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.v1.ModelContainerSpecgetAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic ModelContainerSpec build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic ModelContainerSpec buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic ModelContainerSpec.Builder clone()
clone in interface com.google.protobuf.Message.Builderclone in interface com.google.protobuf.MessageLite.Builderclone in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
setField in interface com.google.protobuf.Message.BuildersetField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
clearField in interface com.google.protobuf.Message.BuilderclearField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface com.google.protobuf.Message.BuilderclearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
setRepeatedField in interface com.google.protobuf.Message.BuildersetRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
addRepeatedField in interface com.google.protobuf.Message.BuilderaddRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder mergeFrom(ModelContainerSpec other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public ModelContainerSpec.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelContainerSpec.Builder>IOExceptionpublic String getImageUri()
Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel], stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
getImageUri in interface ModelContainerSpecOrBuilderpublic com.google.protobuf.ByteString getImageUriBytes()
Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel], stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
getImageUriBytes in interface ModelContainerSpecOrBuilderpublic 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.v1.ModelService.UploadModel], stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
value - The imageUri to set.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.v1.ModelService.UploadModel], stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelService.UploadModel], stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
string image_uri = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
value - The bytes for imageUri to set.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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];getCommandList in interface ModelContainerSpecOrBuilderpublic int getCommandCount()
Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the [args][google.cloud.aiplatform.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];getCommandCount in interface ModelContainerSpecOrBuilderpublic String getCommand(int index)
Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the [args][google.cloud.aiplatform.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];getCommand in interface ModelContainerSpecOrBuilderindex - The index of the element to return.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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];getCommandBytes in interface ModelContainerSpecOrBuilderindex - The index of the value to return.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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];index - The index to set the value at.value - The command to set.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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];value - The command to add.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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];values - The command to add.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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];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.v1.ModelContainerSpec.args] field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string command = 2 [(.google.api.field_behavior) = IMMUTABLE];value - The bytes of the command to add.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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];getArgsList in interface ModelContainerSpecOrBuilderpublic int getArgsCount()
Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the [command][google.cloud.aiplatform.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];getArgsCount in interface ModelContainerSpecOrBuilderpublic String getArgs(int index)
Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the [command][google.cloud.aiplatform.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];getArgs in interface ModelContainerSpecOrBuilderindex - The index of the element to return.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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];getArgsBytes in interface ModelContainerSpecOrBuilderindex - The index of the value to return.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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];index - The index to set the value at.value - The args to set.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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];value - The args to add.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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];values - The args to add.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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];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.v1.ModelContainerSpec.command] field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the [env][google.cloud.aiplatform.v1.ModelContainerSpec.env] field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: <code>$(<var>VARIABLE_NAME</var>)</code> Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: <code>$$(<var>VARIABLE_NAME</var>)</code> This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated string args = 3 [(.google.api.field_behavior) = IMMUTABLE];value - The bytes of the args to add.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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
getEnvList in interface ModelContainerSpecOrBuilderpublic int getEnvCount()
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
getEnvCount in interface ModelContainerSpecOrBuilderpublic EnvVar getEnv(int index)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
getEnv in interface ModelContainerSpecOrBuilderpublic ModelContainerSpec.Builder setEnv(int index, EnvVar value)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addEnv(EnvVar value)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addEnv(EnvVar.Builder builderForValue)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addAllEnv(Iterable<? extends EnvVar> values)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder removeEnv(int index)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
public EnvVarOrBuilder getEnvOrBuilder(int index)
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
getEnvOrBuilder in interface ModelContainerSpecOrBuilderpublic List<? extends EnvVarOrBuilder> getEnvOrBuilderList()
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
getEnvOrBuilderList in interface ModelContainerSpecOrBuilderpublic EnvVar.Builder addEnvBuilder()
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
public List<EnvVar.Builder> getEnvBuilderList()
Immutable. List of environment variables to set in the container. After the
container starts running, code running in the container can read these
environment variables.
Additionally, the
[command][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
[args][google.cloud.aiplatform.v1.ModelContainerSpec.args] fields can
reference these variables. Later entries in this list can also reference
earlier entries. For example, the following example sets the variable
`VAR_2` to have the value `foo bar`:
```json
[
{
"name": "VAR_1",
"value": "foo"
},
{
"name": "VAR_2",
"value": "$(VAR_1) bar"
}
]
```
If you switch the order of the variables in the example, then the expansion
does not occur.
