Mock sample for your project: MaintenanceManagementClient API

Storage operation results.

The Admin Fabric Management Client.

ARM Databricks

Drive operation endpoints and objects.

The Admin Storage Management Client.

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.

API spec for Microsoft.Security (Azure Security Center) resource provider

Azure DevOps Resource Provider

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure PostgreSQL resources including servers, databases, firewall rules, VNET rules, security alert policies, log files, encryption keys, active directory administrator and configurations.

These APIs allow end users to manage Azure Machine Learning Models, Images, Profiles, and Services.

Azure Log Analytics API reference

This API describe ACE Provisioning ManagementPartner

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.

These APIs allow end users to operate on Azure Machine Learning Workspace resources. They support CRUD operations for Azure Machine Learning Workspaces.

Dev Spaces REST API