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Help Center/ ModelArts/ ModelArts User Guide (Standard)/ Inference Deployment/ Managing a Synchronous Real-Time Service/ Viewing Performance Metrics of a Real-Time Service on Cloud Eye

Viewing Performance Metrics of a Real-Time Service on Cloud Eye

Updated on 2024-12-26 GMT+08:00

ModelArts Metrics

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

Table 1 ModelArts metrics

ID

Name

Description

Value Range

Monitored Object

Monitoring Interval

cpu_usage

CPU Usage

CPU usage of ModelArts

Unit: %

≥ 0%

ModelArts model loads

1 minute

mem_usage

Memory Usage

Memory usage of ModelArts

Unit: %

≥ 0%

ModelArts model loads

1 minute

gpu_util

GPU Usage

GPU usage of ModelArts

Unit: %

≥ 0%

ModelArts model loads

1 minute

gpu_mem_usage

GPU Memory Usage

GPU memory usage of ModelArts

Unit: %

≥ 0%

ModelArts model loads

1 minute

npu_util

NPU Usage

NPU usage of ModelArts

Unit: %

≥ 0%

ModelArts model loads

1 minute

npu_mem_usage

NPU Memory Usage

NPU memory usage of ModelArts

Unit: %

≥ 0%

ModelArts model loads

1 minute

successfully_called_times

Number of Successful Calls

Times that ModelArts services have been successfully called

Unit: counts/minute

≥ counts/minute

ModelArts model loads

ModelArts real-time services

1 minute

failed_called_times

Number of Failed Calls

Times that ModelArts services failed to be called

Unit: counts/minute

≥ counts/minute

ModelArts model loads

ModelArts real-time services

1 minute

total_called_times

Total Calls

Times that ModelArts services are called

Unit: counts/minute

≥ counts/minute

ModelArts model loads

ModelArts real-time services

1 minute

disk_read_rate

Disk Read Rate

Disk read rate of ModelArts

Unit: bit/minute

≥ bit/minute

ModelArts model loads

1 minute

disk_write_rate

Disk Write Rate

Disk write rate of ModelArts

Unit: bit/minute

≥ bit/minute

ModelArts model loads

1 minute

send_bytes_rate

Uplink rate

Outbound network traffic rate of ModelArts.

Unit: bit/minute

≥ bit/minute

ModelArts model loads

1 minute

recv_bytes_rate

Downlink rate

Inbound network traffic rate of ModelArts.

≥ bit/minute

ModelArts model loads

1 minute

req_count_2xx

2xx Responses

Number of times that the API returns a 2xx response

≥ counts/minute

ModelArts real-time services

1 minute

req_count_4xx

4xx Errors

Number of times that the API returns a 4xx error

≥ counts/minute

ModelArts real-time services

1 minute

req_count_5xx

5xx Errors

Number of times that the API returns a 5xx error

≥ counts/minute

ModelArts real-time services

1 minute

avg_latency

Average Latency

Average latency of the API

≥ ms

ModelArts real-time services

1 minute

tp_99

TP99

Collects the response durations of each call over the last minute, arranges them in ascending order, and then excludes the top 1% of values. The highest remaining value represents the TP99.

≥ ms

ModelArts real-time services

1 minute

tp_999

TP99.9

Collects the response durations of each call over the last minute, arranges them in ascending order, and then excludes the top 0.1% of values. The highest remaining value represents the TP99.9.

≥ ms

ModelArts real-time services

1 minute

If a monitored object has multiple dimensions, all dimensions are mandatory when you use APIs to query the 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"

    }

    ]

Table 2 Dimension description

Key

Value

service_id

Real-time service ID

model_id

Model ID

Setting Alarm Rules

Setting alarm rules allows you to customize the monitored objects and notification policies so that you can know the status of ModelArts real-time services and models in a timely manner.

An alarm rule includes the alarm rule name, monitored object, metric, threshold, monitoring interval, and whether to send a notification. This section describes how to set alarm rules for ModelArts services and models.

