Mock sample for your project: MariaDBManagementClient API

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.

Infrastructure role operation endpoints and objects.

Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

Creates an Azure Data Lake Analytics account management client.

The Admin Storage Management Client.

Azure Cosmos DB Database Service Resource Provider REST API

The Compute Management Client.

The Admin Storage Management Client.

Update run operation endpoints and objects.

Deployment Admin Client.

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

API to Add/Remove/List Guest Diagnostics Configuration to Azure Resources

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MySQL resources including servers, databases, firewall rules, VNET rules, security alert policies, log files and configurations with new business model.

Amazon Lex provides both build and runtime endpoints. Each endpoint provides a set of operations (API). Your conversational bot uses the runtime API to understand user utterances (user input text or voice). For example, suppose a user says "I want pizza", your bot sends this input to Amazon Lex using the runtime API. Amazon Lex recognizes that the user request is for the OrderPizza intent (one of the intents defined in the bot). Then Amazon Lex engages in user conversation on behalf of the bot to elicit required information (slot values, such as pizza size and crust type), and then performs fulfillment activity (that you configured when you created the bot). You use the build-time API to create and manage your Amazon Lex bot. For a list of build-time operations, see the build-time API, .

Azure Application Insights workbook type.

Azure Event Hubs client

The Anomaly Finder API detects anomalies automatically in time series data. It supports two functionalities, one is for detecting the whole series with model trained by the timeseries, another is detecting last point with model trained by points before. By using this service, business customers can discover incidents and establish a logic flow for root cause analysis.

Elastic Inference public APIs.

Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

Provides read and update functionality for Azure SQL Server backup long term retention vault

AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data. AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management. AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.