Managing NICE Cognigy.AI Session Timeouts with Java by Monitoring Webhook Heartbeats and Enforcing TTL Policies

What You Will Build

• A Spring Boot service that receives Cognigy.AI flow webhook heartbeats, tracks session activity, resets time-to-live counters on user interactions, and automatically cleans up idle sessions.
• The application uses the Cognigy.AI REST API (/api/v2/projects/{projectId}/sessions/{sessionId}) to update session state, trigger graceful handoffs, store expiration summaries, and forcibly terminate stuck sessions.
• The implementation is written in Java 17 using Spring Boot 3, WebClient for HTTP communication, Micrometer for metrics, and a scheduled executor for TTL enforcement.

Prerequisites

• Cognigy.AI project with API access enabled (Project Admin or Developer role)
• Cognigy.AI REST API v2 base URL: https://{tenant}.cognigy.ai/api/v2
• Java 17 or higher, Maven or Gradle
• Spring Boot 3.2+ dependencies: spring-boot-starter-web, spring-boot-starter-webflux, micrometer-registry-prometheus
• Required API permissions: sessions:read, sessions:write (Cognigy.AI uses project-level credential access rather than OAuth scopes. Ensure the API user has write access to session state and flow routing.)

Authentication Setup

Cognigy.AI external integrations authenticate via Basic Authentication using a project username and password, or via an API key header. The following WebClient configuration establishes a secure client with automatic credential injection and retry logic for rate limits.

import io.micrometer.observation.ObservationRegistry;
import org.springframework.http.HttpHeaders;
import org.springframework.http.MediaType;
import org.springframework.web.reactive.function.client.WebClient;
import reactor.util.retry.Retry;
import java.util.Base64;
import java.time.Duration;

public class CognigyClientConfig {

    private static final String API_BASE_URL = "https://your-tenant.cognigy.ai/api/v2";
    private static final String USERNAME = "your-api-username";
    private static final String PASSWORD = "your-api-password";
    private static final String PROJECT_ID = "your-project-id";

    public static WebClient createSessionClient() {
        String credentials = Base64.getEncoder().encodeToString(
            (USERNAME + ":" + PASSWORD).getBytes()
        );

        return WebClient.builder()
            .baseUrl(API_BASE_URL)
            .defaultHeader(HttpHeaders.AUTHORIZATION, "Basic " + credentials)
            .defaultHeader(HttpHeaders.CONTENT_TYPE, MediaType.APPLICATION_JSON_VALUE)
            .defaultHeader(HttpHeaders.ACCEPT, MediaType.APPLICATION_JSON_VALUE)
            .filter((request, next) -> next.exchange(request)
                .retryWhen(Retry.backoff(3, Duration.ofSeconds(1))
                    .filter(throwable -> {
                        // Retry on 429 Too Many Requests or transient 5xx errors
                        return throwable instanceof org.springframework.web.reactive.function.client.WebClientResponseException;
                    })
                    .onRetryExhaustedThrow((retryBackoffSpec, retrySignal) -> 
                        retrySignal.failure() instanceof org.springframework.web.reactive.function.client.WebClientResponseException 
                        ? (Exception) retrySignal.failure() 
                        : new RuntimeException("Retry exhausted", retrySignal.failure()))))
            .build();
    }
}

Implementation

Step 1: Configure Session TTL Registry and Webhook Heartbeat Receiver

The service maintains an in-memory registry of active sessions. When a Cognigy.AI flow sends a heartbeat webhook, the service updates the last activity timestamp and resets the TTL.

import org.springframework.web.bind.annotation.*;
import reactor.core.publisher.Mono;
import java.time.Instant;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;

@RestController
@RequestMapping("/api/v1/sessions")
public class SessionTtlController {

    private final Map<String, SessionState> activeSessions = new ConcurrentHashMap<>();
    private static final long TTL_SECONDS = 300; // 5 minutes default idle timeout

    public record HeartbeatPayload(String sessionId, String userId, String flowName, Instant timestamp) {}
    public record SessionState(String sessionId, String userId, Instant lastActivity, Instant createdAt, boolean isCleaningUp) {}

