Google Cloud Native is in preview. Google Cloud Classic is fully supported.
Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
google-native.retail/v2.getModel
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Google Cloud Native is in preview. Google Cloud Classic is fully supported.
Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
Gets a model.
Using getModel
Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.
function getModel(args: GetModelArgs, opts?: InvokeOptions): Promise<GetModelResult>
function getModelOutput(args: GetModelOutputArgs, opts?: InvokeOptions): Output<GetModelResult>def get_model(catalog_id: Optional[str] = None,
              location: Optional[str] = None,
              model_id: Optional[str] = None,
              project: Optional[str] = None,
              opts: Optional[InvokeOptions] = None) -> GetModelResult
def get_model_output(catalog_id: Optional[pulumi.Input[str]] = None,
              location: Optional[pulumi.Input[str]] = None,
              model_id: Optional[pulumi.Input[str]] = None,
              project: Optional[pulumi.Input[str]] = None,
              opts: Optional[InvokeOptions] = None) -> Output[GetModelResult]func LookupModel(ctx *Context, args *LookupModelArgs, opts ...InvokeOption) (*LookupModelResult, error)
func LookupModelOutput(ctx *Context, args *LookupModelOutputArgs, opts ...InvokeOption) LookupModelResultOutput> Note: This function is named LookupModel in the Go SDK.
public static class GetModel 
{
    public static Task<GetModelResult> InvokeAsync(GetModelArgs args, InvokeOptions? opts = null)
    public static Output<GetModelResult> Invoke(GetModelInvokeArgs args, InvokeOptions? opts = null)
}public static CompletableFuture<GetModelResult> getModel(GetModelArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet
fn::invoke:
  function: google-native:retail/v2:getModel
  arguments:
    # arguments dictionaryThe following arguments are supported:
- catalog_
id str - location str
 - model_
id str - project str
 
getModel Result
The following output properties are available:
- Create
Time string - Timestamp the Recommendation Model was created at.
 - Data
State string - The state of data requirements for this model: 
DATA_OKandDATA_ERROR. Recommendation model cannot be trained if the data is inDATA_ERRORstate. Recommendation model can haveDATA_ERRORstate even if serving state isACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training. - Display
Name string - The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
 - Filtering
Option string - Optional. If 
RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. - Last
Tune stringTime  - The timestamp when the latest successful tune finished.
 - Model
Features Pulumi.Config Google Native. Retail. V2. Outputs. Google Cloud Retail V2Model Model Features Config Response  - Optional. Additional model features config.
 - Name string
 - The fully qualified resource name of the model. Format: 
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}catalog_id has char limit of 50. recommendation_model_id has char limit of 40. - Optimization
Objective string - Optional. The optimization objective e.g. 
cvr. Currently supported values:ctr,cvr,revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation:recommended-for-you=>ctrothers-you-may-like=>ctrfrequently-bought-together=>revenue_per_orderThis field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - Periodic
Tuning stringState  - Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the 
TuneModelmethod. Default value isPERIODIC_TUNING_ENABLED. - Serving
Config List<Pulumi.Lists Google Native. Retail. V2. Outputs. Google Cloud Retail V2Model Serving Config List Response>  - The list of valid serving configs associated with the PageOptimizationConfig.
 - Serving
State string - The serving state of the model: 
ACTIVE,NOT_ACTIVE. - Training
State string - Optional. The training state that the model is in (e.g. 
TRAININGorPAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value forCreateModelmethod isTRAINING. The default value forUpdateModelmethod is to keep the state the same as before. - Tuning
Operation string - The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
 - Type string
 - The type of model e.g. 
home-page. Currently supported values:recommended-for-you,others-you-may-like,frequently-bought-together,page-optimization,similar-items,buy-it-again,on-sale-items, andrecently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - Update
Time string - Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
 
- Create
Time string - Timestamp the Recommendation Model was created at.
 - Data
State string - The state of data requirements for this model: 
DATA_OKandDATA_ERROR. Recommendation model cannot be trained if the data is inDATA_ERRORstate. Recommendation model can haveDATA_ERRORstate even if serving state isACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training. - Display
Name string - The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
 - Filtering
Option string - Optional. If 
RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. - Last
Tune stringTime  - The timestamp when the latest successful tune finished.
 - Model
Features GoogleConfig Cloud Retail V2Model Model Features Config Response  - Optional. Additional model features config.
 - Name string
 - The fully qualified resource name of the model. Format: 
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}catalog_id has char limit of 50. recommendation_model_id has char limit of 40. - Optimization
Objective string - Optional. The optimization objective e.g. 
cvr. Currently supported values:ctr,cvr,revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation:recommended-for-you=>ctrothers-you-may-like=>ctrfrequently-bought-together=>revenue_per_orderThis field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - Periodic
Tuning stringState  - Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the 
TuneModelmethod. Default value isPERIODIC_TUNING_ENABLED. - Serving
Config []GoogleLists Cloud Retail V2Model Serving Config List Response  - The list of valid serving configs associated with the PageOptimizationConfig.
 - Serving
State string - The serving state of the model: 
ACTIVE,NOT_ACTIVE. - Training
State string - Optional. The training state that the model is in (e.g. 
TRAININGorPAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value forCreateModelmethod isTRAINING. The default value forUpdateModelmethod is to keep the state the same as before. - Tuning
Operation string - The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
 - Type string
 - The type of model e.g. 
home-page. Currently supported values:recommended-for-you,others-you-may-like,frequently-bought-together,page-optimization,similar-items,buy-it-again,on-sale-items, andrecently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - Update
Time string - Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
 
