GoogleCloudMlV1__ContainerSpec
import type { GoogleCloudMlV1__ContainerSpec } from "https://googleapis.deno.dev/v1/ml:v1.ts";
Specification of a custom container for serving predictions. This message is a subset of the Kubernetes Container v1 core specification.
§Properties
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.
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.
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.
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.
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.