Hi everyone,
We're trying to understand the root cause of an intermittent scheduler issue and would appreciate any insights from the community.
We are seeing the error:
What's making the investigation difficult is that the behavior is inconsistent across environments and even across schedulers within the same application.
A few observations:
- A colleague of mine previously encountered this error in DEV.
- I never experienced it myself in DEV, and all scheduled flows have been starting correctly there.
- We opened a support ticket for DEV because we initially did not fully understand the scheduler startup/execution order. MuleSoft provided some clarification, and the schedulers in DEV are now working as expected.
- However, during yesterday's deployment to Production, the same "Failed to start scheduler..." error appeared again.
- In Production, some schedulers start successfully while others do not. In most cases they fail to start.
- In one application, neither of the two scheduled flows starts at all after deployment.
At the moment, the issue appears to be intermittent: sometimes the schedulers start correctly, sometimes they don't, and we have not been able to identify a clear pattern or environmental difference that explains the behavior.
Has anyone encountered a similar issue or knows what conditions could cause a scheduler to fail during startup in this way?
Any suggestions, experiences, or troubleshooting tips would be greatly appreciated.
Thank you!
Best Regards,
Rosaria
#MuleSoft Connectors / SDK / DevKit
This usually stems from how cluster node leadership election or timezone offsets interact with Quartz scheduler triggers during application initialization. When multiple replicas spin up simultaneously in higher environments like Production, race conditions or cluster locking can prevent specific flows from acquiring the trigger lock successfully on the first heartbeat, causing them to stall while others start fine.
To troubleshoot and stabilize this, check your container deployment scaling and replica counts to ensure your application isn't hitting cluster concurrency lock contention during startup. You can also review your Cron expression definitions to ensure they don't rely on overly tight execution windows that overlap with the deployment lifecycle, and consider adding a slight staggered startup delay or adjusting your clustering configuration to allow the primary node to claim scheduler ownership cleanly.
