Check Product Status

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The Check Product Status API enables you to monitor the processing status of product creation, update, or deletion requests submitted to Fynd Commerce. After submitting products through the respective APIs, you receive a trace_id which can be used to track whether the operation completed successfully, is still processing, or encountered errors.

This endpoint provides detailed insights into batch processing results, including success counts, failure reasons, and granular error messages for individual products. It's essential for validating that product data has been correctly transmitted and processed by the Fynd Platform.

Request Type: GET
Scheme: HTTPS
Endpoint: https://{{host}}/v3/catalog/status

Common Request Headers

curl -i -X GET \
  'https://fyndkonnect.konnect.uat.fyndx1.de/v3/catalog/status?trace_id=string' \
  -H 'x-access-token: YOUR_API_KEY_HERE'

  {
    "trace_id": "b3bbaead9858e85d-1760266497372",
    "total": 2,
    "success": 2,
    "failed": 0,
    "status": "SUCCESS",
    "errors": {},
    "stage": "COMPLETED",
    "batch_id": "68eb89029955e2f2705c981b",
    "company_id": 6900,
    "meta": {
        "cancelled": 0,
        "cancelled_records": [],
        "failed": 0,
        "failed_records": [],
        "stage": "completed",
        "succeed": 2
    },
    "last_updated_on": "2025-10-12T10:54:59.058168372Z"
  }

Understanding Processing Stages

When to Expect PENDING Stage?

Products remain in PENDING stage when:

1. Batch validation is in progress
2. Products are queued for processing
3. System is performing data validation checks
4. Large batches are being processed sequentially

Recommended Action: Continue polling the status endpoint until stage changes to COMPLETED, PARTIAL, or FAILED.

Common Failure Causes

Products fail validation when:

1. Invalid enum values: Incorrect data types or values for fields with predefined options
2. Reference errors: Invalid category, department, brand, slug, or template that don't exist
3. Missing mandatory fields: Required attributes not provided (check Fetch Attributes by Product)
4. Data format errors: Incorrect date formats, invalid URLs, malformed identifiers
5. Duplicate identifiers: SKUs or slugs that already exist in the catalog

Recommended Action: Review failed_records array, fix the issues in your source data, and resubmit the products.

Best Practices

1. Poll with intervals: Check status every 5-10 seconds for PENDING/RUNNING stages to avoid excessive API calls
2. Implement exponential backoff: Increase polling interval for long-running operations
3. Parse failed_record: Extract error messages programmatically for automated error handling
4. Log trace_id: Maintain a mapping of trace_ids to your internal product identifiers for debugging
5. Handle partial success: Implement logic to resubmit only failed products from PARTIAL batches
6. Set timeouts: Implement reasonable timeouts (5-10 minutes) for status checks
7. Validate before submission: Use reference APIs (departments, categories, brands, templates) to validate data before creating products
8. Monitor error patterns: Track common error types to improve data quality
9. Retry with fixes: For FAILED batches, fix all validation errors before resubmission
10. Archive status responses: Store status responses for audit trails and troubleshooting