can you tell me what the serving example is in terms of the explanation above and what the triton serving engine is,

Great idea!

This line actually creates the control Task (2)
clearml-serving triton --project "serving" --name "serving example"
This line configures the control Task (the idea is that you can do that even when the control Task is already running, but in this case it is still in draft mode).
Notice the actual model serving configuration is already stored on the creating Task/Model. Otherwise you have to explicitly provide configuration on the model serving, i.e. input matrix size type etc. this is the configpb.txt file, example [ https://github.com/allegroai/clearml-serving/blob/7c1c02c9ea49c9ee6ffbdd5b59f5fd8a6f78b4e0/examples/keras/keras_mnist.py#L51 ])
clearml-serving triton --endpoint "keras_mnist" --model-project "examples" --model-name "Keras MNIST serve example - serving_model"
Then you launch the control Task (2) (this is the one we just configured, by default it qwill launch on the services queue, you can also spin an additional agent to listen to the services queue).
The control Task is actually the Task that creates the serving Task, and enqueues it.
(The idea is that it will do auto load balancing, based on serving performance, right now it is still static).
To control the way the serving Task is created and enqueued , check the full help:
` clearml-serving --help

clearml-serving triton --help `