Monitoring NICE Cognigy Bot Health via REST API with TypeScript

What You Will Build

You will build a TypeScript health monitoring service that polls NICE Cognigy bot metrics, validates check configurations against engine constraints, calculates uptime and error rates, triggers webhook alerts on threshold breaches, and maintains structured audit logs for compliance. The code uses Cognigy REST endpoints for authentication, bot status retrieval, and conversation analytics. The implementation covers Node.js 18+ with native TypeScript fetch capabilities.

Prerequisites

• Cognigy OAuth2 client credentials (client ID and client secret) with bot:read and analytics:read scopes
• Cognigy API base URL format: https://{customer}.cognigy.com/api/v3
• Node.js 18 or higher
• TypeScript 5.0 or higher
• npm install typescript @types/node
• No external HTTP libraries required (native fetch is used)

Authentication Setup

Cognigy uses OAuth2 client credentials flow. You must request an access token before invoking any API endpoint. The token expires after a fixed duration and requires renewal.

// auth.ts
export interface CognigyAuthConfig {
  baseUrl: string;
  clientId: string;
  clientSecret: string;
}

export interface CognigyTokenResponse {
  access_token: string;
  token_type: string;
  expires_in: number;
  scope: string;
}

export async function cognigyAuthenticate(config: CognigyAuthConfig): Promise<CognigyTokenResponse> {
  const tokenUrl = `${config.baseUrl.replace(/\/api\/v3$/, '')}/oauth/token`;
  
  const formData = new URLSearchParams({
    grant_type: 'client_credentials',
    client_id: config.clientId,
    client_secret: config.clientSecret,
    scope: 'bot:read analytics:read'
  });

  const response = await fetch(tokenUrl, {
    method: 'POST',
    headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
    body: formData
  });

  if (!response.ok) {
    const errorBody = await response.text();
    throw new Error(`OAuth authentication failed (${response.status}): ${errorBody}`);
  }

  return response.json();
}

The required OAuth scopes are bot:read for retrieving bot metadata and analytics:read for accessing conversation metrics. Store the expires_in value to schedule token refresh before expiration.

Implementation

Step 1: Health Payload Construction and Constraint Validation

The monitoring engine requires structured health check configurations. You will construct payloads containing bot ID references, check type matrices, and threshold alert directives. The validator enforces schema compliance and maximum check frequency limits to prevent 429 rate limit cascades.

// health-config.ts
export type CheckType = 'latency' | 'error_rate' | 'uptime' | 'throughput';

export interface ThresholdDirective {
  metric: CheckType;
  operator: 'gte' | 'lte' | 'eq';
  value: number;
  severity: 'warning' | 'critical';
}

export interface HealthCheckMatrix {
  botId: string;
  checkTypes: CheckType[];
  thresholds: ThresholdDirective[];
  intervalSeconds: number;
}

export interface EngineConstraints {
  minIntervalSeconds: number;
  maxConcurrentChecks: number;
  allowedCheckTypes: CheckType[];
}

export function validateHealthPayload(
  payload: HealthCheckMatrix,
  constraints: EngineConstraints
): void {
  if (payload.intervalSeconds < constraints.minIntervalSeconds) {
    throw new Error(`Interval ${payload.intervalSeconds}s violates minimum constraint ${constraints.minIntervalSeconds}s`);
  }

  const invalidTypes = payload.checkTypes.filter(
    t => !constraints.allowedCheckTypes.includes(t)
  );
  if (invalidTypes.length > 0) {
    throw new Error(`Invalid check types requested: ${invalidTypes.join(', ')}`);
  }

  payload.thresholds.forEach((t, idx) => {
    if (!payload.checkTypes.includes(t.metric)) {
      throw new Error(`Threshold at index ${idx} references metric ${t.metric} not in checkTypes matrix`);
    }
    if (!['gte', 'lte', 'eq'].includes(t.operator)) {
      throw new Error(`Invalid threshold operator: ${t.operator}`);
    }
  });
}

This step guarantees that every health check configuration aligns with monitoring engine constraints before execution. The validator rejects malformed matrices, enforces minimum polling intervals, and verifies threshold metric references.

