Mock sample for your project: AzureBridgeAdminClient API

Use these APIs to manage Azure CDN resources through the Azure Resource Manager. You must make sure that requests made to these resources are secure.

Azure Log Analytics API reference for Query Packs management.

Edge gateway operation endpoints and objects.

Use these REST APIs for performing operations on Identity Provider entity associated with your Azure API Management deployment. Setting up an external Identity Provider for authentication can help you manage the developer portal logins using the OAuth2 flow.

The Admin Storage Management Client.

The Admin Backup Management Client.

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.

Use these REST APIs for performing retrieve a collection of Apis associated with a tag in Azure API Management deployment.

Use these REST APIs to get the analytics reports associated with your Azure API Management deployment.

Cognitive Services Management Client

Azure Customer Lockbox API Reference

Azure EventGrid Management Client

The DNS Management Client.

Azure Event Hubs client for managing Event Hubs Cluster, IPFilter Rules and VirtualNetworkRules resources.

Consumption management client provides access to consumption resources for Azure Enterprise Subscriptions.

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.