You can use the API to query the monitoring information about a service.

Sample Code

In the ModelArts notebook instance, you do not need to enter authentication parameters for session authentication. For details about session authentication of other development environments, see Session Authentication.

Method 1: Query the monitoring information about the service created in Deploying a Real-Time Service.

from modelarts.session import Session
from modelarts.model import Predictor
session = Session()
predictor_instance = Predictor(session, service_id="input your service_id")
predictor_monitor = predictor_instance.get_service_monitor() 

Method 2: Query the monitoring information about the service object returned in Querying the List of Service Objects.

from modelarts.session import Session
from modelarts.model import Predictor
session = Session()
predictor_object_list = Predictor.get_service_object_list(session)
predictor_instance = predictor_object_list[0]                
predictor_monitor = predictor_instance.get_service_monitor()

Parameter Description

**Table 1** **get_service_monitor** response parameters
Parameter	Type	Description
service_id	String	Service ID
service_name	String	Service name
monitors	monitor array corresponding to infer_type of a service	Monitoring details

**Table 2** **monitor** parameters corresponding to **real-time**
Parameter	Type	Description
model_id	String	Model ID
model_name	String	Model name
model_version	String	Model version
invocation_times	Number	Total number of model instance calls
failed_times	Number	Number of failed model instance calls
cpu_core_usage	Float	Number of used CPUs
cpu_core_total	Float	Total number of CPUs
cpu_memory_usage	Integer	Used memory, in MBs
cpu_memory_total	Integer	Total memory, in MBs
gpu_usage	Float	Number of used GPUs
gpu_total	Float	Total number of GPUs

Querying Service Monitoring Details

Sample Code

Parameter Description