Mock sample for your project: Amazon Rekognition API

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Amazon Rekognition

amazonaws.com

Version: 2016-06-27


Use this API in your project

Speed up your application development by using "Amazon Rekognition API" ready-to-use mock sample. Mocking this API will help you accelerate your development lifecycles and allow you to stop relying on an external API to get the job done. No more API keys to provision, accesses to configure or unplanned downtime, just work.
Enhance your development infrastructure by mocking third party APIs during integrating testing.

Description

This is the Amazon Rekognition API reference.

Other APIs by amazonaws.com

AWS Proton

This is the AWS Proton Service API Reference. It provides descriptions, syntax and usage examples for each of the actions and data types for the AWS Proton service. The documentation for each action shows the Query API request parameters and the XML response. Alternatively, you can use the AWS CLI to access an API. For more information, see the AWS Command Line Interface User Guide. The AWS Proton service is a two-pronged automation framework. Administrators create service templates to provide standardized infrastructure and deployment tooling for serverless and container based applications. Developers, in turn, select from the available service templates to automate their application or service deployments. Because administrators define the infrastructure and tooling that AWS Proton deploys and manages, they need permissions to use all of the listed API operations. When developers select a specific infrastructure and tooling set, AWS Proton deploys their applications. To monitor their applications that are running on AWS Proton, developers need permissions to the service create, list, update and delete API operations and the service instance list and update API operations. To learn more about AWS Proton administration, see the AWS Proton Administrator Guide. To learn more about deploying serverless and containerized applications on AWS Proton, see the AWS Proton User Guide. Ensuring Idempotency When you make a mutating API request, the request typically returns a result before the asynchronous workflows of the operation are complete. Operations might also time out or encounter other server issues before they're complete, even if the request already returned a result. This might make it difficult to determine whether the request succeeded. Moreover, you might need to retry the request multiple times to ensure that the operation completes successfully. However, if the original request and the subsequent retries are successful, the operation occurs multiple times. This means that you might create more resources than you intended. Idempotency ensures that an API request action completes no more than one time. With an idempotent request, if the original request action completes successfully, any subsequent retries complete successfully without performing any further actions. However, the result might contain updated information, such as the current creation status. The following lists of APIs are grouped according to methods that ensure idempotency. Idempotent create APIs with a client token The API actions in this list support idempotency with the use of a client token. The corresponding AWS CLI commands also support idempotency using a client token. A client token is a unique, case-sensitive string of up to 64 ASCII characters. To make an idempotent API request using one of these actions, specify a client token in the request. We recommend that you don't reuse the same client token for other API requests. If you don’t provide a client token for these APIs, a default client token is automatically provided by SDKs. Given a request action that has succeeded: If you retry the request using the same client token and the same parameters, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If you retry the request using the same client token, but one or more of the parameters are different, the retry throws a ValidationException with an IdempotentParameterMismatch error. Client tokens expire eight hours after a request is made. If you retry the request with the expired token, a new resource is created. If the original resource is deleted and you retry the request, a new resource is created. Idempotent create APIs with a client token: CreateEnvironmentTemplateVersion CreateServiceTemplateVersion CreateEnvironmentAccountConnection Idempotent create APIs Given a request action that has succeeded: If you retry the request with an API from this group, and the original resource hasn't been modified, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If the original resource has been modified, the retry throws a ConflictException. If you retry with different input parameters, the retry throws a ValidationException with an IdempotentParameterMismatch error. Idempotent create APIs: CreateEnvironmentTemplate CreateServiceTemplate CreateEnvironment CreateService Idempotent delete APIs Given a request action that has succeeded: When you retry the request with an API from this group and the resource was deleted, its metadata is returned in the response. If you retry and the resource doesn't exist, the response is empty. In both cases, the retry succeeds. Idempotent delete APIs: DeleteEnvironmentTemplate DeleteEnvironmentTemplateVersion DeleteServiceTemplate DeleteServiceTemplateVersion DeleteEnvironmentAccountConnection Asynchronous idempotent delete APIs Given a request action that has succeeded: If you retry the request with an API from this group, if the original request delete operation status is DELETEINPROGRESS, the retry returns the resource detail data in the response without performing any further actions. If the original request delete operation is complete, a retry returns an empty response. Asynchronous idempotent delete APIs: DeleteEnvironment DeleteService

AWS Database Migration Service

Database Migration Service Database Migration Service (DMS) can migrate your data to and from the most widely used commercial and open-source databases such as Oracle, PostgreSQL, Microsoft SQL Server, Amazon Redshift, MariaDB, Amazon Aurora, MySQL, and SAP Adaptive Server Enterprise (ASE). The service supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to MySQL or SQL Server to PostgreSQL. For more information about DMS, see What Is Database Migration Service? in the Database Migration Service User Guide.

Alexa For Business

Alexa for Business helps you use Alexa in your organization. Alexa for Business provides you with the tools to manage Alexa devices, enroll your users, and assign skills, at scale. You can build your own context-aware voice skills using the Alexa Skills Kit and the Alexa for Business API operations. You can also make these available as private skills for your organization. Alexa for Business makes it efficient to voice-enable your products and services, thus providing context-aware voice experiences for your customers. Device makers building with the Alexa Voice Service (AVS) can create fully integrated solutions, register their products with Alexa for Business, and manage them as shared devices in their organization.

