Class RecommenderClient (2.7.4)

Provides insights and recommendations for cloud customers for various categories like performance optimization, cost savings, reliability, feature discovery, etc. Insights and recommendations are generated automatically based on analysis of user resources, configuration and monitoring metrics.

Returns the transport used by the client instance.

Instantiates the recommender client.

Releases underlying transport's resources.

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

Creates an instance of this client using the provided credentials file.

Creates an instance of this client using the provided credentials info.

Creates an instance of this client using the provided credentials file.

Gets the requested insight. Requires the recommender.*.get IAM permission for the specified insight type.

from google.cloud import recommender_v1beta1

def sample_get_insight():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.GetInsightRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_insight(request=request)

    # Handle the response
    print(response)

Gets the requested InsightTypeConfig. There is only one instance of the config for each InsightType.

from google.cloud import recommender_v1beta1

def sample_get_insight_type_config():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.GetInsightTypeConfigRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_insight_type_config(request=request)

    # Handle the response
    print(response)

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variabel is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Gets the requested recommendation. Requires the recommender.*.get IAM permission for the specified recommender.

from google.cloud import recommender_v1beta1

def sample_get_recommendation():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.GetRecommendationRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_recommendation(request=request)

    # Handle the response
    print(response)

Gets the requested Recommender Config. There is only one instance of the config for each Recommender.

from google.cloud import recommender_v1beta1

def sample_get_recommender_config():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.GetRecommenderConfigRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_recommender_config(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified insight string.

Returns a fully-qualified insight_type_config string.

Returns a fully-qualified insight_type string.

Lists insights for the specified Cloud Resource. Requires the recommender.*.list IAM permission for the specified insight type.

from google.cloud import recommender_v1beta1

def sample_list_insights():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.ListInsightsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_insights(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists recommendations for the specified Cloud Resource. Requires the recommender.*.list IAM permission for the specified recommender.

from google.cloud import recommender_v1beta1

def sample_list_recommendations():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.ListRecommendationsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_recommendations(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Marks the Insight State as Accepted. Users can use this method to indicate to the Recommender API that they have applied some action based on the insight. This stops the insight content from being updated.

MarkInsightAccepted can be applied to insights in ACTIVE state. Requires the recommender.*.update IAM permission for the specified insight.

from google.cloud import recommender_v1beta1

def sample_mark_insight_accepted():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.MarkInsightAcceptedRequest(
        name="name_value",
        etag="etag_value",
    )

    # Make the request
    response = client.mark_insight_accepted(request=request)

    # Handle the response
    print(response)

Marks the Recommendation State as Claimed. Users can use this method to indicate to the Recommender API that they are starting to apply the recommendation themselves. This stops the recommendation content from being updated. Associated insights are frozen and placed in the ACCEPTED state.

MarkRecommendationClaimed can be applied to recommendations in CLAIMED or ACTIVE state.

Requires the recommender.*.update IAM permission for the specified recommender.

from google.cloud import recommender_v1beta1

def sample_mark_recommendation_claimed():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.MarkRecommendationClaimedRequest(
        name="name_value",
        etag="etag_value",
    )

    # Make the request
    response = client.mark_recommendation_claimed(request=request)

    # Handle the response
    print(response)

Marks the Recommendation State as Failed. Users can use this method to indicate to the Recommender API that they have applied the recommendation themselves, and the operation failed. This stops the recommendation content from being updated. Associated insights are frozen and placed in the ACCEPTED state.

MarkRecommendationFailed can be applied to recommendations in ACTIVE, CLAIMED, SUCCEEDED, or FAILED state.

Requires the recommender.*.update IAM permission for the specified recommender.

from google.cloud import recommender_v1beta1

def sample_mark_recommendation_failed():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.MarkRecommendationFailedRequest(
        name="name_value",
        etag="etag_value",
    )

    # Make the request
    response = client.mark_recommendation_failed(request=request)

    # Handle the response
    print(response)

Marks the Recommendation State as Succeeded. Users can use this method to indicate to the Recommender API that they have applied the recommendation themselves, and the operation was successful. This stops the recommendation content from being updated. Associated insights are frozen and placed in the ACCEPTED state.

MarkRecommendationSucceeded can be applied to recommendations in ACTIVE, CLAIMED, SUCCEEDED, or FAILED state.

Requires the recommender.*.update IAM permission for the specified recommender.

from google.cloud import recommender_v1beta1

def sample_mark_recommendation_succeeded():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.MarkRecommendationSucceededRequest(
        name="name_value",
        etag="etag_value",
    )

    # Make the request
    response = client.mark_recommendation_succeeded(request=request)

    # Handle the response
    print(response)

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a insight path into its component segments.

Parses a insight_type_config path into its component segments.

Parses a insight_type path into its component segments.

Parses a recommendation path into its component segments.

Parses a recommender_config path into its component segments.

Parses a recommender path into its component segments.

Returns a fully-qualified recommendation string.

Returns a fully-qualified recommender_config string.

Returns a fully-qualified recommender string.

Updates an InsightTypeConfig change. This will create a new revision of the config.

from google.cloud import recommender_v1beta1

def sample_update_insight_type_config():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.UpdateInsightTypeConfigRequest(
    )

    # Make the request
    response = client.update_insight_type_config(request=request)

    # Handle the response
    print(response)

Updates a Recommender Config. This will create a new revision of the config.

from google.cloud import recommender_v1beta1

def sample_update_recommender_config():
    # Create a client
    client = recommender_v1beta1.RecommenderClient()

    # Initialize request argument(s)
    request = recommender_v1beta1.UpdateRecommenderConfigRequest(
    )

    # Make the request
    response = client.update_recommender_config(request=request)

    # Handle the response
    print(response)