Archiving Genesys Cloud Interactions via REST API with Java

What You Will Build

A Java utility that constructs and submits archiving payloads for Pure Cloud interactions, validates schema constraints against storage limits, executes atomic POST operations, monitors job completion, and emits audit logs and webhook callbacks. This uses the Genesys Cloud Archiving API and the official genesyscloud-java-sdk. The tutorial covers Java 17.

Prerequisites

• OAuth2 Client Credentials flow configured in Genesys Cloud
• Required scopes: archiving:archiving:create, archiving:archiving:read, archiving:archiving:export
• Genesys Cloud Java SDK v10+ (com.mypurecloud.api.client)
• Java 17+ runtime
• Dependencies: com.google.code.gson:gson, org.slf4j:slf4j-api
• Access to a Genesys Cloud environment with archiving enabled

Authentication Setup

Genesys Cloud requires a bearer token for all API calls. The following code fetches a client credentials token and configures the SDK client. Token caching is handled by storing the token and expiry timestamp, with automatic refresh upon expiration.

import com.google.gson.JsonObject;
import com.google.gson.JsonParser;
import com.mypurecloud.api.client.ApiClient;
import com.mypurecloud.api.client.Configuration;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.nio.charset.StandardCharsets;
import java.time.Instant;
import java.util.Base64;

public class AuthManager {
    private String accessToken;
    private Instant tokenExpiry;

    public ApiClient initializeApiClient(String clientId, String clientSecret, String envId) throws Exception {
        fetchToken(clientId, clientSecret, envId);
        
        Configuration config = new Configuration();
        config.setBasePath("https://api.mypurecloud.com");
        config.setApiKey("Authorization", "Bearer " + accessToken);
        
        ApiClient apiClient = new ApiClient(config);
        apiClient.setDebugging(false);
        return apiClient;
    }

    private void fetchToken(String clientId, String clientSecret, String envId) throws Exception {
        if (accessToken != null && Instant.now().isBefore(tokenExpiry.minusSeconds(60))) {
            return;
        }

        HttpClient client = HttpClient.newHttpClient();
        String credentials = Base64.getEncoder().encodeToString((clientId + ":" + clientSecret).getBytes(StandardCharsets.UTF_8));
        
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create("https://login.mypurecloud.com/oauth/token"))
            .header("Content-Type", "application/x-www-form-urlencoded")
            .header("Authorization", "Basic " + credentials)
            .POST(HttpRequest.BodyPublishers.ofString("grant_type=client_credentials&env_id=" + envId))
            .build();

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

        JsonObject json = JsonParser.parseString(response.body()).getAsJsonObject();
        accessToken = json.get("access_token").getAsString();
        int expiresIn = json.get("expires_in").getAsInt();
        tokenExpiry = Instant.now().plusSeconds(expiresIn);
    }
}

Implementation

Step 1: Construct Archive Payloads with Retention and Compression Directives

The Archiving API accepts a structured request containing query filters, retention policies, and export settings. You must define the interaction scope, retention duration, and compression level before submission. The SDK models map directly to the JSON schema.

import com.mypurecloud.api.client.model.*;
import com.mypurecloud.api.client.api.ArchivingApi;
import com.mypurecloud.api.client.ApiException;
import java.util.List;

public class ArchivePayloadBuilder {
    
    public ArchivingRequest buildRequest(String[] interactionIds, String retentionPolicy, int retentionDays) {
        // Construct query with interaction ID references
        ArchivingQuery query = new ArchivingQuery();
        query.setDateRange(new DateRange().type("absolute").from("-P30D").to("now"));
        
        // Filter by specific interaction IDs
        query.setFilters(List.of(
            new Filter().type("interactionId").values(List.of(interactionIds))
        ));
        
        // Configure retention matrix
        ArchivingRetention retention = new ArchivingRetention();
        retention.setPolicyType(retentionPolicy);
        retention.setDeleteAfterDays(retentionDays);
        
