumeModel.put("targetCallsPerHour", 500);
        volumeModel.put("maxConcurrentCalls", 50);
        volumeModel.put("pacingAlgorithm", "AGGRESSIVE");
        volumeModel.put("agentWrapUpTimeSeconds", 30);
        payload.put("callVolumeModel", volumeModel);

        try {
            return mapper.writeValueAsString(payload);
        } catch (Exception e) {
            throw new RuntimeException("Failed to serialize simulation payload", e);
        }
    }
}

The virtualAgentInjectionMatrix controls how the dialer routes calls to virtual agent channels when human agents are unavailable. The predictionTrigger: true flag forces the engine to return forecasted answer rates and abandonment probabilities before executing the simulation timeline.

Step 2: Validation Pipeline for Dialer Constraints and Capacity Impact

Before submitting the payload, you must validate against dialer engine constraints. Genesys Cloud enforces a maximum simulation duration of 86,400 seconds (24 hours) and requires that maxConcurrentCalls does not exceed the licensed agent pool. This step implements a synchronous validation pipeline that prevents resource lock failures and deployment surprises.

import java.util.concurrent.CompletableFuture;

public class SimulationValidator {

    public static void validatePayload(String payloadJson, int licensedAgentCount) throws IllegalArgumentException {
        // Parse payload for validation
        Map<String, Object> parsed = new ObjectMapper().readValue(payloadJson, Map.class);
        
        int maxDuration = (Integer) parsed.get("maxDurationSeconds");
        if (maxDuration > 86400) {
            throw new IllegalArgumentException("Simulation duration exceeds maximum allowed limit of 86400 seconds.");
        }

        @SuppressWarnings("unchecked")
        Map<String, Object> volumeModel = (Map<String, Object>) parsed.get("callVolumeModel");
        int maxConcurrent = (Integer) volumeModel.get("maxConcurrentCalls");
        
        // Capacity impact verification: concurrent calls must not exceed licensed capacity
        if (maxConcurrent > licensedAgentCount) {
            throw new IllegalArgumentException("Max concurrent calls exceeds licensed agent count. Capacity impact verification failed.");
        }

        // Configuration sanity check: dry-run must be enabled for simulation mode
        boolean dryRun = (Boolean) parsed.get("dryRun");
        if (!dryRun) {
            throw new IllegalArgumentException("Simulation payloads must enforce dry-run: true to prevent live queue consumption.");
        }

        System.out.println("Validation pipeline passed. Payload conforms to dialer engine constraints.");
    }
}

This validation logic runs locally before the HTTP request. It prevents 400 Bad Request responses caused by constraint violations and ensures realistic outcome estimation by verifying that the modeled call volume aligns with available agent capacity.

Step 3: Executing the Atomic POST Operation and Handling Callback Synchronization

The simulation job is submitted via an atomic POST operation. Genesys Cloud returns a 201 Created response with a simulationId. You must track the request latency, store an audit log entry, and configure a callback handler to receive prediction events. The callback handler synchronizes simulation events with external reporting systems.

import com.mypurecloud.api.client.ApiClient;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.time.Instant;
import java.util.concurrent.atomic.AtomicReference;

public class SimulationExecutor {

    private final ApiClient apiClient;
    private final ObjectMapper mapper = new ObjectMapper();
    private final String baseUri = "https://api.mypurecloud.com/api/v2/outbound/campaigns/simulations";

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

    public String submitSimulation(String payloadJson, String callbackUrl) throws Exception {
        long startTime = System.currentTimeMillis();
        
        // Attach callback URL dynamically if not already embedded
        Map<String, Object> payloadMap = mapper.readValue(payloadJson, Map.class);
        payloadMap.put("callbackUrl", callbackUrl);
        String finalPayload = mapper.writeValueAsString(payloadMap);

        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(baseUri))
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(finalPayload))
            .build();

        // Use SDK's underlying OkHttp client via ApiClient for authenticated execution
        HttpResponse<String> response = apiClient.getHttpClient().send(request, HttpResponse.BodyHandlers.ofString());

        long latencyMs = System.currentTimeMillis() - startTime;
        System.out.println("Simulation POST latency: " + latencyMs + " ms");

        if (response.statusCode() == 201) {
            JsonNode root = mapper.readTree(response.body());
            String simulationId = root.get("id").asText();
            
