Package com.google.cloud.aiplatform.v1

Interface ModelContainerSpecOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
ModelContainerSpec, ModelContainerSpec.Builder
@Generated public interface ModelContainerSpecOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • getImageUri

      String getImageUri()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing),
 including permissions requirements for the Vertex AI Service Agent.

 The container image is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#).

 You can use the URI to one of Vertex AI's [pre-built container images for
 prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers)
 in this field.
      string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The imageUri.

    • getImageUriBytes

      com.google.protobuf.ByteString getImageUriBytes()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing),
 including permissions requirements for the Vertex AI Service Agent.

 The container image is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#).

 You can use the URI to one of Vertex AI's [pre-built container images for
 prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers)
 in this field.
      string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The bytes for imageUri.

    • getCommandList

      List<String> getCommandList()
       Immutable. Specifies the command that runs when the container starts. This
 overrides the container's
 [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.args] field or the
 container's [`CMD`](https://docs.docker.com/engine/reference/builder/#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](https://docs.docker.com/engine/reference/builder/#understand-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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 In this field, you can reference [environment variables set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `command` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      A list containing the command.

    • getCommandCount

      int getCommandCount()
       Immutable. Specifies the command that runs when the container starts. This
 overrides the container's
 [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.args] field or the
 container's [`CMD`](https://docs.docker.com/engine/reference/builder/#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](https://docs.docker.com/engine/reference/builder/#understand-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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 In this field, you can reference [environment variables set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `command` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The count of command.

    • getCommand

      String getCommand(int index)
       Immutable. Specifies the command that runs when the container starts. This
 overrides the container's
 [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.args] field or the
 container's [`CMD`](https://docs.docker.com/engine/reference/builder/#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](https://docs.docker.com/engine/reference/builder/#understand-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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 In this field, you can reference [environment variables set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `command` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];
      Parameters:
      index - The index of the element to return.
      Returns:
      The command at the given index.

    • getCommandBytes

      com.google.protobuf.ByteString getCommandBytes(int index)
       Immutable. Specifies the command that runs when the container starts. This
 overrides the container's
 [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.args] field or the
 container's [`CMD`](https://docs.docker.com/engine/reference/builder/#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](https://docs.docker.com/engine/reference/builder/#understand-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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 In this field, you can reference [environment variables set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `command` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the command at the given index.

    • getArgsList

      List<String> getArgsList()
       Immutable. Specifies arguments for the command that runs when the container
 starts. This overrides the container's
 [`CMD`](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 If you don't specify this field and don't specify the `command` field,
 then the container's
 [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and
 `CMD` determine what runs based on their default behavior. See the Docker
 documentation about [how `CMD` and `ENTRYPOINT`
 interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact).

 In this field, you can reference [environment variables
 set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `args` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      A list containing the args.

    • getArgsCount

      int getArgsCount()
       Immutable. Specifies arguments for the command that runs when the container
 starts. This overrides the container's
 [`CMD`](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 If you don't specify this field and don't specify the `command` field,
 then the container's
 [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and
 `CMD` determine what runs based on their default behavior. See the Docker
 documentation about [how `CMD` and `ENTRYPOINT`
 interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact).

 In this field, you can reference [environment variables
 set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `args` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The count of args.

    • getArgs

      String getArgs(int index)
       Immutable. Specifies arguments for the command that runs when the container
 starts. This overrides the container's
 [`CMD`](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 If you don't specify this field and don't specify the `command` field,
 then the container's
 [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and
 `CMD` determine what runs based on their default behavior. See the Docker
 documentation about [how `CMD` and `ENTRYPOINT`
 interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact).

 In this field, you can reference [environment variables
 set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `args` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];
      Parameters:
      index - The index of the element to return.
      Returns:
      The args at the given index.

    • getArgsBytes

      com.google.protobuf.ByteString getArgsBytes(int index)
       Immutable. Specifies arguments for the command that runs when the container
 starts. This overrides the container's
 [`CMD`](https://docs.docker.com/engine/reference/builder/#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][google.cloud.aiplatform.v1.ModelContainerSpec.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`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes).

 If you don't specify this field and don't specify the `command` field,
 then the container's
 [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and
 `CMD` determine what runs based on their default behavior. See the Docker
 documentation about [how `CMD` and `ENTRYPOINT`
 interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact).

