Help Center/ ModelArts/ API Reference/ Service Management/ Deploying Services

Updated on 2024-05-30 GMT+08:00

View PDF

Deploying Services

Function

This API is used to deploy a model as a service.

Debugging

You can debug this API through automatic authentication in API Explorer or use the SDK sample code generated by API Explorer.

URI

POST /v1/{project_id}/services

**Table 1** Path Parameters
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details, see Obtaining a Project ID and Name.

Request Parameters

**Table 2** Request header parameters
Parameter	Mandatory	Type	Description
X-Auth-Token	Yes	String	User token. It can be obtained by calling the IAM API that is used to obtain a user token. The value of X-Subject-Token in the response header is the user token.

**Table 3** Request body parameters
Parameter	Mandatory	Type	Description
workspace_id	No	String	ID of the workspace to which a service belongs. The default value is 0, indicating the default workspace.
schedule	No	Array of Schedule objects	Service scheduling configuration, which can be configured only for real-time services. By default, this parameter is not used. Services run for a long time.
cluster_id	No	String	Dedicated resource pool ID. By default, this parameter is left blank, indicating that dedicated resource pools are not used. When using a dedicated resource pool to deploy services, ensure that the cluster is running properly. After this parameter is configured, the network configuration of the cluster is used, and the vpc_id parameter does not take effect. If both this parameter and cluster_id in real-time config are configured, cluster_id in real-time config is preferentially used. If a dedicated resource pool is used, either cluster_id or pool_name must be specified.
pool_name	No	String	ID of a new-version dedicated resource pool. This parameter is left blank by default, indicating that no dedicated resource pool is used. When using a dedicated resource pool to deploy services, ensure that the cluster is running properly. If both this parameter and pool_name in real-time config are configured, pool_name in real-time config is preferentially used. If a dedicated resource pool is used, either cluster_id or pool_name must be specified.
infer_type	Yes	String	Inference mode. The value is real-time/batch/edge. real-time indicates a real-time service. A model is deployed as a web service. Service, which provides online test UI and monitoring capabilities. The service keeps running. Batch is a batch service. A batch service can perform inference on batch data and automatically stops after data processing is complete. edge indicates an edge service. A model is deployed as a web on an edge node through Intelligent EdgeFabric (IEF). Service. The node must be created on Intelligent EdgeFabric (IEF) in advance.
vpc_id	No	String	ID of the VPC to which a real-time service instance is deployed. By default, this parameter is left blank. In this case, ModelArts allocates a dedicated VPC to each user, and users are isolated from each other. To access other service components in the VPC of the service instance, set this parameter to the ID of the corresponding VPC. Once a VPC is configured, it cannot be modified. If both vpc_id and cluster_id are configured, only the dedicated resource pool takes effect.
service_name	Yes	String	Service name, which consists of 1 to 64 characters. Only letters, digits, hyphens (-), and underscores (_) are allowed.
description	No	String	Service remarks. By default, this parameter is left blank. The value contains a maximum of 100 characters and cannot contain!. < > + &"'
security_group_id	No	String	Security group. By default, this parameter is left blank. This parameter is mandatory if vpc_id is configured. A security group is a virtual firewall that provides secure network access control policies for service instances. A security group must contain at least one inbound rule to permit the requests whose protocol is TCP, source address is 0.0.0.0/0, and port number is 8080.
subnet_network_id	No	String	ID of a subnet. By default, this parameter is left blank. This parameter is mandatory if vpc_id is configured. Enter the network ID displayed in the subnet details on the VPC management console. A subnet provides dedicated network resources that are isolated from other networks.
config	Yes	Array of ServiceConfig objects	Model running configurations. If infer_type is batch or edge, you can configure only one model. If infer_type is real-time, you can configure multiple models and assign weights based on service requirements. However, the versions of multiple models must be unique.
additional_properties	No	Map<String,ServiceAdditionalProperties>	Additional service attribute, which facilitates service management

**Table 4** Schedule
Parameter	Mandatory	Type	Description
duration	Yes	Integer	Value mapping a time unit. For example, if the task stops after two hours, set time_unit to HOURS and duration to 2.
time_unit	Yes	String	Scheduling time unit. Possible values are DAYS, HOURS, and MINUTES.
type	Yes	String	Scheduling type. Only the value stop is supported.

