Mock sample for your project: SearchManagementClient API

The Admin Storage Management Client.

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

Client that can be used to manage and query indexes and documents, as well as manage other resources, on a search service.

The Disk Resource Provider Client.

The Admin Storage Management Client.

IP pool operation endpoints and objects.

Cognitive Services Management Client

Azure Log Analytics API reference for management of saved Queries within Query Packs.

The Admin Storage Management Client.

Use these REST APIs for performing operations on Backend entity in Azure API Management deployment. The Backend entity in API Management represents a backend service that is configured to skip certification chain validation when using a self-signed certificate to test mutual certificate authentication.

The Admin Commerce Management Client.

Specification for ManagedServices.

Billing client provides access to billing resources for Azure subscriptions.

Amazon Kinesis Data Analytics is a fully managed service that you can use to process and analyze streaming data using Java, SQL, or Scala. The service enables you to quickly author and run Java, SQL, or Scala code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.

The REST API specification for Ably.

Use these APIs to manage Azure Front Door resources through the Azure Resource Manager. You must make sure that requests made to these resources are secure.

APIs to manage web application firewall rules for Azure CDN

Infrastructure role operation endpoints and objects.

Compute Optimizer is a service that analyzes the configuration and utilization metrics of your Amazon Web Services compute resources, such as Amazon EC2 instances, Amazon EC2 Auto Scaling groups, Lambda functions, and Amazon EBS volumes. It reports whether your resources are optimal, and generates optimization recommendations to reduce the cost and improve the performance of your workloads. Compute Optimizer also provides recent utilization metric data, in addition to projected utilization metric data for the recommendations, which you can use to evaluate which recommendation provides the best price-performance trade-off. The analysis of your usage patterns can help you decide when to move or resize your running resources, and still meet your performance and capacity requirements. For more information about Compute Optimizer, including the required permissions to use the service, see the Compute Optimizer User Guide.

This section provides documentation for the AWS RoboMaker API operations.