- create
Time String - Timestamp the Recommendation Model was created at.
 - data
State String - The state of data requirements for this model: 
DATA_OKandDATA_ERROR. Recommendation model cannot be trained if the data is inDATA_ERRORstate. Recommendation model can haveDATA_ERRORstate even if serving state isACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training. - display
Name String - The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
 - filtering
Option String - Optional. If 
RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. - last
Tune StringTime  - The timestamp when the latest successful tune finished.
 - model
Features GoogleConfig Cloud Retail V2Model Model Features Config Response  - Optional. Additional model features config.
 - name String
 - The fully qualified resource name of the model. Format: 
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}catalog_id has char limit of 50. recommendation_model_id has char limit of 40. - optimization
Objective String - Optional. The optimization objective e.g. 
cvr. Currently supported values:ctr,cvr,revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation:recommended-for-you=>ctrothers-you-may-like=>ctrfrequently-bought-together=>revenue_per_orderThis field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - periodic
Tuning StringState  - Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the 
TuneModelmethod. Default value isPERIODIC_TUNING_ENABLED. - serving
Config List<GoogleLists Cloud Retail V2Model Serving Config List Response>  - The list of valid serving configs associated with the PageOptimizationConfig.
 - serving
State String - The serving state of the model: 
ACTIVE,NOT_ACTIVE. - training
State String - Optional. The training state that the model is in (e.g. 
TRAININGorPAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value forCreateModelmethod isTRAINING. The default value forUpdateModelmethod is to keep the state the same as before. - tuning
Operation String - The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
 - type String
 - The type of model e.g. 
home-page. Currently supported values:recommended-for-you,others-you-may-like,frequently-bought-together,page-optimization,similar-items,buy-it-again,on-sale-items, andrecently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - update
Time String - Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
 
- create
Time string - Timestamp the Recommendation Model was created at.
 - data
State string - The state of data requirements for this model: 
DATA_OKandDATA_ERROR. Recommendation model cannot be trained if the data is inDATA_ERRORstate. Recommendation model can haveDATA_ERRORstate even if serving state isACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training. - display
Name string - The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
 - filtering
Option string - Optional. If 
RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. - last
Tune stringTime  - The timestamp when the latest successful tune finished.
 - model
Features GoogleConfig Cloud Retail V2Model Model Features Config Response  - Optional. Additional model features config.
 - name string
 - The fully qualified resource name of the model. Format: 
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}catalog_id has char limit of 50. recommendation_model_id has char limit of 40. - optimization
Objective string - Optional. The optimization objective e.g. 
cvr. Currently supported values:ctr,cvr,revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation:recommended-for-you=>ctrothers-you-may-like=>ctrfrequently-bought-together=>revenue_per_orderThis field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - periodic
Tuning stringState  - Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the 
TuneModelmethod. Default value isPERIODIC_TUNING_ENABLED. - serving
Config GoogleLists Cloud Retail V2Model Serving Config List Response[]  - The list of valid serving configs associated with the PageOptimizationConfig.
 - serving
State string - The serving state of the model: 
ACTIVE,NOT_ACTIVE. - training
State string - Optional. The training state that the model is in (e.g. 
TRAININGorPAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value forCreateModelmethod isTRAINING. The default value forUpdateModelmethod is to keep the state the same as before. - tuning
Operation string - The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
 - type string
 - The type of model e.g. 
home-page. Currently supported values:recommended-for-you,others-you-may-like,frequently-bought-together,page-optimization,similar-items,buy-it-again,on-sale-items, andrecently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - update
Time string - Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
 
- create_
time str - Timestamp the Recommendation Model was created at.
 - data_
state str - The state of data requirements for this model: 
DATA_OKandDATA_ERROR. Recommendation model cannot be trained if the data is inDATA_ERRORstate. Recommendation model can haveDATA_ERRORstate even if serving state isACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training. - display_
name str - The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
 - filtering_
option str - Optional. If 
RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. - last_
tune_ strtime  - The timestamp when the latest successful tune finished.
 - model_
features_ Googleconfig Cloud Retail V2Model Model Features Config Response  - Optional. Additional model features config.
 - name str
 - The fully qualified resource name of the model. Format: 
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}catalog_id has char limit of 50. recommendation_model_id has char limit of 40. - optimization_
objective str - Optional. The optimization objective e.g. 
cvr. Currently supported values:ctr,cvr,revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation:recommended-for-you=>ctrothers-you-may-like=>ctrfrequently-bought-together=>revenue_per_orderThis field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - periodic_
tuning_ strstate  - Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the 
TuneModelmethod. Default value isPERIODIC_TUNING_ENABLED. - serving_
config_ Sequence[Googlelists Cloud Retail V2Model Serving Config List Response]  - The list of valid serving configs associated with the PageOptimizationConfig.
 - serving_
state str - The serving state of the model: 
ACTIVE,NOT_ACTIVE. - training_
state str - Optional. The training state that the model is in (e.g. 
TRAININGorPAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value forCreateModelmethod isTRAINING. The default value forUpdateModelmethod is to keep the state the same as before. - tuning_
operation str - The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
 - type str
 - The type of model e.g. 
home-page. Currently supported values:recommended-for-you,others-you-may-like,frequently-bought-together,page-optimization,similar-items,buy-it-again,on-sale-items, andrecently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - update_
time str - Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
 
