CreateService - Platform For AI - Alibaba Cloud Documentation Center

Creates a model service in Elastic Algorithm Service (EAS).

Operation description

**Before you call this operation, make sure that you are familiar with the billing of Elastic Algorithm Service (EAS).

Debugging

You can run this interface directly in OpenAPI Explorer, saving you the trouble of calculating signatures. After running successfully, OpenAPI Explorer can automatically generate SDK code samples.

Debug

Authorization information

The following table shows the authorization information corresponding to the API. The authorization information can be used in the Action policy element to grant a RAM user or RAM role the permissions to call this API operation. Description:

Operation: the value that you can use in the Action element to specify the operation on a resource.
Access level: the access level of each operation. The levels are read, write, and list.
Resource type: the type of the resource on which you can authorize the RAM user or the RAM role to perform the operation. Take note of the following items:
- The required resource types are displayed in bold characters.
- If the permissions cannot be granted at the resource level, All Resources is used in the Resource type column of the operation.
Condition Key: the condition key that is defined by the cloud service.
Associated operation: other operations that the RAM user or the RAM role must have permissions to perform to complete the operation. To complete the operation, the RAM user or the RAM role must have the permissions to perform the associated operations.

Operation	Access level	Resource type	Condition key	Associated operation
eas:CreateService	create	Service `acs:eas:{#regionId}:{#accountId}:service/`	none	none

Request syntax

POST /api/v2/services HTTP/1.1

Request parameters

Parameter	Type	Required	Description	Example
body	string	No	The request body. For more information about the key request parameters, see Table 1. Request body parameters and Table 2. Metadata parameters. For more information about all related parameters, see Parameters of model services.	Service deployment by using an image: { "name": "foo", "metadata": { "instance": 2, "memory": 7000, "cpu": 4 }, "containers": [ { "image": "**", "script": " --listen=0.0.0.0 --server_port=8000 --headless", "port": 8000 } ], "storage": [ { "oss": { "path": "oss://examplebuket/data111/", "readOnly": false }, "properties": { "resource_type": "model" }, "mount_path": "/data" } ] } AI-Web application deployment by using an image: { "name": "foo", "metadata": { "instance": 1, "memory": 7000, "cpu": 4, "enable_webservice": true }, "containers": [ { "image": "", "script": " --listen=0.0.0.0 --server_port=8000 --headless", "port": 8000 } ], "storage": [ { "oss": { "path": "oss://examplebucket/data111/", "readOnly": false }, "properties": { "resource_type": "model" }, "mount_path": "/data" } ] } Service deployment by using models and processors: { "metadata": { "instance": 1, "memory": 7000, "cpu": 4 }, "name": "foo", "model_config": {}, "processor_type": "python", "processor_path": "oss://", "processor_entry": "a.py", "model_path": "oss://**" }
Develop	string	No	Specifies whether to enter development mode. Valid values: true false	true
Labels	object	No	The custom label.
	string	No	The label.	{"key":"value"}
WorkspaceId	string	No	The workspace ID.	123456