        // Configure compression and export limits
        ArchivingExport export = new ArchivingExport();
        export.setFormat("json");
        export.setCompression("gzip");
        export.setMaxSizeBytes(5368709120L); // 5GB limit
        
        // Assemble final request
        ArchivingRequest request = new ArchivingRequest();
        request.setQuery(query);
        request.setRetention(retention);
        request.setExport(export);
        request.setArchiveSettings(new ArchivingSettings()
            .includeInteractionData(true)
            .includeParticipantData(true)
            .includeQueueData(false));
            
        return request;
    }
}

Expected Request Body:

{
  "query": {
    "dateRange": { "type": "absolute", "from": "-P30D", "to": "now" },
    "filters": [ { "type": "interactionId", "values": ["a1b2c3d4-5678-90ab-cdef-1234567890ab"] } ]
  },
  "retention": { "policyType": "custom", "deleteAfterDays": 365 },
  "export": { "format": "json", "compression": "gzip", "maxSizeBytes": 5368709120 },
  "archiveSettings": { "includeInteractionData": true, "includeParticipantData": true, "includeQueueData": false }
}

Step 2: Validate Schema and Execute Atomic POST Operations

Before submitting the job, you must validate the query against backend constraints. Genesys Cloud limits archive jobs by record count and storage size. Use the query validation endpoint to verify the payload will not exceed maximum archive size limits. Then execute the atomic POST with retry logic for rate limiting.

public class ArchiveExecutor {
    private final ArchivingApi archivingApi;
    private static final int MAX_RETRIES = 3;

    public ArchiveExecutor(ApiClient apiClient) {
        this.archivingApi = new ArchivingApi(apiClient);
    }

    public Archiving submitArchiveJob(ArchivingRequest request) throws ApiException, InterruptedException {
        // Step 2A: Pre-flight validation against storage constraints
        validateQueryLimits(request);
        
        // Step 2B: Atomic POST with exponential backoff for 429
        int attempt = 0;
        while (attempt < MAX_RETRIES) {
            try {
                return archivingApi.postArchivings(request);
            } catch (ApiException e) {
                if (e.getCode() == 429 && attempt < MAX_RETRIES - 1) {
                    long delay = (long) Math.pow(2, attempt) * 1000;
                    Thread.sleep(delay);
                    attempt++;
                } else {
                    throw e;
                }
            }
        }
        throw new RuntimeException("Archive job submission failed after " + MAX_RETRIES + " retries");
    }

    private void validateQueryLimits(ArchivingRequest request) throws ApiException {
        // POST /api/v2/archivings/queries validates the filter set without creating a job
        ArchivingQueryResult result = archivingApi.postArchivingsQueries(request.getQuery());
        
        if (result.getMatchedCount() == null || result.getMatchedCount() == 0) {
            throw new IllegalStateException("Query matched zero interactions. Archive job will not generate data.");
        }
        
        // Enforce maximum archive size limits based on estimated record size
        long estimatedBytes = result.getMatchedCount() * 256 * 1024; // 256KB per interaction estimate
        if (estimatedBytes > request.getExport().getMaxSizeBytes()) {
            throw new IllegalStateException("Estimated archive size exceeds maximum limit. Reduce date range or filters.");
        }
    }
}

Step 3: Monitor Job Status, Trigger Index Rebuild Verification, and Emit Callbacks

Archiving jobs run asynchronously. You must poll the status endpoint until the job completes. Upon completion, Genesys Cloud automatically triggers index rebuilding. Verify index readiness by checking the status, then emit a webhook callback to synchronize with external data warehouses. Track latency for storage efficiency metrics.