Step 2: Atomic Health Assessment and Metric Calculation

You will perform atomic GET operations against Cognigy endpoints to retrieve bot status and conversation analytics. The code verifies response formats, calculates uptime verification flags, and computes error rate pipelines. Retry logic handles 429 responses with exponential backoff.

// health-assessment.ts
import { CognigyTokenResponse } from './auth';

export interface BotStatusResponse {
  id: string;
  name: string;
  status: 'active' | 'inactive' | 'draft';
  lastDeployed: string;
}

export interface AnalyticsResponse {
  totalConversations: number;
  failedConversations: number;
  avgResponseTimeMs: number;
  periodStart: string;
  periodEnd: string;
}

export interface HealthAssessmentResult {
  botId: string;
  timestamp: string;
  isOnline: boolean;
  uptimeVerification: boolean;
  errorRate: number;
  avgLatencyMs: number;
  thresholdBreaches: string[];
}

async function fetchWithRetry<T>(
  url: string,
  token: string,
  retries = 3
): Promise<T> {
  for (let attempt = 1; attempt <= retries; attempt++) {
    const response = await fetch(url, {
      headers: {
        'Authorization': `Bearer ${token}`,
        'Accept': 'application/json'
      }
    });

    if (response.status === 429) {
      const retryAfter = response.headers.get('Retry-After') || Math.pow(2, attempt);
      await new Promise(r => setTimeout(r, parseInt(retryAfter, 10) * 1000));
      continue;
    }

    if (!response.ok) {
      throw new Error(`API request failed (${response.status}): ${response.statusText}`);
    }

    return response.json();
  }
  throw new Error('Max retries exceeded for 429 rate limit');
}

export async function assessBotHealth(
  baseUrl: string,
  token: string,
  config: HealthCheckMatrix
): Promise<HealthAssessmentResult> {
  const botUrl = `${baseUrl}/bots/${config.botId}`;
  const analyticsUrl = `${baseUrl}/analytics/conversations?botId=${config.botId}&period=7d`;

  const [botStatus, analytics] = await Promise.all([
    fetchWithRetry<BotStatusResponse>(botUrl, token),
    fetchWithRetry<AnalyticsResponse>(analyticsUrl, token)
  ]);

  const isOnline = botStatus.status === 'active';
  const uptimeVerification = isOnline && botStatus.lastDeployed !== undefined;
  const errorRate = analytics.totalConversations > 0
    ? analytics.failedConversations / analytics.totalConversations
    : 0;

  const breaches: string[] = [];
  config.thresholds.forEach(threshold => {
    let current = 0;
    if (threshold.metric === 'error_rate') current = errorRate;
    if (threshold.metric === 'latency') current = analytics.avgResponseTimeMs;
    if (threshold.metric === 'uptime') current = uptimeVerification ? 1 : 0;

    const breached = threshold.operator === 'gte' ? current >= threshold.value :
                     threshold.operator === 'lte' ? current <= threshold.value :
                     current === threshold.value;
    if (breached) breaches.push(`${threshold.metric}:${threshold.severity}`);
  });

  return {
    botId: config.botId,
    timestamp: new Date().toISOString(),
    isOnline,
    uptimeVerification,
    errorRate,
    avgLatencyMs: analytics.avgResponseTimeMs,
    thresholdBreaches: breaches
  };
}

The Promise.all call executes atomic GET operations. The retry loop intercepts 429 responses and applies exponential backoff. The error rate pipeline divides failed conversations by total conversations. Uptime verification confirms active status and deployment timestamp presence.

Step 3: Alert Escalation and Webhook Synchronization

When threshold breaches occur, the monitor escalates alerts to external systems via webhook callbacks. The code tracks health latency, alert accuracy rates, and synchronizes events with configurable endpoints.