AWS CodePipeline

AWS CodePipeline Overview This is the AWS CodePipeline API Reference. This guide provides descriptions of the actions and data types for AWS CodePipeline. Some functionality for your pipeline can only be configured through the API. For more information, see the AWS CodePipeline User Guide. You can use the AWS CodePipeline API to work with pipelines, stages, actions, and transitions. Pipelines are models of automated release processes. Each pipeline is uniquely named, and consists of stages, actions, and transitions. You can work with pipelines by calling: CreatePipeline, which creates a uniquely named pipeline. DeletePipeline, which deletes the specified pipeline. GetPipeline, which returns information about the pipeline structure and pipeline metadata, including the pipeline Amazon Resource Name (ARN). GetPipelineExecution, which returns information about a specific execution of a pipeline. GetPipelineState, which returns information about the current state of the stages and actions of a pipeline. ListActionExecutions, which returns action-level details for past executions. The details include full stage and action-level details, including individual action duration, status, any errors that occurred during the execution, and input and output artifact location details. ListPipelines, which gets a summary of all of the pipelines associated with your account. ListPipelineExecutions, which gets a summary of the most recent executions for a pipeline. StartPipelineExecution, which runs the most recent revision of an artifact through the pipeline. StopPipelineExecution, which stops the specified pipeline execution from continuing through the pipeline. UpdatePipeline, which updates a pipeline with edits or changes to the structure of the pipeline. Pipelines include stages. Each stage contains one or more actions that must complete before the next stage begins. A stage results in success or failure. If a stage fails, the pipeline stops at that stage and remains stopped until either a new version of an artifact appears in the source location, or a user takes action to rerun the most recent artifact through the pipeline. You can call GetPipelineState, which displays the status of a pipeline, including the status of stages in the pipeline, or GetPipeline, which returns the entire structure of the pipeline, including the stages of that pipeline. For more information about the structure of stages and actions, see AWS CodePipeline Pipeline Structure Reference. Pipeline stages include actions that are categorized into categories such as source or build actions performed in a stage of a pipeline. For example, you can use a source action to import artifacts into a pipeline from a source such as Amazon S3. Like stages, you do not work with actions directly in most cases, but you do define and interact with actions when working with pipeline operations such as CreatePipeline and GetPipelineState. Valid action categories are: Source Build Test Deploy Approval Invoke Pipelines also include transitions, which allow the transition of artifacts from one stage to the next in a pipeline after the actions in one stage complete. You can work with transitions by calling: DisableStageTransition, which prevents artifacts from transitioning to the next stage in a pipeline. EnableStageTransition, which enables transition of artifacts between stages in a pipeline. Using the API to integrate with AWS CodePipeline For third-party integrators or developers who want to create their own integrations with AWS CodePipeline, the expected sequence varies from the standard API user. To integrate with AWS CodePipeline, developers need to work with the following items: Jobs, which are instances of an action. For example, a job for a source action might import a revision of an artifact from a source. You can work with jobs by calling: AcknowledgeJob, which confirms whether a job worker has received the specified job. GetJobDetails, which returns the details of a job. PollForJobs, which determines whether there are any jobs to act on. PutJobFailureResult, which provides details of a job failure. PutJobSuccessResult, which provides details of a job success. Third party jobs, which are instances of an action created by a partner action and integrated into AWS CodePipeline. Partner actions are created by members of the AWS Partner Network. You can work with third party jobs by calling: AcknowledgeThirdPartyJob, which confirms whether a job worker has received the specified job. GetThirdPartyJobDetails, which requests the details of a job for a partner action. PollForThirdPartyJobs, which determines whether there are any jobs to act on. PutThirdPartyJobFailureResult, which provides details of a job failure. PutThirdPartyJobSuccessResult, which provides details of a job success.

Amazon WorkSpaces

Amazon WorkSpaces Service Amazon WorkSpaces enables you to provision virtual, cloud-based Microsoft Windows and Amazon Linux desktops for your users.

AWS Direct Connect

Direct Connect links your internal network to an Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an Direct Connect router. With this connection in place, you can create virtual interfaces directly to the Cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all Regions except the China (Beijing) and (China) Ningxia Regions. Amazon Web Services resources in the China Regions can only be accessed through locations associated with those Regions.

AWS Auto Scaling Plans

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

Amazon Forecast Service

Provides APIs for creating and managing Amazon Forecast resources.

Amazon HealthLake

Amazon HealthLake is a HIPAA eligibile service that allows customers to store, transform, query, and analyze their FHIR-formatted data in a consistent fashion in the cloud.

Amazon Machine Learning

Definition of the public APIs exposed by Amazon Machine Learning

Amazon CloudDirectory

Amazon Cloud Directory Amazon Cloud Directory is a component of the AWS Directory Service that simplifies the development and management of cloud-scale web, mobile, and IoT applications. This guide describes the Cloud Directory operations that you can call programmatically and includes detailed information on data types and errors. For information about Cloud Directory features, see AWS Directory Service and the Amazon Cloud Directory Developer Guide.

AWS Lambda

Lambda Overview This is the Lambda API Reference. The Lambda Developer Guide provides additional information. For the service overview, see What is Lambda, and for information about how the service works, see Lambda: How it Works in the Lambda Developer Guide.

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Amazon Mechanical Turk

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AWS Import/Export

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