Mock sample for your project: SqlManagementClient API

A Storage Cache provides scalable caching service for NAS clients, serving data from either NFSv3 or Blob at-rest storage (referred to as "Storage Targets"). These operations allow you to manage Caches.

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.

HyperDrive REST API

Azure Maintenance Management Client

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

Creates an Azure Data Lake Store filesystem client.

The DNS Management Client.

API spec for Microsoft.Security (Azure Security Center) resource provider

The HDInsight Management Client.

The HDInsight Job Client.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

Azure Event Hubs client

The Microsoft Azure ExpressRouteCrossConnection Resource Provider REST APIs describes the operations for the connectivity provider to provision ExpressRoute circuit, create and modify BGP peering entities and troubleshoot connectivity on customer's ExpressRoute circuit.

The Admin Backup Management Client.

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

The Container Service Client.

Specification for ManagedServices.

Amazon Web Services Transfer Family is a fully managed service that enables the transfer of files over the File Transfer Protocol (FTP), File Transfer Protocol over SSL (FTPS), or Secure Shell (SSH) File Transfer Protocol (SFTP) directly into and out of Amazon Simple Storage Service (Amazon S3). Amazon Web Services helps you seamlessly migrate your file transfer workflows to Amazon Web Services Transfer Family by integrating with existing authentication systems, and providing DNS routing with Amazon Route 53 so nothing changes for your customers and partners, or their applications. With your data in Amazon S3, you can use it with Amazon Web Services services for processing, analytics, machine learning, and archiving. Getting started with Amazon Web Services Transfer Family is easy since there is no infrastructure to buy and set up.

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.

Migrate your workloads to Azure.