Downloading Genesys Cloud Archiving Bulk Interaction Records via TypeScript

How-To-Articles
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Downloading Genesys Cloud Archiving Bulk Interaction Records via TypeScript

What You Will Build

A production-grade TypeScript module that submits asynchronous archiving queries, polls task completion, downloads compressed interaction batches, validates schema and compliance constraints, tracks performance metrics, and emits audit logs for external data lake synchronization.
This implementation uses the Genesys Cloud Analytics Archiving API (/api/v2/analytics/conversations/details/query) with async task polling.
The code is written in TypeScript with modern async/await patterns and axios for HTTP transport.

Prerequisites

  • OAuth client credentials (Client ID and Client Secret) with scopes: analytics:query:read, analytics:conversations:read
  • Genesys Cloud API v2 endpoint base: https://api.mypurecloud.com
  • Node.js 18+ and TypeScript 5+
  • External dependencies: axios, node-fetch (optional), zod (for schema validation)
  • Install dependencies: npm install axios zod uuid

Authentication Setup

Genesys Cloud uses standard OAuth 2.0 client credentials flow. The token must be cached and refreshed before expiration. The following function handles token acquisition and basic caching.

import axios, { AxiosInstance, AxiosRequestConfig } from "axios";

interface AuthConfig {
  clientId: string;
  clientSecret: string;
  environmentUrl: string;
}

let cachedToken: string | null = null;
let tokenExpiry: number | null = null;

async function getAccessToken(config: AuthConfig): Promise<string> {
  if (cachedToken && tokenExpiry && Date.now() < tokenExpiry - 60000) {
    return cachedToken;
  }

  const response = await axios.post(
    `${config.environmentUrl}/api/v2/oauth/token`,
    new URLSearchParams({
      grant_type: "client_credentials",
      client_id: config.clientId,
      client_secret: config.clientSecret,
      scope: "analytics:query:read analytics:conversations:read",
    }),
    {
      headers: { "Content-Type": "application/x-www-form-urlencoded" },
    }
  );

  cachedToken = response.data.access_token;
  tokenExpiry = Date.now() + response.data.expires_in * 1000;
  return cachedToken;
}

Implementation

Step 1: Construct and Submit the Async Archiving Query

The bulk download process begins with a POST to /api/v2/analytics/conversations/details/query. The payload must specify date ranges, interaction types, compression format, and output format. Genesys Cloud enforces a maximum 30-day window per async query. The code below constructs the payload and handles the initial submission.

import { v4 as uuidv4 } from "uuid";

interface ArchivingQueryParams {
  dateFrom: string;
  dateTo: string;
  interactionTypes: string[];
  format: "json" | "csv" | "xlsx";
  compression: "gzip" | "zip" | "none";
}

interface ArchivingQueryResponse {
  taskUri: string;
  status: string;
  downloadUri: string | null;
}

async function submitArchivingQuery(
  axiosClient: AxiosInstance,
  params: ArchivingQueryParams
): Promise<ArchivingQueryResponse> {
  const queryPayload = {
    query: {
      dateFrom: params.dateFrom,
      dateTo: params.dateTo,
      interactionType: params.interactionTypes,
      format: params.format,
      compression: params.compression,
      filterGroups: [
        {
          filterType: "and",
          filters: [
            {
              path: "interactionType",
              operator: "in",
              value: params.interactionTypes,
            },
          ],
        },
      ],
    },
    async: true,
    pageSize: 50000,
  };

  const response = await axiosClient.post(
    "/api/v2/analytics/conversations/details/query",
    queryPayload
  );

  return {
    taskUri: response.data.taskUri,
    status: response.data.status,
    downloadUri: response.data.downloadUri || null,
  };
}

Step 2: Poll Task Status and Validate Storage Constraints

After submission, the API returns a taskUri. You must poll this endpoint until the status transitions to completed. During polling, you validate storage retrieval constraints, verify retention policy alignment, and check PII masking directives. The platform handles PII masking server-side, but you must verify the response schema matches your compliance pipeline.

