Package com.google.cloud.aiplatform.v1beta1

Class ModelContainerSpec.Builder

  • All Implemented Interfaces:
    ModelContainerSpecOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
    Enclosing class:
    ModelContainerSpec
    public static final class ModelContainerSpec.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>
implements ModelContainerSpecOrBuilder
     Specification of a container for serving predictions. Some fields in this
 message correspond to fields in the [Kubernetes Container v1 core
 specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
    Protobuf type google.cloud.aiplatform.v1beta1.ModelContainerSpec

    • Method Detail

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • clear

        public ModelContainerSpec.Builder clear()
        Specified by:
        clear in interface com.google.protobuf.Message.Builder
        Specified by:
        clear in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clear in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • getDefaultInstanceForType

        public ModelContainerSpec getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

      • build

        public ModelContainerSpec build()
        Specified by:
        build in interface com.google.protobuf.Message.Builder
        Specified by:
        build in interface com.google.protobuf.MessageLite.Builder

      • buildPartial

        public ModelContainerSpec buildPartial()
        Specified by:
        buildPartial in interface com.google.protobuf.Message.Builder
        Specified by:
        buildPartial in interface com.google.protobuf.MessageLite.Builder

      • clone

        public ModelContainerSpec.Builder clone()
        Specified by:
        clone in interface com.google.protobuf.Message.Builder
        Specified by:
        clone in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clone in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • setField

        public ModelContainerSpec.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                           Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • clearField

        public ModelContainerSpec.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • clearOneof

        public ModelContainerSpec.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • setRepeatedField

        public ModelContainerSpec.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   int index,
                                                   Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • addRepeatedField

        public ModelContainerSpec.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • mergeFrom

        public ModelContainerSpec.Builder mergeFrom​(com.google.protobuf.Message other)
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelContainerSpec.Builder>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • mergeFrom

        public ModelContainerSpec.Builder mergeFrom​(com.google.protobuf.CodedInputStream input,
                                            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                     throws IOException
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelContainerSpec.Builder>
        Throws:
        IOException

      • getImageUri

        public 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.v1beta1.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];
        Specified by:
        getImageUri in interface ModelContainerSpecOrBuilder
        Returns:
        The imageUri.

      • getImageUriBytes

        public 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.v1beta1.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];
        Specified by:
        getImageUriBytes in interface ModelContainerSpecOrBuilder
        Returns:
        The bytes for imageUri.

      • setImageUri

        public ModelContainerSpec.Builder setImageUri​(String value)
         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.v1beta1.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];
        Parameters:
        value - The imageUri to set.
        Returns:
        This builder for chaining.

      • clearImageUri

        public ModelContainerSpec.Builder clearImageUri()
         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.v1beta1.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:
        This builder for chaining.

      • setImageUriBytes

        public ModelContainerSpec.Builder setImageUriBytes​(com.google.protobuf.ByteString value)
         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.v1beta1.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];
        Parameters:
        value - The bytes for imageUri to set.
        Returns:
        This builder for chaining.

      • getCommandList

        public com.google.protobuf.ProtocolStringList 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.v1beta1.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.v1beta1.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];
        Specified by:
        getCommandList in interface ModelContainerSpecOrBuilder
        Returns:
        A list containing the command.

      • getCommandCount

        public 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.v1beta1.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.v1beta1.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];
        Specified by:
        getCommandCount in interface ModelContainerSpecOrBuilder
        Returns:
        The count of command.

      • getCommand

        public 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.v1beta1.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.v1beta1.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];
        Specified by:
        getCommand in interface ModelContainerSpecOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The command at the given index.

      • getCommandBytes

        public 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.v1beta1.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.v1beta1.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];
        Specified by:
        getCommandBytes in interface ModelContainerSpecOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the command at the given index.

      • setCommand

        public ModelContainerSpec.Builder setCommand​(int index,
                                             String value)
         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.v1beta1.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.v1beta1.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 to set the value at.
        value - The command to set.
        Returns:
        This builder for chaining.

      • addCommand

        public ModelContainerSpec.Builder addCommand​(String value)
         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.v1beta1.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.v1beta1.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:
        value - The command to add.
        Returns:
        This builder for chaining.

      • addAllCommand

        public ModelContainerSpec.Builder addAllCommand​(Iterable<String> values)
         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.v1beta1.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.v1beta1.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:
        values - The command to add.
        Returns:
        This builder for chaining.

