Mock sample for your project: ResourceManagementClient API

API to Add/Remove/List Guest Diagnostics Settings Association for Azure Resources

These are the Network Experiment APIs.

Use these REST APIs for performing operations on the ApiVersionSet entity associated with your Azure API Management deployment. Using this entity you create and manage API Version Sets that are used to group APIs for consistent versioning.

Public IP Address admin endpoints and objects.

Resource health operation endpoints and objects.

Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

An API for QnAMaker runtime

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

ARM Databricks

REST APIs for Azure Active Directory Connect Health

The FinSpace APIs let you take actions inside the FinSpace environment.

Use these REST APIs for performing operations on entities like API, Product, and Subscription associated with your Azure API Management deployment.

Amazon Web Services Systems Manager is a collection of capabilities that helps you automate management tasks such as collecting system inventory, applying operating system (OS) patches, automating the creation of Amazon Machine Images (AMIs), and configuring operating systems (OSs) and applications at scale. Systems Manager lets you remotely and securely manage the configuration of your managed instances. A managed instance is any Amazon Elastic Compute Cloud instance (EC2 instance), or any on-premises server or virtual machine (VM) in your hybrid environment that has been configured for Systems Manager. This reference is intended to be used with the Amazon Web Services Systems Manager User Guide. To get started, verify prerequisites and configure managed instances. For more information, see Setting up Amazon Web Services Systems Manager in the Amazon Web Services Systems Manager User Guide. Related resources For information about how to use a Query API, see Making API requests. For information about other API operations you can perform on EC2 instances, see the Amazon EC2 API Reference. For information about AppConfig, a capability of Systems Manager, see the AppConfig User Guide and the AppConfig API Reference. For information about Incident Manager, a capability of Systems Manager, see the Incident Manager User Guide and the Incident Manager API Reference.

Amazon EC2 Auto Scaling Amazon EC2 Auto Scaling is designed to automatically launch or terminate EC2 instances based on user-defined scaling policies, scheduled actions, and health checks. For more information about Amazon EC2 Auto Scaling, see the Amazon EC2 Auto Scaling User Guide. For information about granting IAM users required permissions for calls to Amazon EC2 Auto Scaling, see Granting IAM users required permissions for Amazon EC2 Auto Scaling resources in the Amazon EC2 Auto Scaling API Reference.

The SAP HANA on Azure Management Client.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

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

MemoryDB for Redis is a fully managed, Redis-compatible, in-memory database that delivers ultra-fast performance and Multi-AZ durability for modern applications built using microservices architectures. MemoryDB stores the entire database in-memory, enabling low latency and high throughput data access. It is compatible with Redis, a popular open source data store, enabling you to leverage Redis’ flexible and friendly data structures, APIs, and commands.

AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data. AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management. AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.

AWS Route53 Recovery Readiness