Bypassing nvmsgconv & kafka python

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) GPU
• DeepStream Version 6.4
• JetPack Version (valid for Jetson only)
• TensorRT Version 8.6.1.6
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs) question

Following the discussion on the previous topic, I would like to ask how I can pass custom messages (create custom payload without nvmsgconv) to nvmsgbroker directly (is it possible?) , or any alternatives (e.g. use kafka-python directly?
What are the disadvantages in performance/asynchronous processing when not using nvmsgconv&nvmgsbroker?

Thank you for your help.

sorry for the late reply! nvmsgconv is used to convert meta information to Json format, which is added as a new user meta. nvmsgbroker will send this user meta to broker. nvmsgconv plugin and low-level are opensource from DS6.4. nvmsgbroker plugin is opensource. please check the code if interested.

this wound be outside of Deepstream.

Thank you for pointing out that nvmsgbroker & nvmsgconv are open-source. I didn’t notice broker was also open source.

I understand this is outside Deepstream, but I need to know what is the advantage of running the broker as a nv-gst plugin. e.g. Does it execute faster asynchronously? Dies it run in the main process of Gstreamer? Does it have hardware acceleration?

There is no update from you for a period, assuming this is not an issue any more. Hence we are closing this topic. If need further support, please open a new one. Thanks.
please refer to nvmsgbroker reference doc. the advantage is ready-made, supporting many protocols, supporting synchronous /asynchronous mode. if in async mode, it run in the thread gst_nvmsgbroker_do_work. there is no hardware acceleration in nvmsgbroker plugin.

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