Querying Service Monitoring Details¶
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¶
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 |
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 |