// alert-escalation.ts
import { HealthAssessmentResult } from './health-assessment';

export interface WebhookConfig {
  url: string;
  apiKey: string;
}

export interface AlertPayload {
  botId: string;
  timestamp: string;
  severity: 'warning' | 'critical';
  breaches: string[];
  metrics: {
    errorRate: number;
    avgLatencyMs: number;
    uptimeVerification: boolean;
  };
  accuracyContext: {
    totalAlerts: number;
    confirmedAlerts: number;
    accuracyRate: number;
  };
}

export class AlertSynchronizer {
  private totalAlerts = 0;
  private confirmedAlerts = 0;
  private webhookConfig: WebhookConfig;

  constructor(config: WebhookConfig) {
    this.webhookConfig = config;
  }

  async escalate(assessment: HealthAssessmentResult): Promise<void> {
    if (assessment.thresholdBreaches.length === 0) return;

    this.totalAlerts++;
    const severity = assessment.thresholdBreaches.includes('critical')
      ? 'critical'
      : 'warning';

    const payload: AlertPayload = {
      botId: assessment.botId,
      timestamp: assessment.timestamp,
      severity,
      breaches: assessment.thresholdBreaches,
      metrics: {
        errorRate: assessment.errorRate,
        avgLatencyMs: assessment.avgLatencyMs,
        uptimeVerification: assessment.uptimeVerification
      },
      accuracyContext: {
        totalAlerts: this.totalAlerts,
        confirmedAlerts: this.confirmedAlerts,
        accuracyRate: this.totalAlerts > 0 ? this.confirmedAlerts / this.totalAlerts : 0
      }
    };

    const start = Date.now();
    const response = await fetch(this.webhookConfig.url, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        'X-API-Key': this.webhookConfig.apiKey,
        'X-Source': 'cognigy-health-monitor'
      },
      body: JSON.stringify(payload)
    });

    const latency = Date.now() - start;
    console.log(`Webhook delivered in ${latency}ms (${response.status})`);

    if (response.ok) {
      this.confirmedAlerts++;
    } else {
      const errorText = await response.text();
      throw new Error(`Webhook escalation failed (${response.status}): ${errorText}`);
    }
  }

  getAccuracyMetrics() {
    return {
      totalAlerts: this.totalAlerts,
      confirmedAlerts: this.confirmedAlerts,
      accuracyRate: this.totalAlerts > 0 ? this.confirmedAlerts / this.totalAlerts : 0
    };
  }
}

The synchronizer tracks alert accuracy by comparing total alerts against confirmed webhook deliveries. Latency measurement uses Date.now() before and after the POST request. The X-Source header enables external systems to route and prioritize incoming health events.

Step 4: Audit Logging and Monitor Exposure

You will generate structured health audit logs for operational compliance and expose a unified monitor interface for automated bot management. The logger records every assessment, validation, and escalation event with timestamps and outcome codes.

// audit-logger.ts
export interface AuditLogEntry {
  timestamp: string;
  event: 'validation' | 'assessment' | 'escalation' | 'error';
  botId: string;
  status: 'success' | 'failure' | 'warning';
  details: string;
  latencyMs?: number;
}

export class AuditLogger {
  private logs: AuditLogEntry[] = [];

  log(entry: AuditLogEntry): void {
    this.logs.push(entry);
    console.log(JSON.stringify(entry));
  }

  exportLogs(): AuditLogEntry[] {
    return [...this.logs];
  }
}

// monitor.ts
import { cognigyAuthenticate } from './auth';
import { validateHealthPayload } from './health-config';
import { assessBotHealth } from './health-assessment';
import { AlertSynchronizer } from './alert-escalation';
import { AuditLogger } from './audit-logger';

export interface MonitorConfig {
  cognigy: {
    baseUrl: string;
    clientId: string;
    clientSecret: string;
  };
  health: {
    botId: string;
    checkTypes: Array<'latency' | 'error_rate' | 'uptime' | 'throughput'>;
    thresholds: Array<{ metric: string; operator: 'gte' | 'lte' | 'eq'; value: number; severity: 'warning' | 'critical' }>;
    intervalSeconds: number;
  };
  webhook: {
    url: string;
    apiKey: string;
  };
  constraints: {
    minIntervalSeconds: number;
    maxConcurrentChecks: number;
    allowedCheckTypes: Array<'latency' | 'error_rate' | 'uptime' | 'throughput'>;
  };
}

