Class GoogleCloudAiplatformV1beta1ModelContainerSpec

Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification.

Inheritance
object
GoogleCloudAiplatformV1beta1ModelContainerSpec
Implements
Inherited Members
Namespace: Google.Apis.Aiplatform.v1beta1.Data
Assembly: Google.Apis.Aiplatform.v1beta1.dll
Syntax
public class GoogleCloudAiplatformV1beta1ModelContainerSpec : IDirectResponseSchema

Properties

Args

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's CMD. Specify this field as an array of executable and arguments, similar to a Docker CMD's "default parameters" form. If you don't specify this field but do specify the command field, then the command from the command field runs without any additional arguments. See the Kubernetes documentation about how the command and args fields interact with a container's ENTRYPOINT and CMD. If you don't specify this field and don't specify the command field, then the container's ENTRYPOINT and CMD determine what runs based on their default behavior. See the Docker documentation about how CMD and ENTRYPOINT interact. In this field, you can reference environment variables set by Vertex AI and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with $$; for example: $$(VARIABLE_NAME) This field corresponds to the args field of the Kubernetes Containers v1 core API.

Declaration
[JsonProperty("args")]
public virtual IList<string> Args { get; set; }
Property Value
Type Description
IList<string>

Command

Immutable. Specifies the command that runs when the container starts. This overrides the container's ENTRYPOINT. Specify this field as an array of executable and arguments, similar to a Docker ENTRYPOINT's "exec" form, not its "shell" form. If you do not specify this field, then the container's ENTRYPOINT runs, in conjunction with the args field or the container's CMD, if either exists. If this field is not specified and the container does not have an ENTRYPOINT, then refer to the Docker documentation about how CMD and ENTRYPOINT interact. If you specify this field, then you can also specify the args field to provide additional arguments for this command. However, if you specify this field, then the container's CMD is ignored. See the Kubernetes documentation about how the command and args fields interact with a container's ENTRYPOINT and CMD. In this field, you can reference environment variables set by Vertex AI and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with $$; for example: $$(VARIABLE_NAME) This field corresponds to the command field of the Kubernetes Containers v1 core API.

Declaration
[JsonProperty("command")]
public virtual IList<string> Command { get; set; }
Property Value
Type Description
IList<string>

DeploymentTimeout

Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.

Declaration
[JsonProperty("deploymentTimeout")]
public virtual object DeploymentTimeout { get; set; }
Property Value
Type Description
object

ETag

The ETag of the item.

Declaration
public virtual string ETag { get; set; }
Property Value
Type Description
string

Env

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable VAR_2 to have the value foo bar:

json [ { "name": "VAR_1",
"value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]

If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the env field of the Kubernetes Containers v1 core API.

Declaration
[JsonProperty("env")]
public virtual IList<GoogleCloudAiplatformV1beta1EnvVar> Env { get; set; }
Property Value
Type Description
IList<GoogleCloudAiplatformV1beta1EnvVar>

GrpcPorts

Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the ports field of the Kubernetes Containers v1 core API.

Declaration
[JsonProperty("grpcPorts")]
public virtual IList<GoogleCloudAiplatformV1beta1Port> GrpcPorts { get; set; }
Property Value
Type Description
IList<GoogleCloudAiplatformV1beta1Port>

HealthProbe

Immutable. Specification for Kubernetes readiness probe.

Declaration
[JsonProperty("healthProbe")]
public virtual GoogleCloudAiplatformV1beta1Probe HealthProbe { get; set; }
Property Value
Type Description
GoogleCloudAiplatformV1beta1Probe

HealthRoute

Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about health checks. For example, if you set this field to /bar, then Vertex AI intermittently sends a GET request to the /bar path on the port of your container specified by the first value of this ModelContainerSpec's ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following endpoints/)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the AIP_ENDPOINT_ID environment variable.)

Declaration
[JsonProperty("healthRoute")]
public virtual string HealthRoute { get; set; }
Property Value
Type Description
string

ImageUri

Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the container publishing requirements, including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see Custom container requirements. You can use the URI to one of Vertex AI's pre-built container images for prediction in this field.

Declaration
[JsonProperty("imageUri")]
public virtual string ImageUri { get; set; }
Property Value
Type Description
string

Ports

Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, it defaults to following value:

json [ { "containerPort": 8080 }
]

Vertex AI does not use ports other than the first one listed. This field corresponds to the ports field of the Kubernetes Containers v1 core API.

Declaration
[JsonProperty("ports")]
public virtual IList<GoogleCloudAiplatformV1beta1Port> Ports { get; set; }
Property Value
Type Description
IList<GoogleCloudAiplatformV1beta1Port>

PredictRoute

Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to /foo, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the /foo path on the port of your container specified by the first value of this ModelContainerSpec's ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following endpoints/)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the AIP_ENDPOINT_ID environment variable.)

Declaration
[JsonProperty("predictRoute")]
public virtual string PredictRoute { get; set; }
Property Value
Type Description
string

SharedMemorySizeMb

Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.

Declaration
[JsonProperty("sharedMemorySizeMb")]
public virtual long? SharedMemorySizeMb { get; set; }
Property Value
Type Description
long?

StartupProbe

Immutable. Specification for Kubernetes startup probe.

Declaration
[JsonProperty("startupProbe")]
public virtual GoogleCloudAiplatformV1beta1Probe StartupProbe { get; set; }
Property Value
Type Description
GoogleCloudAiplatformV1beta1Probe

Implements