Custom batch job instance IDs in Mule 3.8

Welcome to the final post in the three post series about batch improvements on Mule 3.8!

The last new feature we have is a simple one which comes quite handy when you need to read through logs. As you know, batch jobs are just programs processed in batch mode, and each time the job is triggered, a new job instance is created and tracked separately. Each of those instances is unique and therefore has a unique ID.

Mr. Batch and the Quest for the right Threading Profile

Sometimes (more often than we think), less concurrency is actually more. Not too long ago, I found myself in a conversation in which we were discussing non-blocking architectures, tuning, and performance. We were discussing that tuning for those models often starts with “2 threads per core” (2TPC). The discussion made me curious about how Mule’s batch module would perform if tested by 2TPC. I knew beforehand that 2TPC wouldn’t be so impressive on batch, mainly because it doesn’t use a non-blocking threading model.

Handle Errors in your Batch Job… Like a Champ!

Fact: Batch Jobs are tricky to handle when exceptions raise. The problem is the huge amounts of data that these jobs are designed to take. If you’re processing 1 million records you simply can’t log everything. Logs would become huge and unreadable. Not to mention the performance toll it would take. On the other hand, if you log too little then it’s impossible to know what went wrong, and if 30 thousand records failed, not knowing what’s wrong with them can be a royal pain.

Anypoint Platform May 2014 now available!

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We’re very excited to announce the May 2014 release of Anypoint Platform.  This new release, which includes the GA release of Mule 3.5.0, provides a faster, easier way to deliver data to business applications, whether they are event-driven, real-time data or batch data. The Anypoint Platform May 2014 release also includes templates to solve the most common Salesforce integration challenges and new security certifications for CloudHub,