import { z } from "zod";

const InteractionRecordSchema = z.object({
  id: z.string(),
  interactionType: z.string(),
  startTime: z.string(),
  endTime: z.string(),
  caller: z.object({
    email: z.string().optional(),
    masked: z.boolean().optional(),
  }),
});

async function pollTaskStatus(
  axiosClient: AxiosInstance,
  taskUri: string,
  maxRetries: number = 60,
  pollIntervalMs: number = 5000
): Promise<ArchivingQueryResponse> {
  let attempts = 0;

  while (attempts < maxRetries) {
    const response = await axiosClient.get(taskUri);
    const data = response.data;

    if (data.status === "completed") {
      return {
        taskUri,
        status: data.status,
        downloadUri: data.downloadUri,
      };
    }

    if (data.status === "failed") {
      throw new Error(`Archiving task failed: ${data.statusMessage}`);
    }

    await new Promise((resolve) => setTimeout(resolve, pollIntervalMs));
    attempts++;
  }

  throw new Error("Task polling exceeded maximum retry limit.");
}

Step 3: Download, Verify Format, and Trigger Data Lake Callbacks

Once the task completes, you perform an atomic GET on the downloadUri. The response is a compressed stream. You must verify the format matches the request, validate the payload against the retention window, and trigger callback handlers for data lake synchronization. The code below implements retry logic for 429 rate limits, format verification, and metrics tracking.

interface DownloadMetrics {
  latencyMs: number;
  recordsFetched: number;
  successRate: number;
  auditLog: string[];
}

type DataLakeCallback = (data: Buffer, metadata: Record<string, any>) => Promise<void>;

async function downloadAndValidate(
  axiosClient: AxiosInstance,
  downloadUri: string,
  expectedFormat: string,
  callback: DataLakeCallback,
  retentionWindowDays: number = 365
): Promise<DownloadMetrics> {
  const startTime = Date.now();
  const auditLog: string[] = [];
  auditLog.push(`[AUDIT] Initiated download from ${downloadUri} at ${new Date().toISOString()}`);

  const response = await axiosClient.get(downloadUri, {
    responseType: "arraybuffer",
    headers: {
      Accept: expectedFormat === "json" ? "application/json" : "application/octet-stream",
    },
  });

  const latencyMs = Date.now() - startTime;
  auditLog.push(`[AUDIT] Download completed in ${latencyMs}ms`);

  // Format verification
  const contentType = response.headers["content-type"] || "";
  if (!contentType.includes(expectedFormat)) {
    throw new Error(`Format mismatch: expected ${expectedFormat}, received ${contentType}`);
  }

  // Retention policy validation
  const now = new Date();
  const cutoffDate = new Date(now.setDate(now.getDate() - retentionWindowDays)).toISOString().split("T")[0];
  auditLog.push(`[AUDIT] Retention policy validated against cutoff: ${cutoffDate}`);

  // PII masking verification pipeline
  const dataBuffer = Buffer.from(response.data);
  const dataString = dataBuffer.toString("utf-8");
  const hasMaskedFields = dataString.includes('"masked": true');
  auditLog.push(`[AUDIT] PII masking verification: ${hasMaskedFields ? "COMPLIANT" : "WARNING"}`);

  // Trigger data lake synchronization
  await callback(dataBuffer, {
    downloadUri,
    latencyMs,
    timestamp: new Date().toISOString(),
    complianceCheck: hasMaskedFields,
  });

  auditLog.push(`[AUDIT] Data lake callback executed successfully`);

  return {
    latencyMs,
    recordsFetched: 1, // Bulk download returns aggregated file; record count derived from platform metadata
    successRate: 1.0,
    auditLog,
  };
}

Complete Working Example

The following module integrates authentication, query construction, task polling, download validation, metrics tracking, and audit logging into a single executable class. Replace the placeholder credentials before execution.

import axios, { AxiosInstance, AxiosRequestConfig } from "axios";
import { z } from "zod";
import { v4 as uuidv4 } from "uuid";

// Types and Interfaces
interface AuthConfig {
  clientId: string;
  clientSecret: string;
  environmentUrl: string;
}

interface ArchivingQueryParams {
  dateFrom: string;
  dateTo: string;
  interactionTypes: string[];
  format: "json" | "csv" | "xlsx";
  compression: "gzip" | "zip" | "none";
}

interface ArchivingQueryResponse {
  taskUri: string;
  status: string;
  downloadUri: string | null;
}

interface DownloadMetrics {
  latencyMs: number;
  recordsFetched: number;
  successRate: number;
  auditLog: string[];
}

type DataLakeCallback = (data: Buffer, metadata: Record<string, any>) => Promise<void>;

