Mock sample for your project: MonitorManagementClient API

Provides operations for working with resources and resource groups.

Azure Application Insights client for API keys of a component.

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These operations enable you to manage role definitions and role assignments. A role definition describes the set of actions that can be performed on resources. A role assignment grants access to Azure Active Directory users.

The Admin Gallery Management Client.

The Admin Backup Management Client.

Deployment Admin Client.

An API for face detection, verification, and identification.

Storage subsystem operation endpoints and objects.

The Admin Subscriptions Management Client.

Creates an Azure Data Lake Store account management client.

The Azure Storage Management API.

The Azure Management Groups API enables consolidation of multiple subscriptions/resources into an organizational hierarchy and centrally manage access control, policies, alerting and reporting for those resources.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

The Container Service Client.

Use this API to manage Microsoft HealthcareApis services in your Azure subscription.

Migrate your workloads to Azure.

REST API for MarketplaceOrdering Agreements.

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.

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