.NET Hangfire Job Trigger Returns 'Succeeded' in Cloud DB but Doesn’t Execute

Below is a list of possible causes and steps to gather more info:

1. Confirm the Active Processing Server

• Multiple Projects Sharing the Same DB:
  With your cloud database being shared across projects, it’s possible that a different Hangfire server (or even multiple servers) is consuming the triggered job. Verify which server “owns” the job by checking the Hangfire dashboard (or logs). Make sure the server that processes the job has your breakpoints attached (or is running the same executable).

• Server Names & Worker Roles:
  In your local Docker environment, your debugging server picks up the job because it’s the only one. In the cloud scenario, the job might be processed by a server that isn’t attached to Rider. Check the “Servers” panel in the dashboard and verify that the intended server is running, and that its queues match what you’re triggering.

2. Check Job Configuration and Registration

• Method Binding & Assembly Versions:
  Ensure that the job method is correctly registered in the cloud-deployed server instance. In Hangfire, the job’s method call is registered in the recurring job’s data. If multiple projects share the same DB, a job with the same identifier might be registered differently on different servers.

• Manual Trigger Behavior:
  When you use RecurringJob.TriggerJob(), Hangfire enqueues a job to be executed immediately. In your cloud scenario, although the job is enqueued and then marked “Succeeded,” the actual execution might be occurring somewhere else. Confirm that the job definition in the cloud server matches your local job definition.

3. Look at Hangfire Logs and Dashboard Details

• Dashboard Inspection:
  Inspect the job details on the Hangfire dashboard. Look for:
  • The enqueued job’s creation, processing, and completion times.
  • The server instance that processed the job.
  • Any potential errors (even if the final state is “Succeeded”).
• Logging:
  Increase the logging level on the cloud server to track job enqueueing and processing. Logs can reveal if the triggered job is being silently completed (or if a different, maybe even “stub” job is being executed).

4. Use Additional Diagnostics

• Test with BackgroundJob.Enqueue:
  Instead of using RecurringJob.TriggerJob, try manually enqueueing the same job with BackgroundJob.Enqueue. This can help determine whether the problem is specific to manually triggering recurring jobs.

• Inspect Connection Strings & Hangfire Options:
  Double-check that the connection string and MongoDB options in your cloud deployment are configured as expected. A misconfiguration may cause subtle differences in how the job is persisted or delivered.

5. Environment Consistency

• Debug vs. Release:
  Confirm that your cloud server instance isn’t running a different build of your code (which might, for instance, have different startup configurations, error-handling behavior, or even the Hangfire job setup).

Summary

The likely issue is that the manually triggered job is being picked up by a different Hangfire server instance (due to shared DB usage) which doesn’t have your debugger attached or might be running altered configurations. Start by checking the Hangfire dashboard to see which server processes the trigger; then, confirm that the correct job registration and assembly are deployed and in sync with your debugging expectations.

Gather the following details to help diagnose further:

• Which server (by name) processes the job.
• Detailed logs and execution history from Hangfire.
• The exact job metadata from the dashboard (job type, method, etc.).
• Behavior when using BackgroundJob.Enqueue.

These steps should help pinpoint why the code isn’t executing as expected in the cloud environment.