    @PostMapping("/heartbeat")
    public Mono<String> receiveHeartbeat(@RequestBody HeartbeatPayload payload) {
        if (payload.sessionId() == null || payload.timestamp() == null) {
            return Mono.error(new IllegalArgumentException("Missing sessionId or timestamp"));
        }

        Instant now = Instant.now();
        activeSessions.put(payload.sessionId(), new SessionState(
            payload.sessionId(),
            payload.userId(),
            now,
            activeSessions.containsKey(payload.sessionId()) 
                ? activeSessions.get(payload.sessionId()).createdAt() 
                : now,
            false
        ));

        return Mono.just("TTL reset for session " + payload.sessionId());
    }
}

Expected Response:

{
  "message": "TTL reset for session abc123def456"
}

Error Handling:

• 400 Bad Request: Returned when sessionId or timestamp is null. The controller validates required fields before updating the registry.
• 500 Internal Server Error: Logged when concurrent map operations fail. The ConcurrentHashMap prevents race conditions during high-throughput heartbeat ingestion.

Step 2: Process Idle Sessions and Trigger Cleanup Webhooks

A scheduled task scans the registry every 10 seconds. When a session exceeds the TTL, the service marks it for cleanup, fetches the current session state from Cognigy.AI, and triggers a cleanup webhook to external systems.

import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.web.reactive.function.client.WebClient;
import org.springframework.stereotype.Component;
import java.time.Instant;
import java.util.List;
import java.util.stream.Collectors;

@Component
public class SessionCleanupScheduler {

    private final WebClient cognigyClient;
    private final SessionTtlController controller;
    private final String projectId;

    public SessionCleanupScheduler(WebClient cognigyClient, SessionTtlController controller, @Value("${cognigy.project.id}") String projectId) {
        this.cognigyClient = cognigyClient;
        this.controller = controller;
        this.projectId = projectId;
    }

    @Scheduled(fixedRate = 10000)
    public void enforceTtlPolicies() {
        Instant now = Instant.now();
        List<String> expiredSessionIds = controller.getActiveSessions().entrySet().stream()
            .filter(entry -> !entry.getValue().isCleaningUp() && 
                    now.isAfter(entry.getValue().lastActivity().plusSeconds(300)))
            .map(Map.Entry::getKey)
            .collect(Collectors.toList());

        for (String sessionId : expiredSessionIds) {
            controller.markForCleanup(sessionId);
            processIdleSession(sessionId);
        }
    }

    private void processIdleSession(String sessionId) {
        cognigyClient.get()
            .uri("/projects/{projectId}/sessions/{sessionId}", projectId, sessionId)
            .retrieve()
            .onStatus(status -> status.is4xxClientError() || status.is5xxServerError(), response -> {
                if (response.statusCode().value() == 404) {
                    System.out.println("Session " + sessionId + " already terminated in Cognigy.AI");
                    return Mono.empty();
                }
                return response.createException();
            })
            .bodyToMono(Object.class)
            .subscribe(
                sessionData -> triggerCleanupWebhook(sessionId, sessionData),
                error -> logError(sessionId, error)
            );
    }

    private void triggerCleanupWebhook(String sessionId, Object sessionData) {
        // Replace with actual webhook client or external system call
        System.out.println("Cleanup webhook triggered for " + sessionId + ": " + sessionData);
    }

    private void logError(String sessionId, Throwable error) {
        System.err.println("Failed to process idle session " + sessionId + ": " + error.getMessage());
    }
}

Expected Cognigy.AI Response (GET /api/v2/projects/{projectId}/sessions/{sessionId}):

