Thanks to all the people who attended my talk "The Journey to TensorFlow on the JVM Stack" at the Google I/O Extended 2018 in Dublin. The slide deck is available on my SlideShare space. More code examples would be available on this blog in the next months.
In order to show that the considerations done in my last post are general for any log shipping purpose, let's see now how the same process applies to a more real use case scenario: the log shipping and analysis of a MongoDB database logs. MongoDB logs pattern Starting from the release 3.0 (I am considering the release 3.2 for this post) the MongoDB logs come with the following pattern: <timestamp> <severity> <component> [<context>] <message> where: timestamp is in iso8601-local format. severity is the level associated to each log message. It is a single character field. Possible values are F (Fatal), E (Error), W (Warning), I (Informational) and D (Debug). component is for a functional categorization of the log message. Please refer to the specific release of MongoDB you're using to know the full list of possible values. context is the specific context for a me...

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