Mock sample for your project: MonitorManagementClient API

The AAD Domain Services API.

Mixed Reality Resource Provider Proxy API

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.

Assess your workloads for Azure.

Media Services resource management APIs.

Migrate your workloads to Azure.

Mixed Reality Resource Provider REST API

This Swagger was generated by the API Framework.

Mixed Reality Resource Provider Remote Rendering Resource API

Azure Monitor client to create/update/delete metric based alerts.

Azure Monitor API reference for Private Links Scopes management.

The Azure SQL Database management API provides a RESTful set of web services that interact with Azure SQL Database services to manage your external server administrators.

AWS IoT Events monitors your equipment or device fleets for failures or changes in operation, and triggers actions when such events occur. You can use AWS IoT Events API operations to create, read, update, and delete inputs and detector models, and to list their versions.

Billing client provides access to billing resources for Azure subscriptions.

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These calls handle provider operations.

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

Azure Application Insights client for Annotations for a component.

Amazon EMR is a web service that makes it easier to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several Amazon Web Services services to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehouse management.

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.

You can use the Amazon Elastic Block Store (Amazon EBS) direct APIs to create Amazon EBS snapshots, write data directly to your snapshots, read data on your snapshots, and identify the differences or changes between two snapshots. If you’re an independent software vendor (ISV) who offers backup services for Amazon EBS, the EBS direct APIs make it more efficient and cost-effective to track incremental changes on your Amazon EBS volumes through snapshots. This can be done without having to create new volumes from snapshots, and then use Amazon Elastic Compute Cloud (Amazon EC2) instances to compare the differences. You can create incremental snapshots directly from data on-premises into volumes and the cloud to use for quick disaster recovery. With the ability to write and read snapshots, you can write your on-premises data to an snapshot during a disaster. Then after recovery, you can restore it back to Amazon Web Services or on-premises from the snapshot. You no longer need to build and maintain complex mechanisms to copy data to and from Amazon EBS. This API reference provides detailed information about the actions, data types, parameters, and errors of the EBS direct APIs. For more information about the elements that make up the EBS direct APIs, and examples of how to use them effectively, see Accessing the Contents of an Amazon EBS Snapshot in the Amazon Elastic Compute Cloud User Guide. For more information about the supported Amazon Web Services Regions, endpoints, and service quotas for the EBS direct APIs, see Amazon Elastic Block Store Endpoints and Quotas in the Amazon Web Services General Reference.

Doc Engage API - Amazon Pinpoint API

Azure Application Insights workbook type.

Savings Plans are a pricing model that offer significant savings on AWS usage (for example, on Amazon EC2 instances). You commit to a consistent amount of usage, in USD per hour, for a term of 1 or 3 years, and receive a lower price for that usage. For more information, see the AWS Savings Plans User Guide.