      • clearCommand

        public ModelContainerSpec.Builder clearCommand()
         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.v1beta1.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.v1beta1.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:
        This builder for chaining.

      • addCommandBytes

        public ModelContainerSpec.Builder addCommandBytes​(com.google.protobuf.ByteString value)
         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.v1beta1.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.v1beta1.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:
        value - The bytes of the command to add.
        Returns:
        This builder for chaining.

      • getArgsList

        public com.google.protobuf.ProtocolStringList 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.v1beta1.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.v1beta1.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];
        Specified by:
        getArgsList in interface ModelContainerSpecOrBuilder
        Returns:
        A list containing the args.

      • getArgsCount

        public 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.v1beta1.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.v1beta1.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];
        Specified by:
        getArgsCount in interface ModelContainerSpecOrBuilder
        Returns:
        The count of args.

      • getArgs

        public 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.v1beta1.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.v1beta1.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];
        Specified by:
        getArgs in interface ModelContainerSpecOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The args at the given index.

      • getArgsBytes

        public 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.v1beta1.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.v1beta1.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];
        Specified by:
        getArgsBytes in interface ModelContainerSpecOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the args at the given index.

      • setArgs

        public ModelContainerSpec.Builder setArgs​(int index,
                                          String value)
         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.v1beta1.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.v1beta1.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 to set the value at.
        value - The args to set.
        Returns:
        This builder for chaining.

      • addArgs

        public ModelContainerSpec.Builder addArgs​(String value)
         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.v1beta1.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.v1beta1.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:
        value - The args to add.
        Returns:
        This builder for chaining.

      • addAllArgs

        public ModelContainerSpec.Builder addAllArgs​(Iterable<String> values)
         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.v1beta1.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.v1beta1.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:
        values - The args to add.
        Returns:
        This builder for chaining.

      • clearArgs

        public ModelContainerSpec.Builder clearArgs()
         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.v1beta1.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.v1beta1.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:
        This builder for chaining.

      • addArgsBytes

        public ModelContainerSpec.Builder addArgsBytes​(com.google.protobuf.ByteString value)
         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.v1beta1.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.v1beta1.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:
        value - The bytes of the args to add.
        Returns:
        This builder for chaining.

      • getEnvList

        public 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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getEnvList in interface ModelContainerSpecOrBuilder

      • getEnvCount

        public 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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getEnvCount in interface ModelContainerSpecOrBuilder

      • getEnv

        public 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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getEnv in interface ModelContainerSpecOrBuilder

      • setEnv

        public ModelContainerSpec.Builder setEnv​(int index,
                                         EnvVar value)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • setEnv

        public ModelContainerSpec.Builder setEnv​(int index,
                                         EnvVar.Builder builderForValue)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addEnv

        public ModelContainerSpec.Builder addEnv​(EnvVar value)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addEnv

        public ModelContainerSpec.Builder addEnv​(int index,
                                         EnvVar value)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addEnv

        public ModelContainerSpec.Builder addEnv​(EnvVar.Builder builderForValue)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addEnv

        public ModelContainerSpec.Builder addEnv​(int index,
                                         EnvVar.Builder builderForValue)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAllEnv

        public ModelContainerSpec.Builder addAllEnv​(Iterable<? extends EnvVar> values)
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • clearEnv

        public ModelContainerSpec.Builder clearEnv()
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • removeEnv

        public ModelContainerSpec.Builder removeEnv​(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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getEnvBuilder

        public EnvVar.Builder getEnvBuilder​(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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getEnvOrBuilder

        public 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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getEnvOrBuilder in interface ModelContainerSpecOrBuilder

      • getEnvOrBuilderList

        public 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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getEnvOrBuilderList in interface ModelContainerSpecOrBuilder

      • addEnvBuilder

        public EnvVar.Builder addEnvBuilder()
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addEnvBuilder

        public EnvVar.Builder addEnvBuilder​(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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getEnvBuilderList

        public List<EnvVar.Builder> getEnvBuilderList()
         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.v1beta1.ModelContainerSpec.command] and
 [args][google.cloud.aiplatform.v1beta1.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.v1beta1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getPortsList

        public 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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getPortsList in interface ModelContainerSpecOrBuilder