**Table 5** ServiceConfig
Parameter	Mandatory	Type	Description
custom_spec	No	CustomSpec object	Custom resource specifications
envs	No	Map<String,String>	Common parameter. (Optional) Environment variable key-value pair required for running a model. By default, this parameter is left blank.
specification	Yes	String	Common parameter. Resource flavor. You can query the supported service deployment flavors. The current version supports modelarts.vm.cpu.2u, modelarts.vm.gpu.pnt004 (must be requested), modelarts.vm.ai1.snt3 (must be requested), and custom (available only when the service is deployed in a dedicated resource pool). To request a flavor, submit a service ticket and obtain permissions from ModelArts O&M engineers. If this parameter is set to custom, the custom_spec parameter must be specified.
weight	No	Integer	This parameter is mandatory for real-time. Weight of traffic allocated to a model. This parameter is mandatory only when infer_type is set to real-time. The sum of all weights must be equal to 100. If multiple model versions are configured with different traffic weights in a real-time service, ModelArts will continuously access the prediction API of the service and forward prediction requests to the model instances of the corresponding versions based on the weights.
deploy_timeout_in_seconds	No	Integer	Timeout interval for deploying a single model instance
model_id	Yes	String	Common parameters Model ID. You can obtain the value by calling the API for querying the AI application list.
src_path	No	String	Mandatory for batch services. OBS path to the input data of a batch job
req_uri	No	String	Mandatory for batch services. Inference API called in a batch task, which is the RESTful API exposed in the model image. You must select an API URL from the config.json file of the model for inference. If a built-in inference image of ModelArts is used, the API is displayed as /.
mapping_type	No	String	The batch service type is mandatory. Mapping type of the input data. The value can be file or csv. If file is selected, each inference request corresponds to a file in the input data directory. When this mode is used, req_uri corresponding to the model can have only one input parameter and the parameter type is file. If csv is selected, each inference request corresponds to a row of data in the CSV file. If this mode is used, the file name extension in the input data directory must be .csv, and the mapping_rule parameter must be configured to indicate the CSV index corresponding to each parameter in the inference request body.
cluster_id	No	String	Optional for real-time services. ID of a dedicated resource pool. This parameter is left blank by default, indicating that no dedicated resource pool is used. When using a dedicated resource pool to deploy services, ensure that the resource pool is running properly. After this parameter is configured, the network configuration of the cluster is used, and the vpc_id parameter does not take effect.
pool_name	No	String	Specifies the ID of the new dedicated resource pool. By default, this parameter is left blank, indicating that the dedicated resource pool is not used. This parameter corresponds to the ID of the new resource pool. When using dedicated resource pool to deploy services, ensure that the cluster status is normal. If pool_name in real-time config and pool_name in real-time config are configured at the same time, pool_name in real-time config is preferred.
nodes	No	Array of strings	Mandatory for edge services. Edge node ID array. The node ID is the edge node ID on IEF, which can be obtained after the edge node is created on IEF.
mapping_rule	No	Object	Optional for batch services. Mapping between input parameters and CSV data. This parameter is mandatory only when mapping_type is set to csv. The mapping rule is similar to the definition of the input parameters in the config.json file. You only need to configure the index parameters under each parameter of the string, number, integer, or boolean type, and specify the value of this parameter to the values of the index parameters in the CSV file to send an inference request. Use commas (,) to separate multiple pieces of CSV data. The values of the index parameters start from 0. If the value of the index parameter is -1, ignore this parameter. For details, see the sample of creating a batch service.
src_type	No	String	Mandatory for batch services. Data source type, which can be ManifestFile. By default, this parameter is left blank, indicating that only files in the src_path directory are read. If this parameter is set to ManifestFile, src_path must be set to a specific manifest path. Multiple data paths can be specified in the manifest file. For details, see the manifest inference specifications.
dest_path	No	String	Mandatory for batch services. OBS path to the output data of a batch job
instance_count	Yes	Integer	Common parameter. Number of instances deployed in a model. The maximum number of instances is 128. To use more instances, submit a service ticket.
additional_properties	No	Map<String,ModelAdditionalProperties>	Additional attributes for model deployment, facilitating service instance management

**Table 6** CustomSpec
Parameter	Mandatory	Type	Description
gpu_p4	No	Float	Number of GPUs, which can be a decimal. The value cannot be smaller than 0, with the third decimal place is rounded off. This parameter is optional and is not used by default.
memory	Yes	Integer	Memory in MB, which must be an integer
cpu	Yes	Float	Number of CPU cores, which can be a decimal. The value cannot be smaller than 0.01, with the third decimal place is rounded off.
ascend_a310	No	Integer	Number of Ascend chips. This parameter is optional and is not used by default. Either this parameter or gpu is configured.

