Amazon Web Services Projects API

openapi: 3.2.0
info:
  title: Amazon Web Services Projects API
  version: '1.0'
  description: 'Operations tagged Projects across 6 of this provider''s published API definitions: databrew-openapi-original.yml, evidently-openapi-original.yml, iot1click-projects-openapi-original.yml, iotsitewise-openapi-original.yml, lookoutvision-openapi-original.yml, mobile-openapi-original.yml. Each path carries the servers of the definition it was published in.'
tags:
- name: Projects
paths:
  /projects:
    GET:
      summary: Amazon Web Services Listprojects
      description: Lists all of the DataBrew projects that are defined.
      operationId: amazonWebServicesListProjects
      tags:
      - Projects
  /projects/{name}:
    PUT:
      summary: Amazon Web Services Updateproject
      description: Modifies the definition of an existing DataBrew project.
      operationId: amazonWebServicesUpdateProject
      tags:
      - Projects
  /projects/{name}/sendProjectSessionAction:
    PUT:
      summary: Amazon Web Services Sendprojectsessionaction
      description: Performs a recipe step within an interactive DataBrew session that's currently open.
      operationId: amazonWebServicesSendProjectSessionAction
      tags:
      - Projects
  /projects/{name}/startProjectSession:
    PUT:
      summary: Amazon Web Services Startprojectsession
      description: Creates an interactive session, enabling you to manipulate data in a DataBrew project.
      operationId: amazonWebServicesStartProjectSession
      tags:
      - Projects
  /projects/{project}/evaluations:
    POST:
      summary: Amazon Web Services Batchevaluatefeature
      description: This operation assigns feature variation to user sessions. For each user session, you pass in an entityID that represents the user. Evidently then checks the evaluation rules and assigns the variation. The first rules that are evaluated are the override rules. If the user's entityID matches an override rule, the user is served the variation specified by that rule. Next, if there is a launch of the feature, the user might be assigned to a variation in the launch. The chance of this depends on the percentage of users that are allocated to that launch. If the user is enrolled in the launch, the variation they are served depends on the allocation of the various feature variations used for the launch. If the user is not assigned to a launch, and there is an ongoing experiment for this feature, the user might be assigned to a variation in the experiment. The chance of this depends on the percentage of users that are allocated to that experiment. If the user is enrolled in the experiment, the variation they are served depends on the allocation of the various feature variations used for the experiment. If the user is not assigned to a launch or experiment, they are served the default variation.
      operationId: amazonWebServicesBatchEvaluateFeature
      tags:
      - Projects
  /projects/{project}/experiments:
    GET:
      summary: Amazon Web Services Listexperiments
      description: Returns configuration details about all the experiments in the specified project.
      operationId: amazonWebServicesListExperiments
      tags:
      - Projects
  /projects/{project}/features:
    GET:
      summary: Amazon Web Services Listfeatures
      description: Returns configuration details about all the features in the specified project.
      operationId: amazonWebServicesListFeatures
      tags:
      - Projects
  /projects/{project}/launches:
    GET:
      summary: Amazon Web Services Listlaunches
      description: Returns configuration details about all the launches in the specified project.
      operationId: amazonWebServicesListLaunches
      tags:
      - Projects
  /projects/{project}/experiments/{experiment}:
    PATCH:
      summary: Amazon Web Services Updateexperiment
      description: Updates an Evidently experiment. Don't use this operation to update an experiment's tag. Instead, use TagResource.
      operationId: amazonWebServicesUpdateExperiment
      tags:
      - Projects
  /projects/{project}/features/{feature}:
    PATCH:
      summary: Amazon Web Services Updatefeature
      description: Updates an existing feature. You can't use this operation to update the tags of an existing feature. Instead, use TagResource.
      operationId: amazonWebServicesUpdateFeature
      tags:
      - Projects
  /projects/{project}/launches/{launch}:
    PATCH:
      summary: Amazon Web Services Updatelaunch
      description: Updates a launch of a given feature. Don't use this operation to update the tags of an existing launch. Instead, use TagResource.
      operationId: amazonWebServicesUpdateLaunch
      tags:
      - Projects
  /projects/{project}:
    PATCH:
      summary: Amazon Web Services Updateproject
      description: Updates the description of an existing project. To create a new project, use CreateProject. Don't use this operation to update the data storage options of a project. Instead, use UpdateProjectDataDelivery. Don't use this operation to update the tags of a project. Instead, use TagResource.
