Stock batch update jobs fail intermittently during AWS region failover events

ERP Infor CloudSuite
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1

We’re experiencing intermittent failures with our nightly stock batch update jobs, and we’ve identified a correlation with AWS regional issues. When AWS has connectivity problems or does maintenance in our primary region, the batch jobs fail silently without completing the inventory updates.

The frustrating part is that manual stock updates through the UI work perfectly fine even during these AWS events. Our warehouse team can still adjust quantities, create transfers, and everything processes normally. It’s only the automated batch jobs that fail.

We’re ending up with inventory mismatches because the batch processes don’t resume or retry after the AWS issues resolve. Even worse, we have no alerting configured for these failures, so we only discover the problem when warehouse staff notice discrepancies days later.

Has anyone implemented a reliable failover strategy for batch jobs during cloud infrastructure events? We need these jobs to either complete successfully or at least notify us when they fail.

system 2

Here’s a comprehensive solution that addresses all three focus areas without requiring a full multi-region architecture:

First, addressing why jobs fail only during AWS issues while manual updates succeed: The root cause is connection timeout sensitivity. Manual stock updates are short-lived transactions (typically under 5 seconds) that complete before any network disruption impacts them. Your batch jobs, however, process hundreds or thousands of stock records in a single session, holding database connections for 10-30 minutes. When AWS experiences regional connectivity issues - even brief 30-60 second disruptions - these long-held connections exceed TCP timeout thresholds and get terminated by the network layer. CloudSuite’s batch framework doesn’t always detect these connection drops gracefully, causing the job to fail without proper error handling.

Second, implementing automatic recovery since manual updates succeed: Configure intelligent retry logic at the batch scheduler level. In CloudSuite, navigate to System Administration > Batch Scheduler > Job Definitions. Edit your stock update job and enable these settings:

  • Retry on Failure: Enabled
  • Maximum Retry Attempts: 3
  • Retry Delay Strategy: Exponential Backoff (5min, 15min, 30min)
  • Retry Conditions: Network errors, connection timeouts, database unavailable
  • Checkpoint Interval: 100 records

The checkpoint setting is critical - it tells the job to commit progress every 100 stock records. If the job fails at record 450, the retry will resume from record 400 instead of starting over. This makes retries much more likely to succeed because they have less work to complete before the next potential disruption.

Additionally, implement connection health checks within the job itself. Add a pre-execution validation step that tests database connectivity and AWS service availability. If the health check fails, the job should delay execution by 10 minutes and retry the health check rather than attempting to process records with degraded connectivity.

Third, solving the alerting gap for failed jobs: The lack of notifications is dangerous because inventory mismatches compound over time. Implement a two-tier alerting strategy:

Immediate Alerts: Configure ION workflow notifications for real-time job failures. In ION Desk, create a workflow document flow that subscribes to the ‘BatchJobFailed’ event. Route this to your operations team via email and SMS. The alert should include:

  • Job name and scheduled time
  • Failure reason and error code
  • Number of records processed before failure
  • Automatic retry status

Daily Summary: Create a scheduled report that runs every morning at 7 AM listing all batch jobs from the previous 24 hours with their completion status. This catches any failures that might have been missed by the immediate alerts and provides a comprehensive view of batch processing health.

Implement AWS CloudWatch integration for infrastructure-level monitoring. Set up a CloudWatch alarm that monitors your CloudSuite database connection pool metrics. When connection failures spike above 5% within a 5-minute window, trigger a preventive alert that warns your team about potential AWS issues before batch jobs fail. This gives you time to manually delay job execution or switch to manual processing if needed.

With these configurations in place, your batch jobs will automatically retry after transient AWS failures, resume from checkpoints rather than restarting completely, and notify your team immediately if all retries are exhausted. This eliminates the multi-day discovery delays you’re currently experiencing and brings batch job reliability in line with your manual update success rate.

This draft is based on general Infor CloudSuite knowledge. It has not been verified against your specific version and environment. Practitioners: verify the steps and share your experience below.

3

Batch jobs are more sensitive to network interruptions than interactive sessions because they hold database connections for longer periods. When AWS has regional issues, those long-running connections get dropped but the job doesn’t always detect it. You need to implement connection retry logic in your batch job configuration.

kavya_ninja 4

Tested this on CloudSuite Industrial with 50,000-record batch jobs — chunking transactions to 500 records with connection timeout thresholds at 45 seconds eliminated all intermittent failures during our last three AWS us-east-1 degradation events.

5

This is a classic high availability gap. Your manual updates work because they’re short transactions that complete before any network disruption affects them. Batch jobs run for minutes or hours, so they’re vulnerable to transient failures. You should configure your CloudSuite batch scheduler to use AWS multi-region deployment. Set up a secondary region as failover and configure automatic job migration when the primary region degrades. Also implement health checks that pause jobs if network latency exceeds thresholds rather than letting them fail partway through.

6

The multi-region approach sounds good but we’re not set up for that yet. Is there a simpler solution we can implement quickly? Maybe something that just retries the job automatically when it fails?

7

Yes, you can configure retry logic without multi-region setup. In the Batch Scheduler configuration, enable automatic retry with exponential backoff. Set it to retry up to 3 times with 5-minute delays. This handles transient AWS issues that resolve quickly. For the alerting gap, integrate with CloudWatch or your monitoring system to send notifications when jobs fail after all retries are exhausted.

8

For the alerting issue specifically, you can use ION workflow alerts. Create a workflow that triggers on batch job failure events and sends notifications to your operations team. Include the job name, failure reason, and timestamp in the alert. This gives you immediate visibility instead of discovering failures days later through inventory discrepancies.