 In this field, you can reference [environment variables
 set by Vertex
 AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables)
 and environment variables set in the
 [env][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
 example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds
 to the `args` field of the Kubernetes Containers [v1 core
 API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the args at the given index.

    • getEnvList

      List<EnvVar> getEnvList()
       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][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1.ModelContainerSpec.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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

    • getEnv

      EnvVar getEnv(int index)
       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][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1.ModelContainerSpec.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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

    • getEnvCount

      int getEnvCount()
       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][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1.ModelContainerSpec.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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

    • getEnvOrBuilderList

      List<? extends EnvVarOrBuilder> getEnvOrBuilderList()
       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][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1.ModelContainerSpec.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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

    • getEnvOrBuilder

      EnvVarOrBuilder getEnvOrBuilder(int index)
       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][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1.ModelContainerSpec.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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

    • getPortsList

      List<Port> getPortsList()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
 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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

    • getPorts

      Port getPorts(int index)
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
 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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

    • getPortsCount

      int getPortsCount()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
 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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

    • getPortsOrBuilderList

      List<? extends PortOrBuilder> getPortsOrBuilderList()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
 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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

    • getPortsOrBuilder

      PortOrBuilder getPortsOrBuilder(int index)
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
 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](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
      repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

    • getPredictRoute

      String getPredictRoute()
       Immutable. HTTP path on the container to send prediction requests to.
 Vertex AI forwards requests sent using
 [projects.locations.endpoints.predict][google.cloud.aiplatform.v1.PredictionService.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][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field.

 If you don't specify this field, it defaults to the following value when
 you [deploy this Model to an
 Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]:
 <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code>
 The placeholders in this value are replaced as follows:

 * <var>ENDPOINT</var>: 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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

 * <var>DEPLOYED_MODEL</var>:
 [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the
 `DeployedModel`.
 (Vertex AI makes this value available to your container code
 as the [`AIP_DEPLOYED_MODEL_ID` environment
 variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
      string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The predictRoute.

    • getPredictRouteBytes

      com.google.protobuf.ByteString getPredictRouteBytes()
       Immutable. HTTP path on the container to send prediction requests to.
 Vertex AI forwards requests sent using
 [projects.locations.endpoints.predict][google.cloud.aiplatform.v1.PredictionService.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][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field.

 If you don't specify this field, it defaults to the following value when
 you [deploy this Model to an
 Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]:
 <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code>
 The placeholders in this value are replaced as follows:

 * <var>ENDPOINT</var>: 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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

 * <var>DEPLOYED_MODEL</var>:
 [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the
 `DeployedModel`.
 (Vertex AI makes this value available to your container code
 as the [`AIP_DEPLOYED_MODEL_ID` environment
 variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
      string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The bytes for predictRoute.

    • getHealthRoute

      String getHealthRoute()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health).

 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][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field.

 If you don't specify this field, it defaults to the following value when
 you [deploy this Model to an
 Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]:
 <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code>
 The placeholders in this value are replaced as follows:

 * <var>ENDPOINT</var>: 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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

 * <var>DEPLOYED_MODEL</var>:
 [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the
 `DeployedModel`.
 (Vertex AI makes this value available to your container code as the
 [`AIP_DEPLOYED_MODEL_ID` environment
 variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
      string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The healthRoute.

    • getHealthRouteBytes

      com.google.protobuf.ByteString getHealthRouteBytes()
       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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health).

 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][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field.

 If you don't specify this field, it defaults to the following value when
 you [deploy this Model to an
 Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]:
 <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code>
 The placeholders in this value are replaced as follows:

 * <var>ENDPOINT</var>: 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](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

 * <var>DEPLOYED_MODEL</var>:
 [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the
 `DeployedModel`.
 (Vertex AI makes this value available to your container code as the
 [`AIP_DEPLOYED_MODEL_ID` environment
 variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
      string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The bytes for healthRoute.

    • getInvokeRoutePrefix

      String getInvokeRoutePrefix()
       Immutable. Invoke route prefix for the custom container. "/*" is the only
 supported value right now. By setting this field, any non-root route on
 this model will be accessible with invoke http call eg: "/invoke/foo/bar",
 however the [PredictionService.Invoke] RPC is not supported yet.