      operationId: patchProjectsByProject
      tags:
      - Projects
      x-operation-id-source: normalized
      x-operation-id-original: amazonWebServicesUpdateProject
  /projects/{project}/evaluations/{feature}:
    POST:
      summary: Amazon Web Services Evaluatefeature
      description: This operation assigns a feature variation to one given user session. You pass in an entityID that represents the user. Evidently then checks the evaluation rules and assigns the variation. The first rules that are evaluated are the override rules. If the user's entityID matches an override rule, the user is served the variation specified by that rule. If there is a current launch with this feature that uses segment overrides, and if the user session's evaluationContext matches a segment rule defined in a segment override, the configuration in the segment overrides is used. For more information about segments, see CreateSegment and Use segments to focus your audience. If there is a launch with no segment overrides, the user might be assigned to a variation in the launch. The chance of this depends on the percentage of users that are allocated to that launch. If the user is enrolled in the launch, the variation they are served depends on the allocation of the various feature variations used for the launch. If the user is not assigned to a launch, and there is an ongoing experiment for this feature, the user might be assigned to a variation in the experiment. The chance of this depends on the percentage of users that are allocated to that experiment. If the experiment uses a segment, then only user sessions with evaluationContext values that match the segment rule are used in the experiment. If the user is enrolled in the experiment, the variation they are served depends on the allocation of the various feature variations used for the experiment. If the user is not assigned to a launch or experiment, they are served the default variation.
      operationId: amazonWebServicesEvaluateFeature
      tags:
      - Projects
  /projects/{project}/experiments/{experiment}/results:
    POST:
      summary: Amazon Web Services Getexperimentresults
      description: Retrieves the results of a running or completed experiment. No results are available until there have been 100 events for each variation and at least 10 minutes have passed since the start of the experiment. To increase the statistical power, Evidently performs an additional offline p-value analysis at the end of the experiment. Offline p-value analysis can detect statistical significance in some cases where the anytime p-values used during the experiment do not find statistical significance. Experiment results are available up to 63 days after the start of the experiment. They are not available after that because of CloudWatch data retention policies.
      operationId: amazonWebServicesGetExperimentResults
      tags:
      - Projects
  /projects/{project}/experiments/{experiment}/start:
    POST:
      summary: Amazon Web Services Startexperiment
      description: Starts an existing experiment. To create an experiment, use CreateExperiment.
      operationId: amazonWebServicesStartExperiment
      tags:
      - Projects
  /projects/{project}/launches/{launch}/start:
    POST:
      summary: Amazon Web Services Startlaunch
      description: Starts an existing launch. To create a launch, use CreateLaunch.
      operationId: amazonWebServicesStartLaunch
      tags:
      - Projects
  /projects/{project}/experiments/{experiment}/cancel:
    POST:
      summary: Amazon Web Services Stopexperiment
      description: Stops an experiment that is currently running. If you stop an experiment, you can't resume it or restart it.
      operationId: amazonWebServicesStopExperiment
      tags:
      - Projects
  /projects/{project}/launches/{launch}/cancel:
    POST:
      summary: Amazon Web Services Stoplaunch
      description: Stops a launch that is currently running. After you stop a launch, you will not be able to resume it or restart it. Also, it will not be evaluated as a rule for traffic allocation, and the traffic that was allocated to the launch will instead be available to the feature's experiment, if there is one. Otherwise, all traffic will be served the default variation after the launch is stopped.
      operationId: amazonWebServicesStopLaunch
      tags:
      - Projects
  /projects/{project}/data-delivery:
    PATCH:
      summary: Amazon Web Services Updateprojectdatadelivery
      description: Updates the data storage options for this project. If you store evaluation events, you an keep them and analyze them on your own. If you choose not to store evaluation events, Evidently deletes them after using them to produce metrics and other experiment results that you can view. You can't specify both cloudWatchLogs and s3Destination in the same operation.
      operationId: amazonWebServicesUpdateProjectDataDelivery
      tags:
      - Projects
  /projects/{projectName}/placements/{placementName}/devices/{deviceTemplateName}:
    DELETE:
      summary: Amazon Web Services Disassociatedevicefromplacement
      description: Removes a physical device from a placement.
      operationId: amazonWebServicesDisassociateDeviceFromPlacement
      tags:
      - Projects
  /projects/{projectName}/placements:
    GET:
      summary: Amazon Web Services Listplacements
      description: Lists the placement(s) of a project.
      operationId: amazonWebServicesListPlacements
      tags:
      - Projects
  /projects/{projectName}/placements/{placementName}:
    PUT:
      summary: Amazon Web Services Updateplacement
      description: Updates a placement with the given attributes. To clear an attribute, pass an empty value (i.e., "").
