Mock sample for your project: Microsoft Insights API

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

These are the Network Experiment APIs.

Creates an Azure Data Lake Store filesystem client.

The Azure BatchAI Management API.

The Azure Customer Insights management API provides a RESTful set of web services that interact with Azure Customer Insights service to manage your resources. The API has entities that capture the relationship between an end user and the Azure Customer Insights service.

Storage subsystem operation endpoints and objects.

The service is used to perform ink layout and recognition of written words and shapes. Ink strokes passed to the service are recognized and organized into recognition results in the response

The Anomaly Finder API detects anomalies automatically in time series data. It supports two functionalities, one is for detecting the whole series with model trained by the timeseries, another is detecting last point with model trained by points before. By using this service, business customers can discover incidents and establish a logic flow for root cause analysis.

REST APIs for Azure Active Directory Connect Health

This Swagger was generated by the API Framework.

IoT data IoT data enables secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. It implements a broker for applications and things to publish messages over HTTP (Publish) and retrieve, update, and delete shadows. A shadow is a persistent representation of your things and their state in the Amazon Web Services cloud. Find the endpoint address for actions in IoT data by running this CLI command: aws iot describe-endpoint --endpoint-type iot:Data-ATS The service name used by Amazon Web ServicesSignature Version 4 to sign requests is: iotdevicegateway.

The Azure Data Catalog Resource Provider Services API.

The Admin Subscriptions Management Client.

AWS Organizations is a web service that enables you to consolidate your multiple AWS accounts into an organization and centrally manage your accounts and their resources. This guide provides descriptions of the Organizations operations. For more information about using this service, see the AWS Organizations User Guide. Support and feedback for AWS Organizations We welcome your feedback. Send your comments to [email protected] or post your feedback and questions in the AWS Organizations support forum. For more information about the AWS support forums, see Forums Help. Endpoint to call When using the AWS CLI or the AWS SDK For the current release of Organizations, specify the us-east-1 region for all AWS API and AWS CLI calls made from the commercial AWS Regions outside of China. If calling from one of the AWS Regions in China, then specify cn-northwest-1. You can do this in the AWS CLI by using these parameters and commands: Use the following parameter with each command to specify both the endpoint and its region: --endpoint-url https://organizations.us-east-1.amazonaws.com (from commercial AWS Regions outside of China) or --endpoint-url https://organizations.cn-northwest-1.amazonaws.com.cn (from AWS Regions in China) Use the default endpoint, but configure your default region with this command: aws configure set default.region us-east-1 (from commercial AWS Regions outside of China) or aws configure set default.region cn-northwest-1 (from AWS Regions in China) Use the following parameter with each command to specify the endpoint: --region us-east-1 (from commercial AWS Regions outside of China) or --region cn-northwest-1 (from AWS Regions in China) Recording API Requests AWS Organizations supports AWS CloudTrail, a service that records AWS API calls for your AWS account and delivers log files to an Amazon S3 bucket. By using information collected by AWS CloudTrail, you can determine which requests the Organizations service received, who made the request and when, and so on. For more about AWS Organizations and its support for AWS CloudTrail, see Logging AWS Organizations Events with AWS CloudTrail in the AWS Organizations User Guide. To learn more about AWS CloudTrail, including how to turn it on and find your log files, see the AWS CloudTrail User Guide.

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.

Elastic Load Balancing A load balancer distributes incoming traffic across targets, such as your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered targets and ensures that it routes traffic only to healthy targets. 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. You configure a target group with a protocol and port number for connections from the load balancer to the targets, and with health check settings to be used when checking the health status of the targets. Elastic Load Balancing supports the following types of load balancers: Application Load Balancers, Network Load Balancers, Gateway Load Balancers, and Classic Load Balancers. This reference covers the following load balancer types: Application Load Balancer - Operates at the application layer (layer 7) and supports HTTP and HTTPS. Network Load Balancer - Operates at the transport layer (layer 4) and supports TCP, TLS, and UDP. Gateway Load Balancer - Operates at the network layer (layer 3). For more information, see the Elastic Load Balancing User Guide. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds.

Amazon Personalize can consume real-time user event data, such as stream or click data, and use it for model training either alone or combined with historical data. For more information see Recording Events.

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 and configurations with new business model.

API to Add/Remove/List Guest Diagnostics Configuration to Azure Resources

Amazon DynamoDB Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database, so that you don't have to worry about hardware provisioning, setup and configuration, replication, software patching, or cluster scaling. With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic. You can scale up or scale down your tables' throughput capacity without downtime or performance degradation, and use the AWS Management Console to monitor resource utilization and performance metrics. DynamoDB automatically spreads the data and traffic for your tables over a sufficient number of servers to handle your throughput and storage requirements, while maintaining consistent and fast performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across multiple Availability Zones in an AWS region, providing built-in high availability and data durability.