GoogleCloudMlV1__AutoScalingArgs

data class GoogleCloudMlV1__AutoScalingArgs(val maxNodes: Output<Int>? = null, val metrics: Output<List<GoogleCloudMlV1__MetricSpecArgs>>? = null, val minNodes: Output<Int>? = null) : ConvertibleToJava<GoogleCloudMlV1__AutoScalingArgs>

Options for automatically scaling a model.

Constructors

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fun GoogleCloudMlV1__AutoScalingArgs(maxNodes: Output<Int>? = null, metrics: Output<List<GoogleCloudMlV1__MetricSpecArgs>>? = null, minNodes: Output<Int>? = null)

Functions

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open override fun toJava(): GoogleCloudMlV1__AutoScalingArgs

Properties

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val maxNodes: Output<Int>? = null

The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.

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MetricSpec contains the specifications to use to calculate the desired nodes count.

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val minNodes: Output<Int>? = null

Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least rate * min_nodes * number of hours since last billing cycle, where rate is the cost per node-hour as documented in the /ml-engine/docs/pricing, even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least min_nodes. You will be charged for the time in which additional nodes are used. If min_nodes is not specified and AutoScaling is used with a /ml-engine/docs/machine-types-online-prediction, min_nodes defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If min_nodes is not specified and AutoScaling is used with a /ml-engine/docs/machine-types-online-prediction, min_nodes defaults to 1. min_nodes must be at least 1 for use with a Compute Engine machine type. You can set min_nodes when creating the model version, and you can also update min_nodes for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json //*/