Mock sample for your project: AzureBridgeAdminClient API

The DevTest Labs Client.

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.

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.

Use these REST APIs for querying APIs. Operations and Products by tags in your Azure API Management deployment.

The Managed Labs Client.

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

REST API for Azure Redis Cache Service.

To manage and control access to your resources, you can define customized policies and assign them at a scope.

Provides create, read and update functionality for database Threat Detection policies.

Use these REST APIs for performing operations on Identity Provider entity associated with your Azure API Management deployment. Setting up an external Identity Provider for authentication can help you manage the developer portal logins using the OAuth2 flow.

Directory Service Directory Service is a web service that makes it easy for you to setup and run directories in the Amazon Web Services cloud, or connect your Amazon Web Services resources with an existing self-managed Microsoft Active Directory. This guide provides detailed information about Directory Service operations, data types, parameters, and errors. For information about Directory Services features, see Directory Service and the Directory Service Administration Guide. Amazon Web Services provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, iOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to Directory Service and other Amazon Web Services services. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools for Amazon Web Services.

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

The Admin Backup Management Client.

Amazon Managed Service for Prometheus

The Admin Backup Management Client.

Amazon CloudFront This is the Amazon CloudFront API Reference. This guide is for developers who need detailed information about CloudFront API actions, data types, and errors. For detailed information about CloudFront features, see the Amazon CloudFront Developer Guide.

Amazon ElastiCache Amazon ElastiCache is a web service that makes it easier to set up, operate, and scale a distributed cache in the cloud. With ElastiCache, customers get all of the benefits of a high-performance, in-memory cache with less of the administrative burden involved in launching and managing a distributed cache. The service makes setup, scaling, and cluster failure handling much simpler than in a self-managed cache deployment. In addition, through integration with Amazon CloudWatch, customers get enhanced visibility into the key performance statistics associated with their cache and can receive alarms if a part of their cache runs hot.

A client for issuing REST requests to the Azure Batch service.