import com.mypurecloud.api.client.model.Archiving;
import java.time.Duration;
import java.time.Instant;
import java.util.function.Consumer;

public class ArchiveMonitor {
    private final ArchivingApi archivingApi;
    private final Consumer<Archiving> webhookCallback;
    private final AuditLogger auditLogger;

    public ArchiveMonitor(ApiClient apiClient, Consumer<Archiving> webhookCallback, AuditLogger auditLogger) {
        this.archivingApi = new ArchivingApi(apiClient);
        this.webhookCallback = webhookCallback;
        this.auditLogger = auditLogger;
    }

    public Archiving waitForCompletion(String archivingId) throws ApiException, InterruptedException {
        Instant startTime = Instant.now();
        Archiving currentJob = null;
        
        while (true) {
            currentJob = archivingApi.getArchivingsArchivingId(archivingId);
            String status = currentJob.getStatus();
            
            if ("completed".equals(status)) {
                Instant endTime = Instant.now();
                long latencyMs = Duration.between(startTime, endTime).toMillis();
                
                auditLogger.logArchiveCompletion(archivingId, latencyMs, currentJob.getExport().getTotalBytes());
                webhookCallback.accept(currentJob);
                return currentJob;
            }
            
            if ("failed".equals(status)) {
                auditLogger.logArchiveFailure(archivingId, currentJob.getErrors());
                throw new RuntimeException("Archive job failed: " + currentJob.getErrors());
            }
            
            Thread.sleep(5000); // Poll every 5 seconds
        }
    }
}

Step 4: Query Performance Verification Pipeline

After index rebuilding completes, verify historical data accessibility and prevent search degradation. Run a verification query against the archived dataset to confirm retrieval speed rates and schema compatibility.

import com.mypurecloud.api.client.model.ArchivingQueryResult;
import java.time.Instant;

public class ArchiveVerifier {
    private final ArchivingApi archivingApi;
    private final AuditLogger auditLogger;

    public ArchiveVerifier(ApiClient apiClient, AuditLogger auditLogger) {
        this.archivingApi = new ArchivingApi(apiClient);
        this.auditLogger = auditLogger;
    }

    public void verifyArchiveAccessibility(String archivingId) throws ApiException {
        // Retrieve the original query from the completed job
        Archiving job = archivingApi.getArchivingsArchivingId(archivingId);
        
        // Run verification query to test index performance
        Instant queryStart = Instant.now();
        ArchivingQueryResult result = archivingApi.postArchivingsQueries(job.getQuery());
        Instant queryEnd = Instant.now();
        
        long retrievalSpeedMs = Duration.between(queryStart, queryEnd).toMillis();
        
        auditLogger.logQueryPerformance(archivingId, retrievalSpeedMs, result.getMatchedCount());
        
        if (result.getMatchedCount() < 1) {
            throw new IllegalStateException("Archive verification failed: zero records returned after index rebuild.");
        }
        
        auditLogger.logAuditEvent("ARCHIVE_VERIFIED", archivingId, "Schema compatible and index accessible");
    }
}

Complete Working Example

import com.google.gson.Gson;
import com.mypurecloud.api.client.ApiClient;
import com.mypurecloud.api.client.api.ArchivingApi;
import com.mypurecloud.api.client.model.Archiving;
import com.mypurecloud.api.client.model.ArchivingRequest;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.function.Consumer;

public class InteractionArchiver {
    private static final Logger logger = LoggerFactory.getLogger(InteractionArchiver.class);
    private static final Gson gson = new Gson();

    public static void main(String[] args) {
        try {
            // 1. Authentication
            AuthManager authManager = new AuthManager();
            ApiClient apiClient = authManager.initializeApiClient("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET", "YOUR_ENV_ID");
            
            // 2. Build Payload
            ArchivePayloadBuilder builder = new ArchivePayloadBuilder();
            ArchivingRequest request = builder.buildRequest(
                new String[]{"a1b2c3d4-5678-90ab-cdef-1234567890ab"},
                "custom",
                365
            );
            
            // 3. Execute Atomic POST
            ArchiveExecutor executor = new ArchiveExecutor(apiClient);
            Archiving job = executor.submitArchiveJob(request);
            String archivingId = job.getId();
            
            logger.info("Archive job created: {}", archivingId);
            
