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Introduction In Part 1, you learned why an edge AI inference pipeline is a compelling approach for security operations, and you understood the key constraints imposed by the Jetson Nano 4GB hardware and DSDL 5.2.3’s actual behavior. In this post, you will build the inference container – every file, every command, and every decision explained. The build covers four areas: the Dockerfile and its critical dependencies, the DSDL-native Flask application that implements the correct wire protocol, TLS certificate generation using a lab CA, and the distribution workflow for deploying the finished image to all four nodes. ...

Introduction In Part 2, you built four HTTPS inference containers running on Jetson Nano hardware. They are healthy, serving the DSDL-native protocol, and waiting for requests. In this post, you will wire everything together: Splunk DSDL installed on the search head, HEC configured on the indexer cluster, and the exact configuration files that make DSDL’s fit and apply commands route correctly to your containers. This is the most configuration-dense part of the series. It is also where most implementations break down – not because the concepts are complex, but because DSDL 5.2.3 has several undocumented behaviors that only become visible when you read its Python source code. This post documents those behaviors explicitly so you do not have to discover them through trial and error. ...