View Source GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_ContainerSpec (google_api_machine_learning v0.28.1)
Specification of a custom container for serving predictions. This message is a subset of the Kubernetes Container v1 core specification.
Attributes
-
args
(type:list(String.t)
, default:nil
) - Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container'sCMD
. Specify this field as an array of executable and arguments, similar to a DockerCMD
's "default parameters" form. If you don't specify this field but do specify the command field, then the command from thecommand
field runs without any additional arguments. See the Kubernetes documentation about how thecommand
andargs
fields interact with a container'sENTRYPOINT
andCMD
. If you don't specify this field and don't specify thecommmand
field, then the container'sENTRYPOINT
andCMD
determine what runs based on their default behavior. See the Docker documentation about howCMD
andENTRYPOINT
interact. In this field, you can reference environment variables set by AI Platform Prediction 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 theargs
field of the Kubernetes Containers v1 core API. -
command
(type:list(String.t)
, default:nil
) - Immutable. Specifies the command that runs when the container starts. This overrides the container'sENTRYPOINT
. Specify this field as an array of executable and arguments, similar to a DockerENTRYPOINT
's "exec" form, not its "shell" form. If you do not specify this field, then the container'sENTRYPOINT
runs, in conjunction with the args field or the container'sCMD
, if either exists. If this field is not specified and the container does not have anENTRYPOINT
, then refer to the Docker documentation about howCMD
andENTRYPOINT
interact. If you specify this field, then you can also specify theargs
field to provide additional arguments for this command. However, if you specify this field, then the container'sCMD
is ignored. See the Kubernetes documentation about how thecommand
andargs
fields interact with a container'sENTRYPOINT
andCMD
. In this field, you can reference environment variables set by AI Platform Prediction 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 thecommand
field of the Kubernetes Containers v1 core API. -
env
(type:list(GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_EnvVar.t)
, default:nil
) - 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 variableVAR_2
to have the valuefoo 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 theenv
field of the Kubernetes Containers v1 core API. -
image
(type:String.t
, default:nil
) - URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry and begin with the hostname{REGION}-docker.pkg.dev
, where{REGION}
is replaced by the region that matches AI Platform Prediction regional endpoint that you are using. For example, if you are using theus-central1-ml.googleapis.com
endpoint, then this URI must begin withus-central1-docker.pkg.dev
. To use a custom container, the AI Platform Google-managed service account must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format:service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com
{PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read Custom container requirements. -
ports
(type:list(GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_ContainerPort.t)
, default:nil
) - Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends liveness and health checks to this port. If you do not specify this field, it defaults to following value:json [ { "containerPort": 8080 } ]
AI Platform Prediction does not use ports other than the first one listed. This field corresponds to theports
field of the Kubernetes Containers v1 core API.
Summary
Functions
Unwrap a decoded JSON object into its complex fields.
Types
@type t() :: %GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_ContainerSpec{ args: [String.t()] | nil, command: [String.t()] | nil, env: [GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_EnvVar.t()] | nil, image: String.t() | nil, ports: [GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_ContainerPort.t()] | nil }
Functions
Unwrap a decoded JSON object into its complex fields.