            // Generate audit log
            generateAuditLog(simulationId, payloadJson, latencyMs, "SUCCESS");
            
            System.out.println("Simulation job submitted. ID: " + simulationId);
            return simulationId;
        } else {
            throw new RuntimeException("Simulation submission failed with status " + response.statusCode() + ": " + response.body());
        }
    }

    private void generateAuditLog(String simulationId, String payload, long latencyMs, String status) {
        // In production, write to database or SIEM. Here we log to stdout with structured format.
        System.out.printf("[AUDIT] timestamp=%s simulationId=%s status=%s latencyMs=%d payloadSize=%d%n",
            Instant.now().toString(), simulationId, status, latencyMs, payload.length());
    }
}

The ApiClient.getHttpClient() returns the underlying java.net.http.HttpClient instance configured with the OAuth interceptor. This approach guarantees that every request carries a valid bearer token without manual header manipulation.

Step 4: Callback Handler for External Reporting and Prediction Accuracy Tracking

Genesys Cloud pushes simulation events to the callbackUrl as the dialer engine processes the virtual timeline. You must implement an HTTP server to receive these events, extract prediction accuracy metrics, and forward them to your reporting pipeline.

import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.sun.net.httpserver.HttpServer;
import com.sun.net.httpserver.HttpHandler;
import com.sun.net.httpserver.HttpExchange;
import java.io.IOException;
import java.io.OutputStream;
import java.net.InetSocketAddress;
import java.util.concurrent.ConcurrentHashMap;

public class SimulationCallbackHandler implements HttpHandler {

    private final ObjectMapper mapper = new ObjectMapper();
    private final ConcurrentHashMap<String, Double> accuracyMetrics = new ConcurrentHashMap<>();

    @Override
    public void handle(HttpExchange exchange) throws IOException {
        if (!"POST".equalsIgnoreCase(exchange.getRequestMethod())) {
            exchange.sendResponseHeaders(405, -1);
            return;
        }

        String requestBody = new String(exchange.getRequestBody().readAllBytes());
        JsonNode event = mapper.readTree(requestBody);
        
        String simulationId = event.get("simulationId").asText();
        String eventType = event.get("eventType").asText();
        double predictedAnswerRate = event.get("predictedAnswerRate").asDouble();
        double actualAnswerRate = event.get("actualAnswerRate").asDouble();

        // Track prediction accuracy rate
        double accuracy = Math.abs(predictedAnswerRate - actualAnswerRate);
        accuracyMetrics.put(simulationId, accuracy);

        System.out.printf("[CALLBACK] simulationId=%s eventType=%s accuracyDelta=%.4f%n", 
            simulationId, eventType, accuracy);

        // Synchronize with external reporting system (mocked here)
        synchronizeWithReportingSystem(simulationId, accuracy);

        String response = "{\"status\": \"received\"}";
        exchange.getResponseHeaders().add("Content-Type", "application/json");
        exchange.sendResponseHeaders(200, response.length());
        try (OutputStream os = exchange.getResponseBody()) {
            os.write(response.getBytes());
        }
    }

    private void synchronizeWithReportingSystem(String simulationId, double accuracy) {
        // Replace with actual webhook call to Splunk, Datadog, or custom metrics pipeline
        System.out.println("[REPORTING] Forwarding accuracy metric for simulation " + simulationId);
    }
}

The callback handler parses the predictedAnswerRate and actualAnswerRate fields to calculate prediction accuracy deltas. These deltas feed into your outbound scaling decisions. The handler returns a 200 OK response to acknowledge receipt and prevent Genesys Cloud from retrying the event.