This field corresponds to the `env` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.EnvVar env = 4 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
getPortsList in interface ModelContainerSpecOrBuilderpublic int getPortsCount()
Immutable. List of ports to expose from the container. Vertex AI sends any
prediction requests that it receives to the first port on this list. Vertex
AI also sends
[liveness and health
checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
to this port.
If you do not specify this field, it defaults to following value:
```json
[
{
"containerPort": 8080
}
]
```
Vertex AI does not use ports other than the first one listed. This field
corresponds to the `ports` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
getPortsCount in interface ModelContainerSpecOrBuilderpublic Port getPorts(int index)
Immutable. List of ports to expose from the container. Vertex AI sends any
prediction requests that it receives to the first port on this list. Vertex
AI also sends
[liveness and health
checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
to this port.
If you do not specify this field, it defaults to following value:
```json
[
{
"containerPort": 8080
}
]
```
Vertex AI does not use ports other than the first one listed. This field
corresponds to the `ports` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
getPorts in interface ModelContainerSpecOrBuilderpublic 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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
getPortsOrBuilder in interface ModelContainerSpecOrBuilderpublic List<? extends PortOrBuilder> getPortsOrBuilderList()
Immutable. List of ports to expose from the container. Vertex AI sends any
prediction requests that it receives to the first port on this list. Vertex
AI also sends
[liveness and health
checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness)
to this port.
If you do not specify this field, it defaults to following value:
```json
[
{
"containerPort": 8080
}
]
```
Vertex AI does not use ports other than the first one listed. This field
corresponds to the `ports` field of the Kubernetes Containers
[v1 core
API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
repeated .google.cloud.aiplatform.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
getPortsOrBuilderList in interface ModelContainerSpecOrBuilderpublic 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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.Port ports = 5 [(.google.api.field_behavior) = IMMUTABLE];
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.v1.PredictionService.Predict] to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s [ports][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];getPredictRoute in interface ModelContainerSpecOrBuilderpublic com.google.protobuf.ByteString getPredictRouteBytes()
Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using [projects.locations.endpoints.predict][google.cloud.aiplatform.v1.PredictionService.Predict] to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s [ports][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];getPredictRouteBytes in interface ModelContainerSpecOrBuilderpublic 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.v1.PredictionService.Predict] to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s [ports][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];value - The predictRoute to set.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.v1.PredictionService.Predict] to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s [ports][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];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.v1.PredictionService.Predict] to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s [ports][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string predict_route = 6 [(.google.api.field_behavior) = IMMUTABLE];value - The bytes for predictRoute to set.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.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];getHealthRoute in interface ModelContainerSpecOrBuilderpublic com.google.protobuf.ByteString getHealthRouteBytes()
Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s [ports][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];getHealthRouteBytes in interface ModelContainerSpecOrBuilderpublic 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.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];value - The healthRoute to set.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.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];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.v1.ModelContainerSpec.ports] field. If you don't specify this field, it defaults to the following value when you [deploy this Model to an Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]: <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code> The placeholders in this value are replaced as follows: * <var>ENDPOINT</var>: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * <var>DEPLOYED_MODEL</var>: [DeployedModel.id][google.cloud.aiplatform.v1.DeployedModel.id] of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
string health_route = 7 [(.google.api.field_behavior) = IMMUTABLE];value - The bytes for healthRoute to set.public List<Port> getGrpcPortsList()
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
getGrpcPortsList in interface ModelContainerSpecOrBuilderpublic int getGrpcPortsCount()
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
getGrpcPortsCount in interface ModelContainerSpecOrBuilderpublic Port getGrpcPorts(int index)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
getGrpcPorts in interface ModelContainerSpecOrBuilderpublic ModelContainerSpec.Builder setGrpcPorts(int index, Port value)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder setGrpcPorts(int index, Port.Builder builderForValue)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addGrpcPorts(Port value)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addGrpcPorts(int index, Port value)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addGrpcPorts(Port.Builder builderForValue)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addGrpcPorts(int index, Port.Builder builderForValue)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder addAllGrpcPorts(Iterable<? extends Port> values)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder clearGrpcPorts()
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder removeGrpcPorts(int index)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public Port.Builder getGrpcPortsBuilder(int index)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public PortOrBuilder getGrpcPortsOrBuilder(int index)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
getGrpcPortsOrBuilder in interface ModelContainerSpecOrBuilderpublic List<? extends PortOrBuilder> getGrpcPortsOrBuilderList()
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
getGrpcPortsOrBuilderList in interface ModelContainerSpecOrBuilderpublic Port.Builder addGrpcPortsBuilder()
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public Port.Builder addGrpcPortsBuilder(int index)
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public List<Port.Builder> getGrpcPortsBuilderList()
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.