            // 4. Monitor and Callback
            AuditLogger auditLogger = new AuditLogger();
            Consumer<Archiving> warehouseSyncCallback = (completedJob) -> {
                logger.info("Webhook sync triggered for archive: {}. Exported bytes: {}", 
                    completedJob.getId(), completedJob.getExport().getTotalBytes());
            };
            
            ArchiveMonitor monitor = new ArchiveMonitor(apiClient, warehouseSyncCallback, auditLogger);
            monitor.waitForCompletion(archivingId);
            
            // 5. Verify Index and Schema
            ArchiveVerifier verifier = new ArchiveVerifier(apiClient, auditLogger);
            verifier.verifyArchiveAccessibility(archivingId);
            
            logger.info("Archive workflow completed successfully for: {}", archivingId);
            
        } catch (Exception e) {
            logger.error("Archive workflow failed", e);
        }
    }
}

class AuditLogger {
    private static final Logger logger = LoggerFactory.getLogger(AuditLogger.class);
    
    public void logArchiveCompletion(String id, long latencyMs, Long bytes) {
        logger.info("AUDIT|ARCHIVE_COMPLETE|id={}|latencyMs={}|bytes={}", id, latencyMs, bytes);
    }
    
    public void logArchiveFailure(String id, String errors) {
        logger.error("AUDIT|ARCHIVE_FAILURE|id={}|errors={}", id, errors);
    }
    
    public void logQueryPerformance(String id, long retrievalSpeedMs, Long matchedCount) {
        logger.info("AUDIT|QUERY_PERFORMANCE|id={}|retrievalSpeedMs={}|matchedCount={}", id, retrievalSpeedMs, matchedCount);
    }
    
    public void logAuditEvent(String event, String id, String details) {
        logger.info("AUDIT|{}|id={}|details={}", event, id, details);
    }
}

Common Errors & Debugging

Error: 400 Bad Request (Query Validation Failed)

• What causes it: The date range is invalid, filters reference non-existent interaction types, or the query exceeds maximum complexity limits.
• How to fix it: Validate the ArchivingQuery object before submission. Ensure date ranges use ISO 8601 duration format (P30D, PT24H). Verify interaction IDs exist in the target environment.
• Code showing the fix:

if (request.getQuery().getDateRange().getFrom() == null) {
    throw new IllegalArgumentException("Date range 'from' must be specified in ISO 8601 format.");
}

Error: 429 Too Many Requests (Rate Limit Cascade)

• What causes it: Exceeding the Genesys Cloud API rate limit for archiving operations. The platform enforces strict quotas on archive job creation.
• How to fix it: Implement exponential backoff. The ArchiveExecutor already includes retry logic. Adjust poll intervals in ArchiveMonitor if submitting multiple jobs concurrently.
• Code showing the fix:

catch (ApiException e) {
    if (e.getCode() == 429) {
        String retryAfter = e.getResponseHeaders().getFirst("Retry-After");
        long delay = retryAfter != null ? Long.parseLong(retryAfter) * 1000 : 2000L;
        Thread.sleep(delay);
    }
}

Error: 500 Internal Server Error (Storage Backend Constraint)

• What causes it: The archive job exceeds backend storage capacity, compression fails, or the retention policy conflicts with environment quotas.
• How to fix it: Reduce maxSizeBytes in the export configuration. Switch compression from gzip to none temporarily to isolate storage issues. Verify the retention deleteAfterDays aligns with organizational data governance limits.
• Code showing the fix:

export.setMaxSizeBytes(2684354560L); // Reduce to 2.5GB
export.setCompression("none"); // Disable compression for debugging

Official References

• Genesys Cloud Archiving API Documentation
• Java SDK Reference
• OAuth2 Client Credentials Flow
• Archive Query Validation Endpoint