Mock sample for your project: Recommendations API Client

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

REST API for Azure Spring Cloud

Use these REST APIs for performing operations on NamedValue entity associated with your Azure API Management deployment. API Management policies are a powerful capability of the system that allow the publisher to change the behavior of the API through configuration. Policies are a collection of statements that are executed sequentially on the request or response of an API. Policy statements can be constructed using literal text values, policy expressions, and NamedValues. Each API Management service instance has a NamedValues collection of key/value pairs that are global to the service instance. These NamedValues can be used to manage constant string values across all API configuration and policies.

REST APIs for Azure Active Directory Connect Health

These APIs allow end users to operate on Azure Machine Learning Web Services resources. They support the following operations: Create or update a web service Get a web service Patch a web service Delete a web service Get All Web Services in a Resource Group Get All Web Services in a Subscription Get Web Services Keys

The Admin Storage Management Client.

The HDInsight Management Client.

The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.

The SAP HANA on Azure Management Client.

Use these REST APIs to get the analytics reports associated with your Azure API Management deployment.

Logical subnet operation endpoints and objects.

Use these REST APIs for performing operations on Email Templates associated with your Azure API Management deployment.

Amazon RDS Data Service Amazon RDS provides an HTTP endpoint to run SQL statements on an Amazon Aurora Serverless DB cluster. To run these statements, you work with the Data Service API. For more information about the Data Service API, see Using the Data API for Aurora Serverless in the Amazon Aurora User Guide.

The AWS Migration Hub home region APIs are available specifically for working with your Migration Hub home region. You can use these APIs to determine a home region, as well as to create and work with controls that describe the home region. You must make API calls for write actions (create, notify, associate, disassociate, import, or put) while in your home region, or a HomeRegionNotSetException error is returned. API calls for read actions (list, describe, stop, and delete) are permitted outside of your home region. If you call a write API outside the home region, an InvalidInputException is returned. You can call GetHomeRegion action to obtain the account's Migration Hub home region. For specific API usage, see the sections that follow in this AWS Migration Hub Home Region API reference.

Use these REST APIs for performing operations on Group entity in your Azure API Management deployment. Groups are used to manage the visibility of products to developers. Each API Management service instance comes with the following immutable system groups whose membership is automatically managed by API Management. - Administrators - Azure subscription administrators are members of this group. - Developers - Authenticated developer portal users fall into this group. - Guests - Unauthenticated developer portal users are placed into this group. In addition to these system groups, administrators can create custom groups or leverage external groups in associated Azure Active Directory tenants. Custom and external groups can be used alongside system groups in giving developers visibility and access to API products. For example, you could create one custom group for developers affiliated with a specific partner organization and allow them access to the APIs from a product containing relevant APIs only. A user can be a member of more than one group.

The control plane for Amazon QLDB

Use these REST APIs for performing operations on Product entity associated with your Azure API Management deployment. The Product entity represents a product in API Management. Products include one or more APIs and their associated terms of use. Once a product is published, developers can subscribe to the product and begin to use the product’s APIs.

Identity and Access Management Access Analyzer helps identify potential resource-access risks by enabling you to identify any policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview and validate public and cross-account access to your resources before deploying permissions changes. This guide describes the Identity and Access Management Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide. To start using IAM Access Analyzer, you first need to create an analyzer.

Apis for customer in enterprise agreement migrate to new pricing model or rollback to legacy pricing model.

Azure Application Insights client for selecting pricing plans and options.

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.