      operationId: amazonWebServicesUpdatePlacement
      tags:
      - Projects
  /projects/{projectName}:
    PUT:
      summary: Amazon Web Services Updateproject
      description: Updates a project associated with your AWS account and region. With the exception of device template names, you can pass just the values that need to be updated because the update request will change only the values that are provided. To clear a value, pass the empty string (i.e., "").
      operationId: putProjectsByProjectName
      tags:
      - Projects
      x-operation-id-source: normalized
      x-operation-id-original: amazonWebServicesUpdateProject
  /projects/{projectName}/placements/{placementName}/devices:
    GET:
      summary: Amazon Web Services Getdevicesinplacement
      description: Returns an object enumerating the devices in a placement.
      operationId: amazonWebServicesGetDevicesInPlacement
      tags:
      - Projects
  /projects/{projectId}/assets/associate:
    POST:
      summary: Amazon Web Services Batchassociateprojectassets
      description: Associates a group (batch) of assets with an IoT SiteWise Monitor project.
      operationId: amazonWebServicesBatchAssociateProjectAssets
      tags:
      - Projects
  /projects/{projectId}/assets/disassociate:
    POST:
      summary: Amazon Web Services Batchdisassociateprojectassets
      description: Disassociates a group (batch) of assets from an IoT SiteWise Monitor project.
      operationId: amazonWebServicesBatchDisassociateProjectAssets
      tags:
      - Projects
  /projects/{projectId}:
    PUT:
      summary: Amazon Web Services Updateproject
      description: Updates an IoT SiteWise Monitor project.
      operationId: putProjectsByProjectId
      tags:
      - Projects
      x-operation-id-source: normalized
      x-operation-id-original: amazonWebServicesUpdateProject
    DELETE:
      summary: Amazon Web Services Deleteproject
      description: Delets a project in AWS Mobile Hub.
      operationId: amazonWebServicesDeleteProject
      tags:
      - Projects
  /projects/{projectId}/assets:
    GET:
      summary: Amazon Web Services Listprojectassets
      description: Retrieves a paginated list of assets associated with an IoT SiteWise Monitor project.
      operationId: amazonWebServicesListProjectAssets
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/datasets:
    POST:
      summary: Amazon Web Services Createdataset
      description: Creates a new dataset in an Amazon Lookout for Vision project. CreateDataset can create a training or a test dataset from a valid dataset source (DatasetSource). If you want a single dataset project, specify train for the value of DatasetType. To have a project with separate training and test datasets, call CreateDataset twice. On the first call, specify train for the value of DatasetType. On the second call, specify test for the value of DatasetType. This operation requires permissions to perform the lookoutvision:CreateDataset operation.
      operationId: amazonWebServicesCreateDataset
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/models:
    GET:
      summary: Amazon Web Services Listmodels
      description: Lists the versions of a model in an Amazon Lookout for Vision project. The ListModels operation is eventually consistent. Recent calls to CreateModel might take a while to appear in the response from ListProjects. This operation requires permissions to perform the lookoutvision:ListModels operation.
      operationId: amazonWebServicesListModels
      tags:
      - Projects
  /2020-11-20/projects:
    GET:
      summary: Amazon Web Services Listprojects
      description: Lists the Amazon Lookout for Vision projects in your AWS account that are in the AWS Region in which you call ListProjects. The ListProjects operation is eventually consistent. Recent calls to CreateProject and DeleteProject might take a while to appear in the response from ListProjects. This operation requires permissions to perform the lookoutvision:ListProjects operation.
      operationId: get20201120Projects
      tags:
      - Projects
      x-operation-id-source: normalized
      x-operation-id-original: amazonWebServicesListProjects
  /2020-11-20/projects/{projectName}/datasets/{datasetType}:
    GET:
      summary: Amazon Web Services Describedataset
      description: Describe an Amazon Lookout for Vision dataset. This operation requires permissions to perform the lookoutvision:DescribeDataset operation.
      operationId: amazonWebServicesDescribeDataset
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/models/{modelVersion}:
    GET:
      summary: Amazon Web Services Describemodel
      description: Describes a version of an Amazon Lookout for Vision model. This operation requires permissions to perform the lookoutvision:DescribeModel operation.
      operationId: amazonWebServicesDescribeModel
      tags:
      - Projects
  /2020-11-20/projects/{projectName}:
    GET:
      summary: Amazon Web Services Describeproject
      description: Describes an Amazon Lookout for Vision project. This operation requires permissions to perform the lookoutvision:DescribeProject operation.