**Table 7** ModelAdditionalProperties
Parameter	Mandatory	Type	Description
log_volume	No	Array of log_volume objects	Host directory mounting. This parameter takes effect only if a dedicated resource pool is used. If a public resource pool is used to deploy services, this parameter cannot be configured. Otherwise, an error will occur.
max_surge	No	Float	The value must be greater than 0. If this parameter is not set, the default value 1 is used. If the value is less than 1, it indicates the percentage of instances to be added during the rolling upgrade. If the value is greater than 1, it indicates the maximum number of instances to be added during the rolling upgrade.
max_unavailable	No	Float	The value must be greater than 0. If this parameter is not set, the default value 0 is used. If the value is less than 1, it indicates the percentage of instances that can be scaled in during the rolling upgrade. If the value is greater than 1, it indicates the number of instances that can be scaled in during the rolling upgrade.
termination_grace_period_seconds	No	Integer	Graceful stop period of a container.
persistent_volumes	No	Array of persistent_volumes objects	Persistent storage mounting.

**Table 8** log_volume
Parameter	Mandatory	Type	Description
host_path	Yes	String	Log path to be mapped on the host
mount_path	Yes	String	Path to the logs in the container

**Table 9** persistent_volumes
Parameter	Mandatory	Type	Description
name	No	String	Volume name.
mount_path	Yes	String	Mount path of a volume in the container.

**Table 10** ServiceAdditionalProperties
Parameter	Mandatory	Type	Description
smn_notification	Yes	Map<String,SmnNotification>	SMN message notification structure, which is used to notify the user of the service status change
log_report_channels	No	Array of LogReportPipeline objects	Log channel group. If this parameter is not specified or the array length is 0, LTS log interconnection is disabled. This function cannot be modified after being enabled.
websocket_upgrade	No	Boolean	Whether the service interface is upgraded to WebSocket. During service deployment, the default value is false. During service configuration update, the default value is the value set last time. false: Do not upgrade to WebSocket. true: Upgrade to WebSocket. This parameter cannot be modified after WebSocket is enabled. WebSocket cannot be enabled together with Traffic Limit.

**Table 11** SmnNotification
Parameter	Mandatory	Type	Description
topic_urn	Yes	String	URN of an SMN topic
events	Yes	Array of integers	Event ID. The options are as follows: 1: failed 3: running 7: concerning 11: pending

**Table 12** LogReportPipeline
Parameter	Mandatory	Type	Description
type	Yes	String	Log pipeline type. Currently, only LTS is supported.
configuration	No	LtsConfiguration object	LTS log configuration.

**Table 13** LtsConfiguration
Parameter	Mandatory	Type	Description
log_group_id	Yes	String	LTS log group ID. The value contains 64 characters.
log_stream_id	Yes	String	LTS log stream ID. The value contains 64 characters.

Response Parameters

Status code: 200

**Table 14** Response body parameters
Parameter	Type	Description
service_id	String	Service ID
resource_ids	Array of strings	Resource ID array for the resource IDs generated by the target model

Example Requests

Sample request of creating a real-time service

POST https://{endpoint}/v1/{project_id}/services

{
  "infer_type" : "real-time",
  "service_name" : "mnist",
  "description" : "mnist service",
  "config" : [ {
    "specification" : "modelarts.vm.cpu.2u",
    "weight" : 100,
    "model_id" : "0e07b41b-173e-42db-8c16-8e1b44cc0d44",
    "instance_count" : 1
  } ]
}

Create a real-time service and configure multi-version traffic distribution.

POST https://{endpoint}/v1/{project_id}/services

{
  "service_name" : "mnist",
  "description" : "mnist service",
  "infer_type" : "real-time",
  "config" : [ {
    "model_id" : "xxxmodel-idxxx",
    "weight" : "70",
    "specification" : "modelarts.vm.cpu.2u",
    "instance_count" : 1,
    "envs" : {
      "model_name" : "mxnet-model-1",
      "load_epoch" : "0"
    }
  }, {
    "model_id" : "xxxxxx",
    "weight" : "30",
    "specification" : "modelarts.vm.cpu.2u",
    "instance_count" : 1
  } ]
}

Create a real-time service in a dedicated resource pool with custom specifications.

POST https://{endpoint}/v1/{project_id}/services

{
  "service_name" : "realtime-demo",
  "description" : "",
  "infer_type" : "real-time",
  "cluster_id" : "8abf68a969c3cb3a0169c4acb24b0000",
  "config" : [ {
    "model_id" : "eb6a4a8c-5713-4a27-b8ed-c7e694499af5",
    "weight" : "100",
    "cluster_id" : "8abf68a969c3cb3a0169c4acb24b0000",
    "specification" : "custom",
    "custom_spec" : {
      "cpu" : 1.5,
      "memory" : 7500
    },
    "instance_count" : 1
  } ]
}

Create a real-time service and configure it to automatically stop.

