Mock sample for your project: MediaServicesManagementClient API

Provides create, read, update and delete functionality Azure SQL server communication links.

REST API for Azure VirtualWAN As a Service.

This Swagger was generated by the API Framework.

Microsoft Azure Mobile Engagement REST APIs.

This API exposes Azure Log Analytics query capabilities

The APIs listed in this specification can be used to manage Deployment Scripts resource through the Azure Resource Manager.

This Swagger was generated by the API Framework.

Describes the interface for the per-tenant enclave service.

Azure Log Analytics API reference for Solution.

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

Load balancer admin operation endpoints and objects.

The Admin Storage Management Client.

Amazon Lex Build-Time Actions Amazon Lex is an AWS service for building conversational voice and text interfaces. Use these actions to create, update, and delete conversational bots for new and existing client applications.

The AWS Cost and Usage Report API enables you to programmatically create, query, and delete AWS Cost and Usage report definitions. AWS Cost and Usage reports track the monthly AWS costs and usage associated with your AWS account. The report contains line items for each unique combination of AWS product, usage type, and operation that your AWS account uses. You can configure the AWS Cost and Usage report to show only the data that you want, using the AWS Cost and Usage API. Service Endpoint The AWS Cost and Usage Report API provides the following endpoint: cur.us-east-1.amazonaws.com

Amazon Mechanical Turk API Reference

APIs for managing software update configurations.

Amazon Comprehend is an AWS service for gaining insight into the content of documents. Use these actions to determine the topics contained in your documents, the topics they discuss, the predominant sentiment expressed in them, the predominant language used, and more.

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.

Deployment Admin Client.

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