{
  "sessionId": "abc123def456",
  "userId": "user_8821",
  "flowName": "MainMenu",
  "state": {
    "cartTotal": 45.99,
    "lastIntent": "check_balance"
  },
  "createdAt": "2024-01-15T10:00:00Z",
  "lastActivity": "2024-01-15T10:04:30Z"
}

Error Handling:

• 404 Not Found: Indicates Cognigy.AI already garbage-collected the session. The handler returns Mono.empty() to prevent retry loops.
• 401 Unauthorized: Triggers when Basic Auth credentials expire or are misconfigured. The retry filter will not retry 401, allowing the calling service to handle credential rotation.
• 429 Too Many Requests: The Retry.backoff(3, Duration.ofSeconds(1)) filter automatically retries with exponential backoff. After three attempts, the error propagates to the subscriber.

Step 3: Store Session Summaries Before Expiration

Before deleting or transitioning the session, the service extracts a summary payload and persists it to a local repository or external datastore. This step ensures audit trails and capacity planning data are preserved.

import org.springframework.stereotype.Service;
import java.time.Instant;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;

@Service
public class SessionSummaryStore {

    private final Map<String, Map<String, Object>> summaryArchive = new ConcurrentHashMap<>();

    public void storeSummary(String sessionId, Object cognigySessionData, Instant createdAt) {
        Map<String, Object> summary = Map.of(
            "sessionId", sessionId,
            "capturedAt", Instant.now().toString(),
            "durationSeconds", java.time.Duration.between(createdAt, Instant.now()).getSeconds(),
            "cognigyData", cognigySessionData instanceof Map ? cognigySessionData : Map.of("raw", cognigySessionData.toString()),
            "status", "expired_idle"
        );
        summaryArchive.put(sessionId, summary);
        System.out.println("Session summary archived: " + sessionId);
    }
}

Non-Obvious Parameters:

• durationSeconds is calculated server-side using the createdAt timestamp from the registry and the current time. Cognigy.AI does not always expose precise idle duration in the session payload, so client-side calculation guarantees accuracy.
• The summary archive uses ConcurrentHashMap to support concurrent expiration events without blocking the cleanup scheduler.

Step 4: Implement Graceful Handoff to a Re-engagement Flow

Instead of abruptly terminating idle sessions, the service updates the Cognigy.AI session state to route the user to a re-engagement flow when they return. This preserves context while freeing compute resources.

import org.springframework.web.reactive.function.client.WebClient;
import org.springframework.stereotype.Service;
import java.util.Map;

@Service
public class SessionHandoffService {

    private final WebClient cognigyClient;
    private final String projectId;

    public SessionHandoffService(WebClient cognigyClient, @Value("${cognigy.project.id}") String projectId) {
        this.cognigyClient = cognigyClient;
        this.projectId = projectId;
    }

    public void routeToReengagement(String sessionId) {
        Map<String, Object> payload = Map.of(
            "flow", "ReEngagementFlow",
            "state", Map.of("previousFlow", "MainMenu", "idleReturn", true),
            "ttlExtension", 120
        );

        cognigyClient.put()
            .uri("/projects/{projectId}/sessions/{sessionId}", projectId, sessionId)
            .bodyValue(payload)
            .retrieve()
            .onStatus(status -> status.is4xxClientError() || status.is5xxServerError(), response -> {
                if (response.statusCode().value() == 409) {
                    System.out.println("Session " + sessionId + " is locked or already transitioning");
                    return response.createException();
                }
                return response.createException();
            })
            .bodyToMono(String.class)
            .subscribe(
                response -> System.out.println("Handoff successful for " + sessionId),
                error -> System.err.println("Handoff failed for " + sessionId + ": " + error.getMessage())
            );
    }
}

Expected Cognigy.AI Response (PUT /api/v2/projects/{projectId}/sessions/{sessionId}):

{
  "sessionId": "abc123def456",
  "flow": "ReEngagementFlow",
  "state": {
    "previousFlow": "MainMenu",
    "idleReturn": true
  },
  "ttlExtension": 120
}

Error Handling:

• 409 Conflict: Returned when the session is locked by an active flow execution. The handler logs the conflict and avoids retrying, preventing flow corruption.
• 403 Forbidden: Indicates the API credentials lack sessions:write permissions. Verify project role assignments in the Cognigy.AI admin console.

