Ai
Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects. To get more information about Tensorboard, see:
How-to Guides
Example Usage
Vertex Ai Tensorboard
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiTensorboard;
import com.pulumi.gcp.vertex.AiTensorboardArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var tensorboard = new AiTensorboard("tensorboard", AiTensorboardArgs.builder()
.displayName("terraform")
.description("sample description")
.labels(Map.ofEntries(
Map.entry("key1", "value1"),
Map.entry("key2", "value2")
))
.region("us-central1")
.build());
}
}Vertex Ai Tensorboard Full
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.organizations.OrganizationsFunctions;
import com.pulumi.gcp.organizations.inputs.GetProjectArgs;
import com.pulumi.gcp.kms.CryptoKeyIAMMember;
import com.pulumi.gcp.kms.CryptoKeyIAMMemberArgs;
import com.pulumi.gcp.vertex.AiTensorboard;
import com.pulumi.gcp.vertex.AiTensorboardArgs;
import com.pulumi.gcp.vertex.inputs.AiTensorboardEncryptionSpecArgs;
import com.pulumi.resources.CustomResourceOptions;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
final var project = OrganizationsFunctions.getProject();
var cryptoKey = new CryptoKeyIAMMember("cryptoKey", CryptoKeyIAMMemberArgs.builder()
.cryptoKeyId("kms-name")
.role("roles/cloudkms.cryptoKeyEncrypterDecrypter")
.member(String.format("serviceAccount:service-%s@gcp-sa-aiplatform.iam.gserviceaccount.com", project.applyValue(getProjectResult -> getProjectResult.number())))
.build());
var tensorboard = new AiTensorboard("tensorboard", AiTensorboardArgs.builder()
.displayName("terraform")
.description("sample description")
.labels(Map.ofEntries(
Map.entry("key1", "value1"),
Map.entry("key2", "value2")
))
.region("us-central1")
.encryptionSpec(AiTensorboardEncryptionSpecArgs.builder()
.kmsKeyName("kms-name")
.build())
.build(), CustomResourceOptions.builder()
.dependsOn(cryptoKey)
.build());
}
}Import
Tensorboard can be imported using any of these accepted formats
$ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default projects/{{project}}/locations/{{region}}/tensorboards/{{name}}$ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default {{project}}/{{region}}/{{name}}$ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default {{region}}/{{name}}$ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default {{name}}Properties
Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Description of this Tensorboard.
User provided name of this Tensorboard.
Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.