Table 1. Request body parameters

Parameter	Type	Required	Description
name	String	Yes	The service name, which must be unique in a region.
token	String	No	The token for authentication. If you do not specify a token and generate_token is set to true, the token is automatically generated.
model_path	String	No	The path of the model file. You can specify an HTTP address or an Object Storage Service (OSS) path. If you specify an HTTP address, the HTTP address must be publicly accessible. If you specify an OSS path, the path can be a directory or file name. If you specify a `.tar.gz`, `.tar.bz2`, or `.zip` file, the system automatically decompresses the file.
role_arn	string	No	If you set model_path or processor_path to an OSS address, you need to specify the role_arn parameter to access OSS and the Role_ARN parameter to obtain the role_arn.
oss_endpoint	String	No	The endpoint of the OSS bucket. If you set model_path or processor_path to an OSS path, you must specify this parameter.
model_entry	String	No	The primary file of the model. Any file can be specified as the primary file of the model. If no file is specified, the file specified by model_path is used as the primary file of the model. The path of the primary file is delivered to the `Load()` function in the processor.
processor_path	String	Yes	The path of the processor file. You can specify a local file or an HTTP address. If you specify a `.tar.gz`, `.tar.bz2`, or `.zip` file, the system automatically decompresses the file.
processor_entry	String	No	If you set processor_type to C, C++, or Python, this parameter is required. The main file of the processor. The main file contains the implementations of the `Load()` and `Process()` functions that are required for prediction.
processor_mainclass	String	No	If you set processor_type to Java, this parameter is required. The main class in the JAR package of the processor.
processor_type	String	Yes	The language that is used to implement the processor. Valid values: C, C++, Java, and Python.
metadata	Dict	No	The metadata of the service. For more information, see Table 2.
cloud	Dict	No	The map key. This parameter is required only if you specify an instance type to deploy the service. You must specify this parameter in the following format: `"cloud":{"computing":{"instance_type": "ecs.gxxxxxx.large"}}`.
containers	List	No	The method of container deployment that is implemented by using custom images. If the container that is deployed by using the processor cannot meet your requirements, you can deploy the container by using custom images. For more information, see Deploy a model service by using a custom image.

Description The model_path parameter and the processor_path parameter specify the sources of the model input and the processor input. You can set the paths to HTTP addresses or OSS paths. When you use the test command to debug the model on your on-premises machine, you can set the parameters to local files and directories.

If you use an HTTP address, you must compress the relevant files into .tar.gz, .tar.bz2, or .zip files. Then, you can upload the files to OSS to generate an HTTP address.
If you use an OSS path, you can enter a directory or file name as the path.

Table 2. Metadata parameters

Parameter	Type	Required	Description	Example
instance	Int	No	The number of workers that are required to start the service.	1
cpu	Int	No	The number of CPUs that are required by each worker.	1
gpu	Int	No	The number of GPUs that are required by each worker.	0
memory	Int	No	The memory size that is required by each worker. Unit: MB.	1000
resource	String	No	The resource group to which the service belongs.	eas-r-aaabbbccc
rpc.worker_threads	Int	No	The number of threads that are used to concurrently process requests in each instance.	5
rpc.max_queue_size	Int	No	The maximum size of a queue for processing requests. If the queue is full, new requests are dropped and an HTTP 450 status code is returned.	64
rpc.keepalive	Int	No	The timeout period of the request. Unit: milliseconds.	5000
rpc.rate_limit	Int	No	The queries per second (QPS) value that triggers request throttling for a single instance. If the QPS is exceeded, new requests are dropped and an HTTP 429 status code is returned.	0
release	Bool	No	Specifies whether to create a service for canary release. Valid values: true and false. If you set this parameter to true, you must create a service for canary release.	false

Response parameters

Parameter	Type	Description	Example
	object	The response parameters.
RequestId	string	The request ID.	40325405-579C-4D82****
ServiceId	string	The ID of the created service.	eas-m-aaxxxddf
ServiceName	string	The name of the created service.	yourname
Status	string	The service state.	Creating
Region	string	The region ID of the created service.	cn-shanghai
InternetEndpoint	string	The public endpoint of the created service.	http://pai-eas.vpc.cn-shanghai.****
IntranetEndpoint	string	The internal endpoint of the created service.	http://pai-eas.cn-shanghai.****

Examples

Sample success responses

JSONformat

{
  "RequestId": "40325405-579C-4D82****",
  "ServiceId": "eas-m-aaxxxddf",
  "ServiceName": "yourname",
  "Status": "Creating",
  "Region": "cn-shanghai",
  "InternetEndpoint": "http://pai-eas.vpc.cn-shanghai.****",
  "IntranetEndpoint": "http://pai-eas.cn-shanghai.****"
}

Error codes

For a list of error codes, visit the Service error codes.

Change history

Change time	Summary of changes	Operation
2023-09-01	The request parameters of the API has changed	View Change Details
2023-01-04	The request parameters of the API has changed	View Change Details