export class CognigyBotHealthMonitor {
  private token: string | null = null;
  private tokenExpiry: number = 0;
  private alertSync: AlertSynchronizer;
  private logger: AuditLogger;
  private config: MonitorConfig;
  private running = false;
  private intervalId: NodeJS.Timeout | null = null;

  constructor(config: MonitorConfig) {
    this.config = config;
    this.alertSync = new AlertSynchronizer(config.webhook);
    this.logger = new AuditLogger();
  }

  private async ensureToken(): Promise<string> {
    if (this.token && Date.now() < this.tokenExpiry) {
      return this.token;
    }

    const authStart = Date.now();
    const auth = await cognigyAuthenticate(this.config.cognigy);
    const authLatency = Date.now() - authStart;

    this.logger.log({
      timestamp: new Date().toISOString(),
      event: 'validation',
      botId: this.config.health.botId,
      status: 'success',
      details: `OAuth token refreshed in ${authLatency}ms`,
      latencyMs: authLatency
    });

    this.token = auth.access_token;
    this.tokenExpiry = Date.now() + (auth.expires_in * 1000) - 60000;
    return this.token;
  }

  async start(): Promise<void> {
    validateHealthPayload(this.config.health, this.config.constraints);
    this.logger.log({
      timestamp: new Date().toISOString(),
      event: 'validation',
      botId: this.config.health.botId,
      status: 'success',
      details: 'Health payload validated against engine constraints'
    });

    this.running = true;
    await this.runAssessment();

    this.intervalId = setInterval(async () => {
      if (this.running) await this.runAssessment();
    }, this.config.health.intervalSeconds * 1000);
  }

  private async runAssessment(): Promise<void> {
    const start = Date.now();
    try {
      const token = await this.ensureToken();
      const assessment = await assessBotHealth(
        this.config.cognigy.baseUrl,
        token,
        this.config.health
      );

      const latency = Date.now() - start;
      this.logger.log({
        timestamp: assessment.timestamp,
        event: 'assessment',
        botId: assessment.botId,
        status: assessment.thresholdBreaches.length > 0 ? 'warning' : 'success',
        details: `Error rate: ${assessment.errorRate.toFixed(4)}, Latency: ${assessment.avgLatencyMs}ms`,
        latencyMs: latency
      });

      if (assessment.thresholdBreaches.length > 0) {
        await this.alertSync.escalate(assessment);
        this.logger.log({
          timestamp: new Date().toISOString(),
          event: 'escalation',
          botId: assessment.botId,
          status: 'success',
          details: `Triggered ${assessment.thresholdBreaches.length} alert(s)`,
          latencyMs: latency
        });
      }
    } catch (error) {
      const latency = Date.now() - start;
      this.logger.log({
        timestamp: new Date().toISOString(),
        event: 'error',
        botId: this.config.health.botId,
        status: 'failure',
        details: error instanceof Error ? error.message : 'Unknown failure',
        latencyMs: latency
      });
    }
  }

  stop(): void {
    this.running = false;
    if (this.intervalId) clearInterval(this.intervalId);
  }

  getAuditLogs() {
    return this.logger.exportLogs();
  }

  getAlertAccuracy() {
    return this.alertSync.getAccuracyMetrics();
  }
}

The monitor class orchestrates authentication, validation, assessment, escalation, and logging. The start method validates the payload, begins polling, and schedules recurring checks. The stop method halts execution safely. All operations record structured audit entries with latency measurements.

Complete Working Example

The following script demonstrates the full monitor lifecycle. Replace the placeholder credentials and URLs with your Cognigy environment values.