      • getPortsCount

        public 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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getPortsCount in interface ModelContainerSpecOrBuilder

      • getPorts

        public 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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getPorts in interface ModelContainerSpecOrBuilder

      • setPorts

        public ModelContainerSpec.Builder setPorts​(int index,
                                           Port value)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • setPorts

        public ModelContainerSpec.Builder setPorts​(int index,
                                           Port.Builder builderForValue)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • addPorts

        public ModelContainerSpec.Builder addPorts​(Port value)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • addPorts

        public ModelContainerSpec.Builder addPorts​(int index,
                                           Port value)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • addPorts

        public ModelContainerSpec.Builder addPorts​(Port.Builder builderForValue)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • addPorts

        public ModelContainerSpec.Builder addPorts​(int index,
                                           Port.Builder builderForValue)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • addAllPorts

        public ModelContainerSpec.Builder addAllPorts​(Iterable<? extends Port> values)
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • clearPorts

        public ModelContainerSpec.Builder clearPorts()
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • removePorts

        public ModelContainerSpec.Builder removePorts​(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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • getPortsBuilder

        public Port.Builder getPortsBuilder​(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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • getPortsOrBuilder

        public 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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getPortsOrBuilder in interface ModelContainerSpecOrBuilder

      • getPortsOrBuilderList

        public 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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getPortsOrBuilderList in interface ModelContainerSpecOrBuilder

      • addPortsBuilder

        public Port.Builder addPortsBuilder()
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • addPortsBuilder

        public Port.Builder addPortsBuilder​(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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • getPortsBuilderList

        public List<Port.Builder> getPortsBuilderList()
         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.v1beta1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];

      • getPredictRoute

        public 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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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];
        Specified by:
        getPredictRoute in interface ModelContainerSpecOrBuilder
        Returns:
        The predictRoute.

      • getPredictRouteBytes

        public 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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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];
        Specified by:
        getPredictRouteBytes in interface ModelContainerSpecOrBuilder
        Returns:
        The bytes for predictRoute.

      • setPredictRoute

        public ModelContainerSpec.Builder setPredictRoute​(String value)
         Immutable. HTTP path on the container to send prediction requests to.
 Vertex AI forwards requests sent using
 [projects.locations.endpoints.predict][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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];
        Parameters:
        value - The predictRoute to set.
        Returns:
        This builder for chaining.

      • clearPredictRoute

        public ModelContainerSpec.Builder clearPredictRoute()
         Immutable. HTTP path on the container to send prediction requests to.
 Vertex AI forwards requests sent using
 [projects.locations.endpoints.predict][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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:
        This builder for chaining.

      • setPredictRouteBytes

        public ModelContainerSpec.Builder setPredictRouteBytes​(com.google.protobuf.ByteString value)
         Immutable. HTTP path on the container to send prediction requests to.
 Vertex AI forwards requests sent using
 [projects.locations.endpoints.predict][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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];
        Parameters:
        value - The bytes for predictRoute to set.
        Returns:
        This builder for chaining.

      • getHealthRoute

        public 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.v1beta1.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.v1beta1.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.v1beta1.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];
        Specified by:
        getHealthRoute in interface ModelContainerSpecOrBuilder
        Returns:
        The healthRoute.

      • getHealthRouteBytes

        public 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.v1beta1.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.v1beta1.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.v1beta1.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];
        Specified by:
        getHealthRouteBytes in interface ModelContainerSpecOrBuilder
        Returns:
        The bytes for healthRoute.

      • setHealthRoute

        public ModelContainerSpec.Builder setHealthRoute​(String value)
         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.v1beta1.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.v1beta1.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.v1beta1.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];
        Parameters:
        value - The healthRoute to set.
        Returns:
        This builder for chaining.

      • clearHealthRoute

        public ModelContainerSpec.Builder clearHealthRoute()
         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.v1beta1.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.v1beta1.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.v1beta1.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:
        This builder for chaining.

      • setHealthRouteBytes

        public ModelContainerSpec.Builder setHealthRouteBytes​(com.google.protobuf.ByteString value)
         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.v1beta1.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.v1beta1.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.v1beta1.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];
        Parameters:
        value - The bytes for healthRoute to set.
        Returns:
        This builder for chaining.

      • setUnknownFields

        public final ModelContainerSpec.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>

      • mergeUnknownFields

        public final ModelContainerSpec.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>