NOTE:

Only real-time services in the Running status can be interconnected with CES.

Prerequisites:

  • A ModelArts real-time service has been created.
  • ModelArts monitoring has been enabled on Cloud Eye. To do so, log in to the Cloud Eye console. On the Cloud Eye page, click Custom Monitoring. Then, enable ModelArts monitoring as prompted.

Set an alarm rule in any of the following ways:

  • Set an alarm rule for all ModelArts services.
  • Set an alarm rule for a ModelArts service.
  • Set an alarm rule for a model version.
  • Set an alarm rule for a metric of a service or model version.

Method 1: Setting an Alarm Rule for All ModelArts Services

  1. Log in to the management console.
  2. In the Service List, click Cloud Eye under Management & Governance.
  3. In the navigation pane on the left, choose Alarm Management > Alarm Rules and click Create Alarm Rule.
  4. On the Create Alarm Rule page, set Resource Type to ModelArts, Dimension to Service, and Method to Configure manually, and set alarm policies. Then, confirm settings and click Create.

Method 2: Setting an Alarm Rule for a Single Service

  1. Log in to the management console.
  2. In the Service List, click Cloud Eye under Management & Governance.
  3. In the navigation pane, choose Cloud Service Monitoring > ModelArts.
  4. Locate a real-time service for which you want to create an alarm rule and click Create Alarm Rule in the Operation column.
  5. On the Create Alarm Rule page, create an alarm rule for ModelArts real-time services and models as prompted.

Method 3: Setting an Alarm Rule for a Model Version

  1. Log in to the management console.
  2. In the Service List, click Cloud Eye under Management & Governance.
  3. In the navigation pane, choose Cloud Service Monitoring > ModelArts.
  4. Click the down arrow next to the target real-time service name. Then, click Create Alarm Rule in the Operation column of the target version.
  5. On the Create Alarm Rule page, create an alarm rule for model loads as prompted.

Method 4: Setting an Alarm Rule for a Metric of a Service or Model Version

  1. Log in to the management console.
  2. In the Service List, click Cloud Eye under Management & Governance.
  3. In the navigation pane, choose Cloud Service Monitoring > ModelArts.
  4. Click the down arrow next to the target real-time service name. Then, click the target version and view alarm rule details.
  5. On the alarm rule details page, click the plus sign (+) in the upper right corner of a metric and set an alarm rule for the metric.

Viewing Monitoring Metrics

Cloud Eye on the cloud service platform monitors the statuses of ModelArts real-time services and model loads. You can obtain the monitoring metrics of each ModelArts real-time service and model on the management console. It takes a period of time to transmit and display monitored data. The statuses displayed on the Cloud Eye console are obtained 5 to 10 minutes before. You can view the monitoring data of a newly created real-time service 5 to 10 minutes later.

Prerequisites:

  • The ModelArts real-time service is running properly.
  • Alarm rules have been configured on the Cloud Eye page. For details, see Setting Alarm Rules.
  • The real-time service has been properly running for at least 10 minutes.
  • The monitored data and graphics are available for a new real-time service after the service runs for at least 10 minutes.
  • Cloud Eye does not display the metrics of a faulty or deleted real-time service. The monitoring metrics can be viewed after the real-time service starts or recovers.

The monitoring data is unavailable without alarm rules configured in Cloud Eye. For details, see Setting Alarm Rules.

  1. Log in to the management console.
  2. In the Service List, click Cloud Eye under Management & Governance.
  3. In the navigation pane, choose Cloud Service Monitoring > ModelArts.
  4. View monitoring graphs.

    • Viewing monitoring graphs of a real-time service: Click View Metric in the Operation column.
    • Viewing monitoring graphs of the model loads: Click next to the target real-time service, and click View Metric in the Operation column of the target model.

  5. In the monitoring area, you can select a period to view the monitoring data.

    You can view the monitoring data in the last 1 hour, 3 hours, or 12 hours. To view the monitoring curve of a longer time range, click to enlarge the graph.

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