Mock sample for your project: Azure Media Services API

The Hybrid Compute Management Client.

Logical network operation endpoints and objects.

Azure Maintenance Management Client

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, encryption keys, active directory administrator and configurations.

The Resource Health Client.

API for using the Azure IoT Hub Device Provisioning Service features.

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.

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

Box Platform provides functionality to provide access to content stored within Box. It provides endpoints for basic manipulation of files and folders, management of users within an enterprise, as well as more complex topics such as legal holds and retention policies.

Migrate your workloads to Azure.

The HDInsight Management Client.

Microsoft.Intune Resource provider Api features in the swagger-2.0 specification

The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.

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.

Azure Cosmos DB Database Service Resource Provider REST API

An API for QnAMaker Service

Amazon Textract detects and analyzes text in documents and converts it into machine-readable text. This is the API reference documentation for Amazon Textract.

ARM Databricks