---
title: Getting Started with Datadog
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > Infrastructure > Datadog Resource Catalog
---

# gcp_aiplatform_data_labeling_job{% #gcp_aiplatform_data_labeling_job %}

## `active_learning_config`{% #active_learning_config %}

**Type**: `STRUCT`**Provider name**: `activeLearningConfig`**Description**: Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

- `max_data_item_count`**Type**: `INT64`**Provider name**: `maxDataItemCount`**Description**: Max number of human labeled DataItems.
- `max_data_item_percentage`**Type**: `INT32`**Provider name**: `maxDataItemPercentage`**Description**: Max percent of total DataItems for human labeling.
- `sample_config`**Type**: `STRUCT`**Provider name**: `sampleConfig`**Description**: Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
  - `following_batch_sample_percentage`**Type**: `INT32`**Provider name**: `followingBatchSamplePercentage`**Description**: The percentage of data needed to be labeled in each following batch (except the first batch).
  - `initial_batch_sample_percentage`**Type**: `INT32`**Provider name**: `initialBatchSamplePercentage`**Description**: The percentage of data needed to be labeled in the first batch.
  - `sample_strategy`**Type**: `STRING`**Provider name**: `sampleStrategy`**Description**: Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.**Possible values**:
    - `SAMPLE_STRATEGY_UNSPECIFIED` - Default will be treated as UNCERTAINTY.
    - `UNCERTAINTY` - Sample the most uncertain data to label.
- `training_config`**Type**: `STRUCT`**Provider name**: `trainingConfig`**Description**: CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
  - `timeout_training_milli_hours`**Type**: `INT64`**Provider name**: `timeoutTrainingMilliHours`**Description**: The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.

## `ancestors`{% #ancestors %}

**Type**: `UNORDERED_LIST_STRING`

## `create_time`{% #create_time %}

**Type**: `TIMESTAMP`**Provider name**: `createTime`**Description**: Output only. Timestamp when this DataLabelingJob was created.

## `current_spend`{% #current_spend %}

**Type**: `STRUCT`**Provider name**: `currentSpend`**Description**: Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.

- `currency_code`**Type**: `STRING`**Provider name**: `currencyCode`**Description**: The three-letter currency code defined in ISO 4217.
- `nanos`**Type**: `INT32`**Provider name**: `nanos`**Description**: Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000.
- `units`**Type**: `INT64`**Provider name**: `units`**Description**: The whole units of the amount. For example if `currencyCode` is `"USD"`, then 1 unit is one US dollar.

## `datasets`{% #datasets %}

**Type**: `UNORDERED_LIST_STRING`**Provider name**: `datasets`**Description**: Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`

## `encryption_spec`{% #encryption_spec %}

**Type**: `STRUCT`**Provider name**: `encryptionSpec`**Description**: Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.

- `kms_key_name`**Type**: `STRING`**Provider name**: `kmsKeyName`**Description**: Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.

## `error`{% #error %}

**Type**: `STRUCT`**Provider name**: `error`**Description**: Output only. DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

- `code`**Type**: `INT32`**Provider name**: `code`**Description**: The status code, which should be an enum value of google.rpc.Code.
- `message`**Type**: `STRING`**Provider name**: `message`**Description**: A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

## `gcp_display_name`{% #gcp_display_name %}

**Type**: `STRING`**Provider name**: `displayName`**Description**: Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.

## `inputs_schema_uri`{% #inputs_schema_uri %}

**Type**: `STRING`**Provider name**: `inputsSchemaUri`**Description**: Required. Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the [https://storage.googleapis.com/google-cloud-aiplatform](https://storage.googleapis.com/google-cloud-aiplatform) bucket in the /schema/datalabelingjob/inputs/ folder.

## `instruction_uri`{% #instruction_uri %}

**Type**: `STRING`**Provider name**: `instructionUri`**Description**: Required. The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.

## `labeler_count`{% #labeler_count %}

**Type**: `INT32`**Provider name**: `labelerCount`**Description**: Required. Number of labelers to work on each DataItem.

## `labeling_progress`{% #labeling_progress %}

**Type**: `INT32`**Provider name**: `labelingProgress`**Description**: Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.

## `labels`{% #labels %}

**Type**: `UNORDERED_LIST_STRING`

## `name`{% #name %}

**Type**: `STRING`**Provider name**: `name`**Description**: Output only. Resource name of the DataLabelingJob.

## `organization_id`{% #organization_id %}

**Type**: `STRING`

## `parent`{% #parent %}

**Type**: `STRING`

## `project_id`{% #project_id %}

**Type**: `STRING`

## `project_number`{% #project_number %}

**Type**: `STRING`

## `region_id`{% #region_id %}

**Type**: `STRING`

## `resource_name`{% #resource_name %}

**Type**: `STRING`

## `specialist_pools`{% #specialist_pools %}

**Type**: `UNORDERED_LIST_STRING`**Provider name**: `specialistPools`**Description**: The SpecialistPools' resource names associated with this job.

## `state`{% #state %}

**Type**: `STRING`**Provider name**: `state`**Description**: Output only. The detailed state of the job.**Possible values**:

- `JOB_STATE_UNSPECIFIED` - The job state is unspecified.
- `JOB_STATE_QUEUED` - The job has been just created or resumed and processing has not yet begun.
- `JOB_STATE_PENDING` - The service is preparing to run the job.
- `JOB_STATE_RUNNING` - The job is in progress.
- `JOB_STATE_SUCCEEDED` - The job completed successfully.
- `JOB_STATE_FAILED` - The job failed.
- `JOB_STATE_CANCELLING` - The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
- `JOB_STATE_CANCELLED` - The job has been cancelled.
- `JOB_STATE_PAUSED` - The job has been stopped, and can be resumed.
- `JOB_STATE_EXPIRED` - The job has expired.
- `JOB_STATE_UPDATING` - The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.
- `JOB_STATE_PARTIALLY_SUCCEEDED` - The job is partially succeeded, some results may be missing due to errors.

## `tags`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`

## `update_time`{% #update_time %}

**Type**: `TIMESTAMP`**Provider name**: `updateTime`**Description**: Output only. Timestamp when this DataLabelingJob was updated most recently.

## `zone_id`{% #zone_id %}

**Type**: `STRING`