Mock sample for your project: AppServiceCertificateOrders API Client

Azure resources can be locked to prevent other users in your organization from deleting or modifying resources.

Storage system operation endpoints and objects.

Use these REST APIs for performing operations on Diagnostic entity associated with your Azure API Management deployment. Diagnostics are used to log requests/responses in the APIM proxy.

Azure Application Insights client for favorites.

Drive operation endpoints and objects.

Azure Log Analytics API reference for management of saved Queries within Query Packs.

This Swagger was generated by the API Framework.

Migrate your workloads to Azure.

Resource Provider

Provides create, read, update and delete functionality for Azure SQL Database resources including servers, databases, elastic pools, recommendations, operations, and usage metrics.

Subscription client provides an interface to create and manage Azure subscriptions programmatically.

Identity and Access Management Access Analyzer helps identify potential resource-access risks by enabling you to identify any policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview and validate public and cross-account access to your resources before deploying permissions changes. This guide describes the Identity and Access Management Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide. To start using IAM Access Analyzer, you first need to create an analyzer.

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 and configurations with new business model.

Provides create, read, update and delete functionality for Azure SQL Database resources including recommendations and operations.

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.