// main.ts
import { CognigyBotHealthMonitor } from './monitor';

const monitorConfig = {
  cognigy: {
    baseUrl: 'https://yourcustomer.cognigy.com/api/v3',
    clientId: 'your_client_id',
    clientSecret: 'your_client_secret'
  },
  health: {
    botId: 'your_bot_id',
    checkTypes: ['error_rate', 'latency', 'uptime'],
    thresholds: [
      { metric: 'error_rate', operator: 'gte', value: 0.15, severity: 'warning' },
      { metric: 'error_rate', operator: 'gte', value: 0.25, severity: 'critical' },
      { metric: 'latency', operator: 'gte', value: 3000, severity: 'warning' },
      { metric: 'uptime', operator: 'lte', value: 0, severity: 'critical' }
    ],
    intervalSeconds: 60
  },
  webhook: {
    url: 'https://your-alerting-system.com/api/webhooks/cognigy-health',
    apiKey: 'your_webhook_api_key'
  },
  constraints: {
    minIntervalSeconds: 30,
    maxConcurrentChecks: 5,
    allowedCheckTypes: ['latency', 'error_rate', 'uptime', 'throughput']
  }
} as const;

async function main() {
  const monitor = new CognigyBotHealthMonitor(monitorConfig);
  
  process.on('SIGINT', () => {
    console.log('Shutting down monitor...');
    monitor.stop();
    console.log('Audit logs:');
    console.log(JSON.stringify(monitor.getAuditLogs(), null, 2));
    console.log('Alert accuracy:');
    console.log(JSON.stringify(monitor.getAlertAccuracy(), null, 2));
    process.exit(0);
  });

  console.log('Starting Cognigy Bot Health Monitor...');
  await monitor.start();
}

main().catch(err => {
  console.error('Monitor initialization failed:', err);
  process.exit(1);
});

Compile and run with:

npx tsc main.ts
node main.js

The script validates the health matrix, authenticates, begins polling at 60-second intervals, calculates metrics, triggers webhooks on threshold breaches, and exports audit logs and accuracy rates on graceful shutdown.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: OAuth token expired, invalid client credentials, or missing bot:read/analytics:read scopes.
• Fix: Verify client ID and secret in Cognigy administration. Ensure the scope parameter in the token request matches required permissions. The ensureToken method automatically refreshes tokens before expiration.
• Code showing the fix: The authentication module throws a descriptive error on non-200 responses. Catch it and verify credentials.

try {
  const token = await cognigyAuthenticate(config);
} catch (err) {
  console.error('Authentication failed. Verify client credentials and scopes.');
  console.error(err);
}

Error: 429 Too Many Requests

• Cause: Polling interval violates Cognigy rate limits or concurrent check threshold.
• Fix: Increase intervalSeconds in the health configuration. The fetchWithRetry function implements exponential backoff and respects Retry-After headers.
• Code showing the fix: The retry loop pauses execution and increments delay on each 429 response.

if (response.status === 429) {
  const retryAfter = response.headers.get('Retry-After') || Math.pow(2, attempt);
  await new Promise(r => setTimeout(r, parseInt(retryAfter, 10) * 1000));
  continue;
}

Error: Schema Validation Failure

• Cause: Health check matrix references metrics not in checkTypes, or interval falls below minIntervalSeconds.
• Fix: Align threshold metrics with the check type matrix. Increase polling interval to meet engine constraints.
• Code showing the fix: The validateHealthPayload function throws explicit errors before execution begins.

validateHealthPayload(healthConfig, constraints); // Throws if misaligned

Error: 500 Internal Server Error or Webhook Delivery Failure

• Cause: Cognigy analytics endpoint unavailable or external alerting system rejects payload.
• Fix: Verify Cognigy platform status. Confirm webhook URL accepts JSON and validates API keys. The monitor logs 5xx failures and continues polling without crashing.
• Code showing the fix: The runAssessment method catches all errors and records them in the audit logger.

Official References

• Cognigy OAuth2 Authentication Documentation
• Cognigy Bot Management API Reference
• Cognigy Analytics API Reference
• Node.js Fetch API Documentation
• TypeScript Handbook: Working with Promises