Classification flow
This is a flow that implements a classification algorithm. This algorithm compares the distance between the three centroids given from the K-means clustering flow and the values inside function object. So like the the flow mentioned above it's possible to run this flow ether as a node red flow or as a Openwhisk function.
Example input
{
"function": {
"owendpoint": "cluster.url",
"actionname": "Inference_3fff08e8-3617-4eb4-b118-4229f30514e3.json",
"cpu": 0.28138695097583194,
"branchname": "Inference",
"flow": "Inference",
"memory": 74014720,
"networkReceived": 131.45833333333331,
"networkTransmitted": 279.4666666666667,
"fsReads": 70729728,
"fsWrites": 28672
},
"cluster": {
"cpu": [
{
"category": "low",
"value": 0.005801420285783651
},
{
"category": "medium",
"value": 0.029655391993717292
},
{
"category": "high",
"value": 0.1852146552507543
}
],
"memory": [
{
"category": "low",
"value": 22821091.555555556
},
{
"category": "medium",
"value": 27701589.333333332
},
{
"category": "high",
"value": 47930026.666666664
}
],
"fsWrites": [
{
"category": "low",
"value": 20480
},
{
"category": "medium",
"value": 285696
},
{
"category": "high",
"value": 454656
}
],
"networkTransmitted": [
{
"category": "low",
"value": 196.98828026984765
},
{
"category": "medium",
"value": 359.94572729706005
},
{
"category": "high",
"value": 495.8401658633009
}
],
"fsReads": [
{
"category": "low",
"value": 12274688
},
{
"category": "medium",
"value": 1494016
},
{
"category": "high",
"value": 49229824
}
],
"networkReceived": [
{
"category": "low",
"value": 173.3337710628692
},
{
"category": "medium",
"value": 663.1380479260863
},
{
"category": "high",
"value": 983.7239894223181
}
]
}
}
In the function object Prometheus performance metrics get inserted and the cluster contains the output of the clustering function
Example output
{
"cpu": "high",
"flow": "Inference",
"fsReads": "high",
"fsWrites": "low",
"memory": "high",
"networkReceived": "low",
"networkTransmitted": "medium"
}
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