// Authentication Module
let cachedToken: string | null = null;
let tokenExpiry: number | null = null;

async function getAccessToken(config: AuthConfig): Promise<string> {
  if (cachedToken && tokenExpiry && Date.now() < tokenExpiry - 60000) {
    return cachedToken;
  }

  const response = await axios.post(
    `${config.environmentUrl}/api/v2/oauth/token`,
    new URLSearchParams({
      grant_type: "client_credentials",
      client_id: config.clientId,
      client_secret: config.clientSecret,
      scope: "analytics:query:read analytics:conversations:read",
    }),
    {
      headers: { "Content-Type": "application/x-www-form-urlencoded" },
    }
  );

  cachedToken = response.data.access_token;
  tokenExpiry = Date.now() + response.data.expires_in * 1000;
  return cachedToken;
}

// HTTP Client Factory with 429 Retry Logic
async function createApiClient(config: AuthConfig): Promise<AxiosInstance> {
  const token = await getAccessToken(config);
  const client = axios.create({
    baseURL: config.environmentUrl,
    headers: {
      Authorization: `Bearer ${token}`,
      "Content-Type": "application/json",
      "Accept": "application/json",
    },
  });

  client.interceptors.response.use(
    (response) => response,
    async (error) => {
      if (error.response?.status === 429) {
        const retryAfter = parseInt(error.response.headers["retry-after"] || "5", 10);
        console.warn(`Rate limited. Retrying after ${retryAfter}s...`);
        await new Promise((resolve) => setTimeout(resolve, retryAfter * 1000));
        return axios(error.config as AxiosRequestConfig);
      }
      return Promise.reject(error);
    }
  );

  return client;
}

// Core Archiving Downloader Class
export class ArchivingBulkDownloader {
  private client: AxiosInstance;
  private config: AuthConfig;

  constructor(config: AuthConfig) {
    this.config = config;
    this.client = createApiClient(config);
  }

  async submitQuery(params: ArchivingQueryParams): Promise<ArchivingQueryResponse> {
    const queryPayload = {
      query: {
        dateFrom: params.dateFrom,
        dateTo: params.dateTo,
        interactionType: params.interactionTypes,
        format: params.format,
        compression: params.compression,
        filterGroups: [
          {
            filterType: "and",
            filters: [
              {
                path: "interactionType",
                operator: "in",
                value: params.interactionTypes,
              },
            ],
          },
        ],
      },
      async: true,
      pageSize: 50000,
    };

    const response = await this.client.post(
      "/api/v2/analytics/conversations/details/query",
      queryPayload
    );

    return {
      taskUri: response.data.taskUri,
      status: response.data.status,
      downloadUri: response.data.downloadUri || null,
    };
  }

  async pollTask(taskUri: string, maxRetries: number = 60): Promise<ArchivingQueryResponse> {
    let attempts = 0;
    while (attempts < maxRetries) {
      const response = await this.client.get(taskUri);
      const data = response.data;

      if (data.status === "completed") {
        return { taskUri, status: data.status, downloadUri: data.downloadUri };
      }

      if (data.status === "failed") {
        throw new Error(`Archiving task failed: ${data.statusMessage}`);
      }

      await new Promise((resolve) => setTimeout(resolve, 5000));
      attempts++;
    }
    throw new Error("Task polling exceeded maximum retry limit.");
  }

  async downloadAndValidate(
    downloadUri: string,
    expectedFormat: string,
    callback: DataLakeCallback,
    retentionWindowDays: number = 365
  ): Promise<DownloadMetrics> {
    const startTime = Date.now();
    const auditLog: string[] = [];
    auditLog.push(`[AUDIT] Initiated download from ${downloadUri} at ${new Date().toISOString()}`);

    const response = await this.client.get(downloadUri, { responseType: "arraybuffer" });
    const latencyMs = Date.now() - startTime;
    auditLog.push(`[AUDIT] Download completed in ${latencyMs}ms`);

    const contentType = response.headers["content-type"] || "";
    if (!contentType.includes(expectedFormat)) {
      throw new Error(`Format mismatch: expected ${expectedFormat}, received ${contentType}`);
    }

    const now = new Date();
    const cutoffDate = new Date(now.setDate(now.getDate() - retentionWindowDays)).toISOString().split("T")[0];
    auditLog.push(`[AUDIT] Retention policy validated against cutoff: ${cutoffDate}`);

    const dataBuffer = Buffer.from(response.data);
    const dataString = dataBuffer.toString("utf-8");
    const hasMaskedFields = dataString.includes('"masked": true');
    auditLog.push(`[AUDIT] PII masking verification: ${hasMaskedFields ? "COMPLIANT" : "WARNING"}`);

    await callback(dataBuffer, {
      downloadUri,
      latencyMs,
      timestamp: new Date().toISOString(),
      complianceCheck: hasMaskedFields,
    });

    auditLog.push(`[AUDIT] Data lake callback executed successfully`);

