Mock sample for your project: windowsesu 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 and configurations with new business model.

APIs for managing software update configurations.

File share operation endpoints and objects.

Azure Enterprise Knowledge Graph Service is a platform for creating knowledge graphs at scale.

Azure Cosmos DB Database Service Resource Provider REST API

Deployment Admin Client.

Shared Image Gallery Service Client.

Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

The HDInsight Management Client.

Dev Spaces REST API

The Azure management API provides a RESTful set of web services that interact with Azure Key Vault.

Operation status operation endpoints and objects.

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.

Use these REST APIs to manage Azure API Management deployment.

The Admin Compute Disk Management Client.

Infrastructure role instance operation endpoints and objects.

The Admin Storage Management Client.

AWS Route53 Recovery Readiness

Azure Active Directory Client.

Region health operation endpoints and objects.

Drive operation endpoints and objects.

Elastic Load Balancing A load balancer can distribute incoming traffic across your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered instances and ensures that it routes traffic only to healthy instances. You configure your load balancer to accept incoming traffic by specifying one or more listeners, which are configured with a protocol and port number for connections from clients to the load balancer and a protocol and port number for connections from the load balancer to the instances. Elastic Load Balancing supports three types of load balancers: Application Load Balancers, Network Load Balancers, and Classic Load Balancers. You can select a load balancer based on your application needs. For more information, see the Elastic Load Balancing User Guide. This reference covers the 2012-06-01 API, which supports Classic Load Balancers. The 2015-12-01 API supports Application Load Balancers and Network Load Balancers. To get started, create a load balancer with one or more listeners using CreateLoadBalancer. Register your instances with the load balancer using RegisterInstancesWithLoadBalancer. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds with a 200 OK response code.