proposalbot 7c5b3f5e25 Changes to ma_umn from docs/doc-exports#373 (Another fixes for the conversion

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Reviewed-by: gtema <artem.goncharov@gmail.com>
Co-authored-by: proposalbot <proposalbot@otc-service.com>
Co-committed-by: proposalbot <proposalbot@otc-service.com>

2022-10-24 09:34:01 +00:00

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original_name: modelarts_23_0187.html

ModelArts Metrics

Description

The cloud service platform provides Cloud Eye to help you better understand the status of your ModelArts real-time services and models. You can use Cloud Eye to automatically monitor your ModelArts real-time services and models in real time and manage alarms and notifications, so that you can keep track of performance metrics of ModelArts and models.

Namespace

SYS.ModelArts

Monitoring Metrics

**Table 1** ModelArts metrics
Metric ID	Metric Name	Meaning	Value Range	Measurement Object & Dimension	Monitoring Interval
cpu_usage	CPU Usage	CPU usage of ModelArts Unit: %	>= 0%	Measurement object: ModelArts models Dimension: model_id	1 minute
mem_usage	Memory Usage	Memory usage of ModelArts Unit: %	>= 0%	Measurement object: ModelArts models Dimension: model_id	1 minute
gpu_util	GPU Usage	GPU usage of ModelArts Unit: %	>= 0%	Measurement object: ModelArts models Dimension: model_id	1 minute
successfully_called_times	Number of Successful Calls	Times that ModelArts has been successfully called Unit: Times/min	>=Count/min	Measurement object: ModelArts models ModelArts real-time services Dimension: model_id, service_id	1 minute
failed_called_times	Number of Failed Calls	Times that ModelArts failed to be called Unit: Times/min	>=Count/min	Measurement object: ModelArts models ModelArts real-time services Dimension: model_id, service_id	1 minute
total_called_times	API Calls	Times that ModelArts is called Unit: Times/min	>=Count/min	Measurement object: ModelArts models ModelArts real-time services Dimension: model_id, service_id	1 minute
If a measurement object has multiple measurement dimensions, all the measurement dimensions are mandatory when you use an API to query monitoring metrics. The following provides an example of using the multi-dimensional dim to query a single monitoring metric: dim.0=service_id,530cd6b0-86d7-4818-837f-935f6a27414d&dim.1="model_id,3773b058-5b4f-4366-9035-9bbd9964714a The following provides an example of using the multi-dimensional dim to query monitoring metrics in batches: "dimensions": [ { "name": "service_id", "value": "530cd6b0-86d7-4818-837f-935f6a27414d" } { "name": "model_id", "value": "3773b058-5b4f-4366-9035-9bbd9964714a" } ],

Dimensions

**Table 2** Dimension description
Key	Value
service_id	Real-time service ID
model_id	Model ID

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