Best Practices for Error Handling in External System

Error handling is a crucial aspect of any integration to ensure data integrity and system reliability. When integrating with the 4ws suite for stock updates, it is essential to have a robust error handling mechanism. This chapter outlines best practices for error handling in the external system.

1. Logging and Monitoring

1.1. Comprehensive Logging

Log All Requests and Responses: Capture all incoming and outgoing requests, including headers and payloads. This is essential for debugging and auditing purposes.

Error Logs: Maintain a separate log for errors, capturing details such as error messages, stack traces, and timestamps.

Granular Logging Levels: Use different logging levels (e.g., INFO, DEBUG, WARN, ERROR) to categorize log entries based on their severity.

1.2. Real-Time Monitoring

Monitoring Tools: Use monitoring tools (e.g., Prometheus, Grafana) to track system performance and detect anomalies in real time.

Alerting: Set up alerts for critical errors and performance degradation to ensure timely intervention.

2. Error Handling Strategy

2.1. Retry Mechanism

Automatic Retries: Implement automatic retries for transient errors, such as network timeouts or temporary unavailability of the 4ws suite services.

Exponential Backoff: Use exponential backoff for retry attempts to avoid overwhelming the 4ws suite with repeated requests in a short period.

2.2. Graceful Degradation

Fallback Mechanisms: Implement fallback mechanisms to handle cases when the 4ws suite services are unavailable. For instance, cache the last successful response and serve from the cache until the service is back online.

User Notifications: Inform users about temporary unavailability of stock data, and provide an estimated time for resolution.

3. Data Integrity

3.1. Validation

Schema Validation: Validate incoming data against a predefined schema to ensure data consistency and correctness.

Business Rules Validation: Implement business rules validation to check for logical errors in the data (e.g., negative stock quantities).

3.2. Idempotency

Idempotent Operations: Ensure that repeated processing of the same data (e.g., due to retries) does not result in inconsistent state. Use unique request identifiers to track and handle duplicate requests.

4. Error Handling for CSV Processing

4.1. CSV Validation

Format Validation: Check the CSV file for correct format, mandatory fields, and data types before processing.

Record Validation: Validate each record in the CSV file for completeness and correctness.

4.2. Partial Failures

Error Reporting: Report and log individual record errors without halting the entire CSV processing.

Batch Processing: Process valid records and skip invalid ones, generating a detailed error report for skipped records.

5. Error Handling for Delta Stock Updates

5.1. Pagination Handling

Paginated Responses: Implement logic to handle paginated responses from the Get last stock service, ensuring all pages are retrieved and processed.

Partial Updates: Handle partial updates gracefully, ensuring stock records are consistent even if a subset of updates fails.

5.2. API Rate Limits

Rate Limiting: Respect the rate limits of the 4ws suite APIs to avoid throttling. Implement request throttling in the external system if necessary.

Backoff Strategy: Implement a backoff strategy to handle rate limit exceeded errors, retrying the request after a specified interval.

6. Notifications and Alerts

6.1. Error Notifications

Email Alerts: Send email alerts to the IT department for critical errors that require immediate attention.

SMS Alerts: Use SMS alerts for urgent issues that need instant response.

6.2. Dashboard

Error Dashboard: Create a dashboard to visualize errors, processing status, and system health. This helps in quick identification and resolution of issues.

7. Error Recovery

7.1. Retry Mechanism for Failed Updates

Persistent Queue: Use a persistent queue to store failed updates. Implement a retry mechanism to process these updates at regular intervals.

Manual Intervention: Provide an interface for the IT team to manually review and reprocess failed updates if automatic retries fail.

7.2. Data Reconciliation

Periodic Reconciliation: Perform periodic data reconciliation between the external system and the 4ws suite to ensure data consistency. Generate reports for any discrepancies found.

Reprocessing Mechanism: Implement a mechanism to reprocess data for specific time ranges or entities in case of data mismatches.

8. Pagination Handling

If the API response indicates that there are more rows available (moreRows: true), ensure that your system is capable of making subsequent requests to retrieve all data.
Use the appropriate query parameters (cursor) to manage large datasets effectively.
Refer to our Paginated Responses.

Conclusion

By following these best practices, the external system can ensure robust error handling, maintain data integrity, and provide reliable and accurate stock updates based on the data from the 4ws suite. Comprehensive logging, monitoring, and a well-defined error recovery process are key to achieving this goal.

Best Practices for Error Handling in External System