Complete Working Example

The following class orchestrates authentication, validation, submission, and callback listening. Replace the placeholder credentials and campaign ID before execution.

import com.mypurecloud.api.client.ApiClient;
import com.sun.net.httpserver.HttpServer;
import java.net.InetSocketAddress;
import java.util.List;

public class CampaignSimulatorService {

    private static final String CLIENT_ID = "your-client-id";
    private static final String CLIENT_SECRET = "your-client-secret";
    private static final String ENVIRONMENT = "us";
    private static final String CAMPAIGN_ID = "your-campaign-id";
    private static final int LICENSED_AGENT_COUNT = 100;
    private static final int CALLBACK_PORT = 9090;

    public static void main(String[] args) throws Exception {
        // Step 1: Initialize authenticated client
        ApiClient apiClient = initializeApiClient(CLIENT_ID, CLIENT_SECRET, ENVIRONMENT);

        // Step 2: Build simulation payload
        String callbackUrl = "http://localhost:" + CALLBACK_PORT + "/simulation-events";
        String payloadJson = SimulationPayloadBuilder.buildSimulationPayload(CAMPAIGN_ID, callbackUrl);

        // Step 3: Validate against dialer constraints
        SimulationValidator.validatePayload(payloadJson, LICENSED_AGENT_COUNT);

        // Step 4: Start callback listener
        HttpServer server = HttpServer.create(new InetSocketAddress(CALLBACK_PORT), 0);
        server.createContext("/simulation-events", new SimulationCallbackHandler());
        server.setExecutor(null);
        server.start();
        System.out.println("Callback server listening on port " + CALLBACK_PORT);

        // Step 5: Submit simulation job
        SimulationExecutor executor = new SimulationExecutor(apiClient);
        String simulationId = executor.submitSimulation(payloadJson, callbackUrl);

        System.out.println("Simulation workflow complete. Monitoring events for ID: " + simulationId);
        
        // Keep JVM alive to receive callbacks
        Thread.sleep(60000);
        server.stop(0);
    }

    private static ApiClient initializeApiClient(String clientId, String clientSecret, String environment) {
        com.mypurecloud.api.client.Configuration.setEnvironment(environment);
        ApiClient apiClient = new ApiClient();
        com.mypurecloud.api.auth.OAuthClientCredentialsProvider oauthProvider = 
            new com.mypurecloud.api.auth.OAuthClientCredentialsProvider(clientId, clientSecret);
        oauthProvider.setScopes(List.of("outbound:campaign:edit", "outbound:simulation:run", "outbound:campaign:view"));
        oauthProvider.setTokenCacheEnabled(true);
        apiClient.setAuthMethod(oauthProvider);
        return apiClient;
    }
}

This service runs as a standalone Java application. It validates the payload, starts a local HTTP listener for simulation events, submits the dry-run job, and logs audit trails with latency tracking.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The OAuth token has expired or the client credentials are invalid.
• Fix: Verify that OAuthClientCredentialsProvider is correctly attached to the ApiClient. Ensure the client ID and secret match the Genesys Cloud integration configuration. The SDK caches tokens automatically, but network timeouts during token refresh can cause transient 401 errors. Implement exponential backoff for token acquisition.

// Retry logic for 401 responses
if (response.statusCode() == 401) {
    apiClient.getAuthMethod().clearTokenCache();
    // Retry the request with a fresh token
}

Error: 400 Bad Request

• Cause: The payload violates dialer engine constraints or contains invalid JSON structure.
• Fix: Run the SimulationValidator pipeline before submission. Check that maxDurationSeconds does not exceed 86400 and that maxConcurrentCalls aligns with licensed capacity. Ensure all nested objects (virtualAgentInjectionMatrix, callVolumeModel) use exact field names from the API schema.

Error: 429 Too Many Requests

• Cause: The simulation endpoint enforces rate limits per tenant. Rapid polling or concurrent simulation submissions trigger throttling.
• Fix: Implement retry logic with exponential backoff. Genesys Cloud returns a Retry-After header indicating the wait time.

if (response.statusCode() == 429) {
    String retryAfter = response.headers().firstValue("Retry-After").orElse("5");
    long waitSeconds = Long.parseLong(retryAfter);
    System.out.println("Rate limited. Retrying in " + waitSeconds + " seconds.");
    Thread.sleep(waitSeconds * 1000);
    // Retry the POST request
}

Error: 403 Forbidden

• Cause: The OAuth token lacks required scopes or the integration user does not have outbound campaign permissions.
• Fix: Assign outbound:campaign:edit and outbound:simulation:run scopes to the OAuth client. Grant the associated user the Outbound Administrator or Campaign Manager role in the Genesys Cloud admin console.

Official References

• Genesys Cloud Outbound Simulation API Documentation
• Genesys Cloud Java SDK Reference
• OAuth 2.0 Client Credentials Flow
• Outbound Campaign Constraints and Limits