- create
Time String - Timestamp the Recommendation Model was created at.
 - data
State String - The state of data requirements for this model: 
DATA_OKandDATA_ERROR. Recommendation model cannot be trained if the data is inDATA_ERRORstate. Recommendation model can haveDATA_ERRORstate even if serving state isACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training. - display
Name String - The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
 - filtering
Option String - Optional. If 
RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. - last
Tune StringTime  - The timestamp when the latest successful tune finished.
 - model
Features Property MapConfig  - Optional. Additional model features config.
 - name String
 - The fully qualified resource name of the model. Format: 
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}catalog_id has char limit of 50. recommendation_model_id has char limit of 40. - optimization
Objective String - Optional. The optimization objective e.g. 
cvr. Currently supported values:ctr,cvr,revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation:recommended-for-you=>ctrothers-you-may-like=>ctrfrequently-bought-together=>revenue_per_orderThis field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - periodic
Tuning StringState  - Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the 
TuneModelmethod. Default value isPERIODIC_TUNING_ENABLED. - serving
Config List<Property Map>Lists  - The list of valid serving configs associated with the PageOptimizationConfig.
 - serving
State String - The serving state of the model: 
ACTIVE,NOT_ACTIVE. - training
State String - Optional. The training state that the model is in (e.g. 
TRAININGorPAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value forCreateModelmethod isTRAINING. The default value forUpdateModelmethod is to keep the state the same as before. - tuning
Operation String - The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
 - type String
 - The type of model e.g. 
home-page. Currently supported values:recommended-for-you,others-you-may-like,frequently-bought-together,page-optimization,similar-items,buy-it-again,on-sale-items, andrecently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =frequently-bought-togetherand optimization_objective =ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs. - update
Time String - Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
 
Supporting Types
GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponse         
- Context
Products stringType  - Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the 
frequently-bought-togethertype. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS. 
- Context
Products stringType  - Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the 
frequently-bought-togethertype. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS. 
- context
Products StringType  - Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the 
frequently-bought-togethertype. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS. 
- context
Products stringType  - Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the 
frequently-bought-togethertype. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS. 
- context_
products_ strtype  - Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the 
frequently-bought-togethertype. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS. 
- context
Products StringType  - Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the 
frequently-bought-togethertype. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS. 
GoogleCloudRetailV2ModelModelFeaturesConfigResponse       
- Frequently
Bought Pulumi.Together Config Google Native. Retail. V2. Inputs. Google Cloud Retail V2Model Frequently Bought Together Features Config Response  - Additional configs for frequently-bought-together models.
 
- Frequently
Bought GoogleTogether Config Cloud Retail V2Model Frequently Bought Together Features Config Response  - Additional configs for frequently-bought-together models.
 
- frequently
Bought GoogleTogether Config Cloud Retail V2Model Frequently Bought Together Features Config Response  - Additional configs for frequently-bought-together models.
 
- frequently
Bought GoogleTogether Config Cloud Retail V2Model Frequently Bought Together Features Config Response  - Additional configs for frequently-bought-together models.
 
- frequently_
bought_ Googletogether_ config Cloud Retail V2Model Frequently Bought Together Features Config Response  - Additional configs for frequently-bought-together models.
 
- frequently
Bought Property MapTogether Config  - Additional configs for frequently-bought-together models.
 
GoogleCloudRetailV2ModelServingConfigListResponse       
- Serving
Config List<string>Ids  - Optional. A set of valid serving configs that may be used for 
PAGE_OPTIMIZATION. 
- Serving
Config []stringIds  - Optional. A set of valid serving configs that may be used for 
PAGE_OPTIMIZATION. 
- serving
Config List<String>Ids  - Optional. A set of valid serving configs that may be used for 
PAGE_OPTIMIZATION. 
- serving
Config string[]Ids  - Optional. A set of valid serving configs that may be used for 
PAGE_OPTIMIZATION. 
- serving_
config_ Sequence[str]ids  - Optional. A set of valid serving configs that may be used for 
PAGE_OPTIMIZATION. 
- serving
Config List<String>Ids  - Optional. A set of valid serving configs that may be used for 
PAGE_OPTIMIZATION. 
Package Details
- Repository
 - Google Cloud Native pulumi/pulumi-google-native
 - License
 - Apache-2.0
 
Google Cloud Native is in preview. Google Cloud Classic is fully supported.
Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi