Class GoogleCloudMlV1ContainerSpec
Specification of a custom container for serving predictions. This message is a subset of the Kubernetes Container v1 core specification.
Implements
Inherited Members
Namespace: Google.Apis.CloudMachineLearningEngine.v1.Data
Assembly: Google.Apis.CloudMachineLearningEngine.v1.dll
Syntax
public class GoogleCloudMlV1ContainerSpec : 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 commmand
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 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 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 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 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> |
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<GoogleCloudMlV1EnvVar> Env { get; set; }
Property Value
Type | Description |
---|---|
IList<GoogleCloudMlV1EnvVar> |
Image
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 the us-central1-ml.googleapis.com
endpoint, then this URI must begin with
us-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.
Declaration
[JsonProperty("image")]
public virtual string Image { get; set; }
Property Value
Type | Description |
---|---|
string |
Ports
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 the ports
field
of the Kubernetes Containers v1 core
API.
Declaration
[JsonProperty("ports")]
public virtual IList<GoogleCloudMlV1ContainerPort> Ports { get; set; }
Property Value
Type | Description |
---|---|
IList<GoogleCloudMlV1ContainerPort> |