repeated .google.cloud.aiplatform.v1.Port grpc_ports = 9 [(.google.api.field_behavior) = IMMUTABLE];
public boolean hasDeploymentTimeout()
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
hasDeploymentTimeout in interface ModelContainerSpecOrBuilderpublic com.google.protobuf.Duration getDeploymentTimeout()
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
getDeploymentTimeout in interface ModelContainerSpecOrBuilderpublic ModelContainerSpec.Builder setDeploymentTimeout(com.google.protobuf.Duration value)
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder setDeploymentTimeout(com.google.protobuf.Duration.Builder builderForValue)
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder mergeDeploymentTimeout(com.google.protobuf.Duration value)
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder clearDeploymentTimeout()
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
public com.google.protobuf.Duration.Builder getDeploymentTimeoutBuilder()
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
public com.google.protobuf.DurationOrBuilder getDeploymentTimeoutOrBuilder()
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
.google.protobuf.Duration deployment_timeout = 10 [(.google.api.field_behavior) = IMMUTABLE];
getDeploymentTimeoutOrBuilder in interface ModelContainerSpecOrBuilderpublic long getSharedMemorySizeMb()
Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.
int64 shared_memory_size_mb = 11 [(.google.api.field_behavior) = IMMUTABLE];getSharedMemorySizeMb in interface ModelContainerSpecOrBuilderpublic ModelContainerSpec.Builder setSharedMemorySizeMb(long value)
Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.
int64 shared_memory_size_mb = 11 [(.google.api.field_behavior) = IMMUTABLE];value - The sharedMemorySizeMb to set.public ModelContainerSpec.Builder clearSharedMemorySizeMb()
Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.
int64 shared_memory_size_mb = 11 [(.google.api.field_behavior) = IMMUTABLE];public boolean hasStartupProbe()
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
hasStartupProbe in interface ModelContainerSpecOrBuilderpublic Probe getStartupProbe()
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
getStartupProbe in interface ModelContainerSpecOrBuilderpublic ModelContainerSpec.Builder setStartupProbe(Probe value)
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder setStartupProbe(Probe.Builder builderForValue)
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder mergeStartupProbe(Probe value)
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder clearStartupProbe()
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
public Probe.Builder getStartupProbeBuilder()
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
public ProbeOrBuilder getStartupProbeOrBuilder()
Immutable. Specification for Kubernetes startup probe.
.google.cloud.aiplatform.v1.Probe startup_probe = 12 [(.google.api.field_behavior) = IMMUTABLE];
getStartupProbeOrBuilder in interface ModelContainerSpecOrBuilderpublic boolean hasHealthProbe()
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
hasHealthProbe in interface ModelContainerSpecOrBuilderpublic Probe getHealthProbe()
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
getHealthProbe in interface ModelContainerSpecOrBuilderpublic ModelContainerSpec.Builder setHealthProbe(Probe value)
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder setHealthProbe(Probe.Builder builderForValue)
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder mergeHealthProbe(Probe value)
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
public ModelContainerSpec.Builder clearHealthProbe()
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
public Probe.Builder getHealthProbeBuilder()
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
public ProbeOrBuilder getHealthProbeOrBuilder()
Immutable. Specification for Kubernetes readiness probe.
.google.cloud.aiplatform.v1.Probe health_probe = 13 [(.google.api.field_behavior) = IMMUTABLE];
getHealthProbeOrBuilder in interface ModelContainerSpecOrBuilderpublic final ModelContainerSpec.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface com.google.protobuf.Message.BuildersetUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>public final ModelContainerSpec.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface com.google.protobuf.Message.BuildermergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelContainerSpec.Builder>Copyright © 2024 Google LLC. All rights reserved.