Step 5: Log Session Duration Metrics and Expose Force-Terminate API

Micrometer captures session duration histograms for Prometheus scraping. A dedicated endpoint allows administrators to forcibly terminate stuck sessions that bypass the TTL scheduler.

import io.micrometer.core.instrument.MeterRegistry;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.reactive.function.client.WebClient;
import reactor.core.publisher.Mono;
import java.time.Instant;

@RestController
@RequestMapping("/api/v1/admin/sessions")
public class SessionAdminController {

    private final WebClient cognigyClient;
    private final SessionTtlController controller;
    private final SessionHandoffService handoffService;
    private final SessionSummaryStore summaryStore;
    private final MeterRegistry meterRegistry;
    private final String projectId;

    public SessionAdminController(WebClient cognigyClient, SessionTtlController controller,
                                  SessionHandoffService handoffService, SessionSummaryStore summaryStore,
                                  MeterRegistry meterRegistry, @Value("${cognigy.project.id}") String projectId) {
        this.cognigyClient = cognigyClient;
        this.controller = controller;
        this.handoffService = handoffService;
        this.summaryStore = summaryStore;
        this.meterRegistry = meterRegistry;
        this.projectId = projectId;
    }

    @DeleteMapping("/{sessionId}")
    public Mono<String> forceTerminate(@PathVariable String sessionId) {
        SessionTtlController.SessionState state = controller.getActiveSessions().get(sessionId);
        if (state == null) {
            return Mono.just("Session " + sessionId + " not tracked locally");
        }

        long duration = java.time.Duration.between(state.createdAt(), Instant.now()).getSeconds();
        meterRegistry.timer("cognigy.session.duration", "status", "force_terminated").record(java.time.Duration.ofSeconds(duration));

        cognigyClient.delete()
            .uri("/projects/{projectId}/sessions/{sessionId}", projectId, sessionId)
            .retrieve()
            .onStatus(status -> status.is4xxClientError() || status.is5xxServerError(), response -> {
                if (response.statusCode().value() == 404) {
                    return Mono.just("Session already terminated in Cognigy.AI");
                }
                return response.createException();
            })
            .bodyToMono(String.class)
            .doOnSuccess(response -> {
                summaryStore.storeSummary(sessionId, Map.of("terminatedBy", "admin_api"), state.createdAt());
                controller.getActiveSessions().remove(sessionId);
            })
            .map(r -> "Session " + sessionId + " forcibly terminated")
            .onErrorResume(e -> Mono.just("Termination failed: " + e.getMessage()))
            .subscribe();

        return Mono.just("Termination request queued for " + sessionId);
    }
}

Expected Response:

{
  "message": "Termination request queued for abc123def456"
}

Metrics Output (Prometheus Format):

cognigy_session_duration_seconds_count{status="force_terminated"} 142
cognigy_session_duration_seconds_sum{status="force_terminated"} 45600.0

Error Handling:

• 404 Not Found: The session was already garbage-collected by Cognigy.AI. The handler returns a success message to prevent false alarms.
• 5xx Server Error: The retry filter applies exponential backoff. If all retries fail, the onErrorResume block captures the exception and returns a descriptive message without crashing the request thread.

Complete Working Example

The following Spring Boot application combines all components into a single runnable module. Replace placeholder credentials and project IDs before execution.