 Only one of `predict_route` or `invoke_route_prefix` can be set, and we
 default to using `predict_route` if this field is not set. If this field
 is set, the Model can only be deployed to dedicated endpoint.
      string invoke_route_prefix = 15 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The invokeRoutePrefix.

    • getInvokeRoutePrefixBytes

      com.google.protobuf.ByteString getInvokeRoutePrefixBytes()
       Immutable. Invoke route prefix for the custom container. "/*" is the only
 supported value right now. By setting this field, any non-root route on
 this model will be accessible with invoke http call eg: "/invoke/foo/bar",
 however the [PredictionService.Invoke] RPC is not supported yet.

 Only one of `predict_route` or `invoke_route_prefix` can be set, and we
 default to using `predict_route` if this field is not set. If this field
 is set, the Model can only be deployed to dedicated endpoint.
      string invoke_route_prefix = 15 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The bytes for invokeRoutePrefix.

    • getGrpcPortsList

      List<Port> getGrpcPortsList()
       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.
      repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];

    • getGrpcPorts

      Port getGrpcPorts(int index)
       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.
      repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];

    • getGrpcPortsCount

      int getGrpcPortsCount()
       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.
      repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];

    • getGrpcPortsOrBuilderList

      List<? extends PortOrBuilder> getGrpcPortsOrBuilderList()
       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.
      repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];

    • getGrpcPortsOrBuilder

      PortOrBuilder getGrpcPortsOrBuilder(int index)
       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.
      repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];

    • hasDeploymentTimeout

      boolean hasDeploymentTimeout()
       Immutable. Deployment timeout.
 Limit for deployment timeout is 2 hours.
      .google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      Whether the deploymentTimeout field is set.

    • getDeploymentTimeout

      com.google.protobuf.Duration getDeploymentTimeout()
       Immutable. Deployment timeout.
 Limit for deployment timeout is 2 hours.
      .google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The deploymentTimeout.

    • getDeploymentTimeoutOrBuilder

      com.google.protobuf.DurationOrBuilder getDeploymentTimeoutOrBuilder()
       Immutable. Deployment timeout.
 Limit for deployment timeout is 2 hours.
      .google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];

    • getSharedMemorySizeMb

      long getSharedMemorySizeMb()
       Immutable. The amount of the VM memory to reserve as the shared memory for
 the model in megabytes.
      int64 shared_memory_size_mb = 11 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The sharedMemorySizeMb.

    • hasStartupProbe

      boolean hasStartupProbe()
       Immutable. Specification for Kubernetes startup probe.
      .google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      Whether the startupProbe field is set.

    • getStartupProbe

      Probe getStartupProbe()
       Immutable. Specification for Kubernetes startup probe.
      .google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The startupProbe.

    • getStartupProbeOrBuilder

      ProbeOrBuilder getStartupProbeOrBuilder()
       Immutable. Specification for Kubernetes startup probe.
      .google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];

    • hasHealthProbe

      boolean hasHealthProbe()
       Immutable. Specification for Kubernetes readiness probe.
      .google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      Whether the healthProbe field is set.

    • getHealthProbe

      Probe getHealthProbe()
       Immutable. Specification for Kubernetes readiness probe.
      .google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The healthProbe.

    • getHealthProbeOrBuilder

      ProbeOrBuilder getHealthProbeOrBuilder()
       Immutable. Specification for Kubernetes readiness probe.
      .google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];

    • hasLivenessProbe

      boolean hasLivenessProbe()
       Immutable. Specification for Kubernetes liveness probe.
      .google.cloud.aiplatform.v1.Probe liveness_probe = 14 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      Whether the livenessProbe field is set.

    • getLivenessProbe

      Probe getLivenessProbe()
       Immutable. Specification for Kubernetes liveness probe.
      .google.cloud.aiplatform.v1.Probe liveness_probe = 14 [(.google.api.field_behavior) = IMMUTABLE];
      Returns:
      The livenessProbe.

    • getLivenessProbeOrBuilder

      ProbeOrBuilder getLivenessProbeOrBuilder()
       Immutable. Specification for Kubernetes liveness probe.
      .google.cloud.aiplatform.v1.Probe liveness_probe = 14 [(.google.api.field_behavior) = IMMUTABLE];