Implementation of batch job on Mulesoft Runtime Fabric on Azure Kubernetes Service (Specific to MuleSoft implementation)

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Did anyone use MuleSoft Batch process on Runtime Fabric on Azure/AWS? How was your experience with that implementation? Any best practices? I am trying to work on an example where we need to push 100Million messages to Cosmos and the solution is supposed to be deployed on RTF on Azure. Batch process supports persistent queues and I don't see any settings that can help configuring external queues for persistence as Pods may crash and the persistent files will be lost.

Are there any other alternatives for this other than batch job? If we use Parallel for each, that works as splitter and aggregator and it is not efficient.

Any suggestions are appreciated.

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Persistent queues are a feature only for Anypoint Platforms CloudHub deployments and are not available for Anypoint Runtime Fabric. Even in CloudHub they are guaranteed to provide reliability of Mule batch processes (see this KB for more information). Assume that a crash will restart the worker or pod respectively and the batch queues and stores may be lost.