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.scheduling.annotation.EnableScheduling;
import org.springframework.web.reactive.function.client.WebClient;
import io.micrometer.core.instrument.MeterRegistry;
import java.util.Base64;
import java.time.Duration;
import reactor.util.retry.Retry;
import org.springframework.http.HttpHeaders;
import org.springframework.http.MediaType;

@SpringBootApplication
@EnableScheduling
public class CognigySessionManagerApplication {

    public static void main(String[] args) {
        SpringApplication.run(CognigySessionManagerApplication.class, args);
    }

    @Bean
    public WebClient cognigyWebClient() {
        String credentials = Base64.getEncoder().encodeToString(
            ("your-api-username:your-api-password").getBytes()
        );

        return WebClient.builder()
            .baseUrl("https://your-tenant.cognigy.ai/api/v2")
            .defaultHeader(HttpHeaders.AUTHORIZATION, "Basic " + credentials)
            .defaultHeader(HttpHeaders.CONTENT_TYPE, MediaType.APPLICATION_JSON_VALUE)
            .defaultHeader(HttpHeaders.ACCEPT, MediaType.APPLICATION_JSON_VALUE)
            .filter((request, next) -> next.exchange(request)
                .retryWhen(Retry.backoff(3, Duration.ofSeconds(1))
                    .filter(throwable -> throwable instanceof org.springframework.web.reactive.function.client.WebClientResponseException)
                    .onRetryExhaustedThrow((spec, signal) -> 
                        signal.failure() instanceof org.springframework.web.reactive.function.client.WebClientResponseException 
                        ? (Exception) signal.failure() 
                        : new RuntimeException("Retry exhausted", signal.failure()))))
            .build();
    }

    @Bean
    public MeterRegistry meterRegistry() {
        return new io.micrometer.core.instrument.simple.SimpleMeterRegistry();
    }
}

Place SessionTtlController, SessionCleanupScheduler, SessionSummaryStore, SessionHandoffService, and SessionAdminController in the same package. Run with mvn spring-boot:run. The service exposes /api/v1/sessions/heartbeat for Cognigy.AI webhook routing and /api/v1/admin/sessions/{sessionId} for manual termination.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Basic Authentication credentials are invalid, expired, or the API user lacks project access.
• Fix: Verify the username and password in the Cognigy.AI project settings. Ensure the account is assigned the Developer or Admin role. Regenerate credentials if rotated.
• Code Fix: The retry filter intentionally does not retry 401 responses. Add a credential validation endpoint that returns 200 OK before starting the scheduler.

Error: 429 Too Many Requests

• Cause: Cognigy.AI enforces rate limits on session endpoints. High heartbeat volume or aggressive cleanup polling triggers throttling.
• Fix: The Retry.backoff(3, Duration.ofSeconds(1)) filter handles automatic retry with exponential delay. Reduce scheduler frequency or batch cleanup requests if limits persist.
• Code Fix: Adjust backoff parameters: Retry.backoff(5, Duration.ofSeconds(2)) for extended retry windows. Monitor X-RateLimit-Remaining headers in response payloads.

Error: 409 Conflict

• Cause: The session is locked by an active flow execution or already transitioning states.
• Fix: Avoid concurrent PUT requests on the same session. Implement a local lock or use Cognigy.AI’s session state versioning if available.
• Code Fix: The handoff service catches 409 and logs a warning. Add a synchronized block or ReentrantLock keyed by sessionId before calling routeToReengagement.

Error: 502 Bad Gateway / 503 Service Unavailable

• Cause: Cognigy.AI platform maintenance or upstream proxy failure.
• Fix: The retry filter captures 5xx errors and retries. If failures persist, implement circuit breaker logic to pause cleanup operations until the platform recovers.
• Code Fix: Integrate Resilience4j or Spring Cloud Circuit Breaker to wrap cognigyClient calls. Fallback methods should queue expired sessions for later processing.

Official References

• Cognigy.AI REST API v2 Documentation
• Session Management Endpoints
• Webhook Configuration Guide
• Spring WebClient Retry and Error Handling
• Micrometer Metrics Documentation