POST https://{endpoint}/v1/{project_id}/services

{
  "service_name" : "service-demo",
  "description" : "demo",
  "infer_type" : "real-time",
  "config" : [ {
    "model_id" : "xxxmodel-idxxx",
    "weight" : "100",
    "specification" : "modelarts.vm.cpu.2u",
    "instance_count" : 1
  } ],
  "schedule" : [ {
    "type" : "stop",
    "time_unit" : "HOURS",
    "duration" : 1
  } ]
}

Create a batch service and set mapping_type to file.

POST https://{endpoint}/v1/{project_id}/services

{
  "service_name" : "batchservicetest",
  "description" : "",
  "infer_type" : "batch",
  "cluster_id" : "8abf68a969c3cb3a0169c4acb24b****",
  "config" : [ {
    "model_id" : "598b913a-af3e-41ba-a1b5-bf065320f1e2",
    "specification" : "modelarts.vm.cpu.2u",
    "instance_count" : 1,
    "src_path" : "https://infers-data.obs.xxxxx.com/xgboosterdata/",
    "dest_path" : "https://infers-data.obs.xxxxx.com/output/",
    "req_uri" : "/",
    "mapping_type" : "file"
  } ]
}

Create a batch service and set mapping_type to csv.

POST https://{endpoint}/v1/{project_id}/services

{
  "service_name" : "batchservicetest",
  "description" : "",
  "infer_type" : "batch",
  "config" : [ {
    "model_id" : "598b913a-af3e-41ba-a1b5-bf065320f1e2",
    "specification" : "modelarts.vm.cpu.2u",
    "instance_count" : 1,
    "src_path" : "https://infers-data.obs.xxxxx.com/xgboosterdata/",
    "dest_path" : "https://infers-data.obs.xxxxx.com/output/",
    "req_uri" : "/",
    "mapping_type" : "csv",
    "mapping_rule" : {
      "type" : "object",
      "properties" : {
        "data" : {
          "type" : "object",
          "properties" : {
            "req_data" : {
              "type" : "array",
              "items" : [ {
                "type" : "object",
                "properties" : {
                  "input5" : {
                    "type" : "number",
                    "index" : 0
                  },
                  "input4" : {
                    "type" : "number",
                    "index" : 1
                  },
                  "input3" : {
                    "type" : "number",
                    "index" : 2
                  },
                  "input2" : {
                    "type" : "number",
                    "index" : 3
                  },
                  "input1" : {
                    "type" : "number",
                    "index" : 4
                  }
                }
              } ]
            }
          }
        }
      }
    }
  } ]
}

Create an edge service.

POST https://{endpoint}/v1/{project_id}/services

{
  "service_name" : "service-edge-demo",
  "description" : "",
  "infer_type" : "edge",
  "config" : [ {
    "model_id" : "eb6a4a8c-5713-4a27-b8ed-c7e694499af5",
    "specification" : "custom",
    "instance_count" : 1,
    "custom_spec" : {
      "cpu" : 1.5,
      "memory" : 7500
    },
    "envs" : { },
    "nodes" : [ "2r8c4fb9-t497-40u3-89yf-skui77db0472" ]
  } ]
}

Example Responses

Status code: 200

Service deployed

{
  "service_id" : "10eb0091-887f-4839-9929-cbc884f1e20e",
  "resource_ids" : [ "INF-f878991839647358@1598319442708" ]
}

Status Codes

Status Code	Description
200	Service deployed

Error Codes

See Error Codes.

Parent topic: Service Management

Previous topic: Obtaining Services

Next topic: Obtaining Supported Service Deployment Specifications

Feedback

Was this page helpful?

Helpful Not helpful

Provide feedback

Thank you very much for your feedback. We will continue working to improve the documentation.See the reply and handling status in My Cloud VOC.

The system is busy. Please try again later.

Which of the following issues have you encountered?

Content is inconsistent with the product UI

Unclear descriptions

Lack of examples or code

Incorrect steps

Can't find what I need

Lack of best practices

Feedback (optional)

0/500

Select at least one type of issue, and enter your comments or suggestions.

Enter a maximum of 500 characters.

Submit Cancel

For any further questions, feel free to contact us through the chatbot.

Chatbot