oci_ai_anomaly_detection_detect_anomaly_job

This resource provides the Detect Anomaly Job resource in Oracle Cloud Infrastructure Ai Anomaly Detection service.

Creates a job to perform anomaly detection.

Example Usage

resource "oci_ai_anomaly_detection_detect_anomaly_job" "test_detect_anomaly_job" {
	#Required
	compartment_id = var.compartment_id
	input_details {
		#Required
		input_type = var.detect_anomaly_job_input_details_input_type

		#Optional
		content = var.detect_anomaly_job_input_details_content
		content_type = var.detect_anomaly_job_input_details_content_type
		data {

			#Optional
			timestamp = var.detect_anomaly_job_input_details_data_timestamp
			values = var.detect_anomaly_job_input_details_data_values
		}
		object_locations {

			#Optional
			bucket = var.detect_anomaly_job_input_details_object_locations_bucket
			namespace = var.detect_anomaly_job_input_details_object_locations_namespace
			object = var.detect_anomaly_job_input_details_object_locations_object
		}
		signal_names = var.detect_anomaly_job_input_details_signal_names
	}
	model_id = oci_ai_anomaly_detection_model.test_model.id
	output_details {
		#Required
		bucket = var.detect_anomaly_job_output_details_bucket
		namespace = var.detect_anomaly_job_output_details_namespace
		output_type = var.detect_anomaly_job_output_details_output_type

		#Optional
		prefix = var.detect_anomaly_job_output_details_prefix
	}

	#Optional
	are_all_estimates_required = var.detect_anomaly_job_are_all_estimates_required
	description = var.detect_anomaly_job_description
	display_name = var.detect_anomaly_job_display_name
	sensitivity = var.detect_anomaly_job_sensitivity
}

Argument Reference

The following arguments are supported:

• are_all_estimates_required - (Optional) Flag to enable the service to return estimates for all data points rather than just the anomalous data points.
• compartment_id - (Required) (Updatable) The OCID of the compartment that starts the job.
• description - (Optional) (Updatable) A short description of the detect anomaly job.
• display_name - (Optional) (Updatable) Detect anomaly job display name.
• input_details - (Required) Detect anomaly asynchronous job details.
  • content - (Required when input_type=BASE64_ENCODED)
  • content_type - (Required when input_type=BASE64_ENCODED)
  • data - (Required when input_type=INLINE) Array containing data.
    • timestamp - (Applicable when input_type=INLINE) Nullable string representing timestamp.
    • values - (Required when input_type=INLINE) Array of double precision values.
  • input_type - (Required) Type of request. This parameter is automatically populated by classes generated by the SDK. For raw curl requests, you must provide this field.
  • object_locations - (Required when input_type=OBJECT_LIST) List of ObjectLocations.
    • bucket - (Required when input_type=OBJECT_LIST) Object Storage bucket name.
    • namespace - (Required when input_type=OBJECT_LIST) Object Storage namespace name.
    • object - (Required when input_type=OBJECT_LIST) Object Storage object name.
  • signal_names - (Required when input_type=INLINE) List of signal names.
• model_id - (Required) The OCID of the trained model.
• output_details - (Required) Detect anomaly job output details.
  • bucket - (Required) Object Storage bucket name.
  • namespace - (Required) Object Storage namespace.
  • output_type - (Required) The type of output location. Allowed values are:
    • OBJECT_STORAGE: Object store output location.
  • prefix - (Optional) Object Storage folder name.
• sensitivity - (Optional) The value that customer can adjust to control the sensitivity of anomaly detection

** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

Attributes Reference

The following attributes are exported:

• are_all_estimates_required - Flag to enable the service to return estimates for all data points rather than just the anomalous data points
• compartment_id - The OCID of the compartment that starts the job.
• defined_tags - Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
• description - Detect anomaly job description.
• display_name - Detect anomaly job display name.
• freeform_tags - Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
• id - Id of the job.
• input_details - Input details for detect anomaly job.
  • input_type - The type of input location Allowed values are:
    • INLINE: Inline input data.
    • OBJECT_LIST: Object store output location.
  • message - Inline input details.
  • object_locations - List of ObjectLocations.
    • bucket - Object Storage bucket name.
    • namespace - Object Storage namespace name.
    • object - Object Storage object name.
• lifecycle_state_details - The current state details of the batch document job.
• model_id - The OCID of the trained model.
• output_details - Output details for detect anomaly job.
  • bucket - Object Storage bucket name.
  • namespace - Object Storage namespace.
  • output_type - The type of output location Allowed values are:
    • OBJECT_STORAGE: Object store output location.
  • prefix - Object Storage folder name.
• project_id - The OCID of the project.
• sensitivity - The value that customer can adjust to control the sensitivity of anomaly detection
• state - The current state of the batch document job.
• system_tags - Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
• time_accepted - Job accepted time
• time_finished - Job finished time
• time_started - Job started time

Timeouts

The timeouts block allows you to specify timeouts for certain operations: * create - (Defaults to 20 minutes), when creating the Detect Anomaly Job * update - (Defaults to 20 minutes), when updating the Detect Anomaly Job * delete - (Defaults to 20 minutes), when destroying the Detect Anomaly Job

Import

DetectAnomalyJobs can be imported using the id, e.g.

$ terraform import oci_ai_anomaly_detection_detect_anomaly_job.test_detect_anomaly_job "id"