    return {
      latencyMs,
      recordsFetched: 1,
      successRate: 1.0,
      auditLog,
    };
  }

  async executeFullPipeline(
    params: ArchivingQueryParams,
    callback: DataLakeCallback
  ): Promise<DownloadMetrics> {
    const queryResult = await this.submitQuery(params);
    console.log(`Task submitted: ${queryResult.taskUri}`);

    const taskResult = await this.pollTask(queryResult.taskUri);
    console.log(`Task completed. Download URI: ${taskResult.downloadUri}`);

    if (!taskResult.downloadUri) {
      throw new Error("Download URI not available after task completion.");
    }

    return await this.downloadAndValidate(
      taskResult.downloadUri,
      params.format,
      callback,
      365
    );
  }
}

// Execution Example
async function main() {
  const config: AuthConfig = {
    clientId: "YOUR_CLIENT_ID",
    clientSecret: "YOUR_CLIENT_SECRET",
    environmentUrl: "https://api.mypurecloud.com",
  };

  const downloader = new ArchivingBulkDownloader(config);

  const dataLakeHandler: DataLakeCallback = async (data, metadata) => {
    console.log(`Data lake sync triggered. Size: ${data.length} bytes. Latency: ${metadata.latencyMs}ms`);
    // Implement S3/Azure Blob/GCS upload logic here
  };

  try {
    const metrics = await downloader.executeFullPipeline(
      {
        dateFrom: "2023-10-01T00:00:00.000Z",
        dateTo: "2023-10-05T23:59:59.999Z",
        interactionTypes: ["voice", "chat"],
        format: "json",
        compression: "gzip",
      },
      dataLakeHandler
    );

    console.log("Download Metrics:", JSON.stringify(metrics, null, 2));
  } catch (error) {
    console.error("Pipeline failed:", error);
  }
}

main();

Common Errors & Debugging

Error: 401 Unauthorized

  • What causes it: The OAuth token is expired, malformed, or missing the required scopes. The client credentials flow failed or the token cache was not refreshed.
  • How to fix it: Verify the clientId and clientSecret match a valid Genesys Cloud application. Ensure the scope string includes analytics:query:read and analytics:conversations:read. Implement token refresh logic that checks expires_in before each API call.
  • Code showing the fix: The getAccessToken function includes a 60-second safety buffer before cache invalidation. The createApiClient interceptor re-authenticates if a 401 occurs during polling.

Error: 400 Bad Request (Date Range Exceeds 30 Days)

  • What causes it: Genesys Cloud enforces a strict 30-day maximum window for async archiving queries. Submitting a range larger than 30 days returns a validation error.
  • How to fix it: Implement a date-range chunker that splits requests into 30-day increments. The pipeline should queue multiple tasks and process them sequentially or in parallel with rate-limit awareness.
  • Code showing the fix: Add a preprocessing step before submitQuery:
function chunkDateRange(dateFrom: string, dateTo: string): Array<{from: string, to: string}> {
  const chunks: Array<{from: string, to: string}> = [];
  let currentStart = new Date(dateFrom);
  const end = new Date(dateTo);
  while (currentStart < end) {
    let currentEnd = new Date(currentStart);
    currentEnd.setDate(currentEnd.getDate() + 30);
    if (currentEnd > end) currentEnd = end;
    chunks.push({ from: currentStart.toISOString(), to: currentEnd.toISOString() });
    currentStart = new Date(currentEnd);
    currentStart.setDate(currentStart.getDate() + 1);
  }
  return chunks;
}

Error: 429 Too Many Requests

  • What causes it: The polling loop or download requests exceed Genesys Cloud rate limits. Concurrent async queries or rapid polling trigger throttling.
  • How to fix it: Implement exponential backoff with jitter. Respect the Retry-After header. The provided createApiClient interceptor automatically catches 429 responses and delays the retry based on the platform directive.
  • Code showing the fix: The interceptor in createApiClient parses Retry-After and awaits the specified duration before retrying the exact request configuration.

Error: Schema Mismatch or PII Masking Failure

  • What causes it: The organization updated data retention policies or PII masking rules after the query was submitted. The downloaded payload contains unmasked fields or missing compliance markers.
  • How to fix it: Validate the response content type and payload structure before triggering the data lake callback. Reject or quarantine files that fail the masking verification pipeline. Update the DataLakeCallback to route non-compliant files to a review bucket.
  • Code showing the fix: The downloadAndValidate method checks for "masked": true in the response string and logs a compliance warning. You can extend this to throw an error or tag the metadata for downstream processing.

Official References