Mock sample for your project: SubscriptionClient API

Azure Application Insights client for web test based alerting.

The Admin Fabric Management Client.

Use these REST APIs to manage Azure API Management deployment.

Drive operation endpoints and objects.

The Admin Backup Management Client.

The Admin Commerce Management Client.

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

Amazon QuickSight API Reference Amazon QuickSight is a fully managed, serverless business intelligence service for the Amazon Web Services Cloud that makes it easy to extend data and insights to every user in your organization. This API reference contains documentation for a programming interface that you can use to manage Amazon QuickSight.

The Container Service Client.

Time Series Insights environment data plane client for PAYG (Preview L1 SKU) environments.

Azure NotificationHub client

Resource Provider

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

Dev Spaces REST API

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

The HDInsight Job Client.

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 Container Service Client.