      operationId: amazonWebServicesDescribeProject
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/modelpackagingjobs/{jobName}:
    GET:
      summary: Amazon Web Services Describemodelpackagingjob
      description: Describes an Amazon Lookout for Vision model packaging job. This operation requires permissions to perform the lookoutvision:DescribeModelPackagingJob operation. For more information, see Using your Amazon Lookout for Vision model on an edge device in the Amazon Lookout for Vision Developer Guide.
      operationId: amazonWebServicesDescribeModelPackagingJob
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/models/{modelVersion}/detect:
    POST:
      summary: Amazon Web Services Detectanomalies
      description: Detects anomalies in an image that you supply. The response from DetectAnomalies includes a boolean prediction that the image contains one or more anomalies and a confidence value for the prediction. If the model is an image segmentation model, the response also includes segmentation information for each type of anomaly found in the image. Before calling DetectAnomalies, you must first start your model with the StartModel operation. You are charged for the amount of time, in minutes, that a model runs and for the number of anomaly detection units that your model uses. If you are not using a model, use the StopModel operation to stop your model. For more information, see Detecting anomalies in an image in the Amazon Lookout for Vision developer guide. This operation requires permissions to perform the lookoutvision:DetectAnomalies operation.
      operationId: amazonWebServicesDetectAnomalies
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/datasets/{datasetType}/entries:
    PATCH:
      summary: Amazon Web Services Updatedatasetentries
      description: Adds or updates one or more JSON Line entries in a dataset. A JSON Line includes information about an image used for training or testing an Amazon Lookout for Vision model. To update an existing JSON Line, use the source-ref field to identify the JSON Line. The JSON line that you supply replaces the existing JSON line. Any existing annotations that are not in the new JSON line are removed from the dataset. For more information, see Defining JSON lines for anomaly classification in the Amazon Lookout for Vision Developer Guide. The images you reference in the source-ref field of a JSON line, must be in the same S3 bucket as the existing images in the dataset. Updating a dataset might take a while to complete. To check the current status, call DescribeDataset and check the Status field in the response. This operation requires permissions to perform the lookoutvision:UpdateDatasetEntries operation.
      operationId: amazonWebServicesUpdateDatasetEntries
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/modelpackagingjobs:
    POST:
      summary: Amazon Web Services Startmodelpackagingjob
      description: 'Starts an Amazon Lookout for Vision model packaging job. A model packaging job creates an AWS IoT Greengrass component for a Lookout for Vision model. You can use the component to deploy your model to an edge device managed by Greengrass. Use the DescribeModelPackagingJob API to determine the current status of the job. The model packaging job is complete if the value of Status is SUCCEEDED. To deploy the component to the target device, use the component name and component version with the AWS IoT Greengrass CreateDeployment API. This operation requires the following permissions: lookoutvision:StartModelPackagingJob s3:PutObject s3:GetBucketLocation kms:GenerateDataKey greengrass:CreateComponentVersion greengrass:DescribeComponent (Optional) greengrass:TagResource. Only required if you want to tag the component. For more information, see Using your Amazon Lookout for Vision model on an edge device in the Amazon Lookout for Vision Developer Guide.'
      operationId: amazonWebServicesStartModelPackagingJob
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/models/{modelVersion}/start:
    POST:
      summary: Amazon Web Services Startmodel
      description: Starts the running of the version of an Amazon Lookout for Vision model. Starting a model takes a while to complete. To check the current state of the model, use DescribeModel. A model is ready to use when its status is HOSTED. Once the model is running, you can detect custom labels in new images by calling DetectAnomalies. You are charged for the amount of time that the model is running. To stop a running model, call StopModel. This operation requires permissions to perform the lookoutvision:StartModel operation.
      operationId: amazonWebServicesStartModel
      tags:
      - Projects
  /2020-11-20/projects/{projectName}/models/{modelVersion}/stop:
    POST:
      summary: Amazon Web Services Stopmodel
      description: Stops the hosting of a running model. The operation might take a while to complete. To check the current status, call DescribeModel. After the model hosting stops, the Status of the model is TRAINED. This operation requires permissions to perform the lookoutvision:StopModel operation.
      operationId: amazonWebServicesStopModel
      tags:
      - Projects
x-refined-from:
- databrew-openapi-original.yml
- evidently-openapi-original.yml
- iot1click-projects-openapi-original.yml
- iotsitewise-openapi-original.yml
- lookoutvision-openapi-original.yml
- mobile-openapi-original.yml