Mock sample for your project: Update Management API

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

Azure Application Insights client for Annotations for a component.

Deployment Admin Client.

Use this API to manage the IoT hubs in your Azure subscription.

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

These APIs allow end users to operate on Azure Machine Learning Compute resources. They support the following operations: Create or update a cluster Get a cluster Patch a cluster Delete a cluster Get keys for a cluster Check if updates are available for system services in a cluster Update system services in a cluster Get all clusters in a resource group Get all clusters in a subscription

Azure Application Insights client for web test based alerting.

Use these REST APIs for performing retrieve a collection of Apis associated with a tag in Azure API Management deployment.

The Azure Management Groups API enables consolidation of multiple subscriptions/resources into an organizational hierarchy and centrally manage access control, policies, alerting and reporting for those resources.

These APIs allow end users to operate on Azure Machine Learning Team Account resources. They support CRUD operations for Azure Machine Learning Team Accounts.

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.

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.

The service for managing third party addons.

AWS Step Functions AWS Step Functions is a service that lets you coordinate the components of distributed applications and microservices using visual workflows. You can use Step Functions to build applications from individual components, each of which performs a discrete function, or task, allowing you to scale and change applications quickly. Step Functions provides a console that helps visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step, and retries steps when there are errors, so your application executes predictably and in the right order every time. Step Functions logs the state of each step, so you can quickly diagnose and debug any issues. Step Functions manages operations and underlying infrastructure to ensure your application is available at any scale. You can run tasks on AWS, your own servers, or any system that has access to AWS. You can access and use Step Functions using the console, the AWS SDKs, or an HTTP API. For more information about Step Functions, see the AWS Step Functions Developer Guide .

Welcome to the AWS Ground Station API Reference. AWS Ground Station is a fully managed service that enables you to control satellite communications, downlink and process satellite data, and scale your satellite operations efficiently and cost-effectively without having to build or manage your own ground station infrastructure.

Glue Defines the public endpoint for the Glue service.

Use these REST APIs for performing operations on Certificate entity in your Azure API Management deployment. Certificates can be used to setup mutual authentication with your Backend in API Management. For more information refer to How to secure backend using Mutual Auth Certificate.

Provides APIs for creating and managing Amazon Forecast resources.

Amazon DynamoDB Amazon DynamoDB Streams provides API actions for accessing streams and processing stream records. To learn more about application development with Streams, see Capturing Table Activity with DynamoDB Streams in the Amazon DynamoDB Developer Guide.

Amazon Web Services Transfer Family is a fully managed service that enables the transfer of files over the File Transfer Protocol (FTP), File Transfer Protocol over SSL (FTPS), or Secure Shell (SSH) File Transfer Protocol (SFTP) directly into and out of Amazon Simple Storage Service (Amazon S3). Amazon Web Services helps you seamlessly migrate your file transfer workflows to Amazon Web Services Transfer Family by integrating with existing authentication systems, and providing DNS routing with Amazon Route 53 so nothing changes for your customers and partners, or their applications. With your data in Amazon S3, you can use it with Amazon Web Services services for processing, analytics, machine learning, and archiving. Getting started with Amazon Web Services Transfer Family is easy since there is no infrastructure to buy and set up.

Recovery Control Configuration API Reference for Amazon Route 53 Application Recovery Controller

With Application Auto Scaling, you can configure automatic scaling for the following resources: Amazon AppStream 2.0 fleets Amazon Aurora Replicas Amazon Comprehend document classification and entity recognizer endpoints Amazon DynamoDB tables and global secondary indexes throughput capacity Amazon ECS services Amazon ElastiCache for Redis clusters (replication groups) Amazon EMR clusters Amazon Keyspaces (for Apache Cassandra) tables Lambda function provisioned concurrency Amazon Managed Streaming for Apache Kafka broker storage Amazon SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services API Summary The Application Auto Scaling service API includes three key sets of actions: Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets. Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history. Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.