Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
We run Apex batch jobs on a schedule, and most of the time they complete successfully. Occasionally, they fail without obvious errors or with inconsistent behavior. Rerunning the same job often works. I’m trying to understand why batch jobs behave unreliably.
Batch Apex runs in multiple transactions, and failures often depend on data distribution rather than logic. A specific batch chunk may hit governor limits, record locks, or validation errors that don’t exist in other chunks.
Because batches process subsets of data, the same code path might encounter edge cases only under certain data conditions. This makes failures appear random even though they’re data-driven.
Improving batch reliability usually involves adding defensive checks, better exception handling, and logging failed record IDs for analysis.
Takeaway: Batch failures are usually caused by edge-case data, not random system behavior.