Mock sample for your project: Azure Enterprise Knowledge Graph Service API

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.

Streaming resource management client for Azure Media Services

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 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.

A client for issuing REST requests to the Azure metrics service.

This Swagger was generated by the API Framework.

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.

Use these REST APIs for performing operations on Product entity associated with your Azure API Management deployment. The Product entity represents a product in API Management. Products include one or more APIs and their associated terms of use. Once a product is published, developers can subscribe to the product and begin to use the product’s APIs.

Deployment Admin Client.

REST API for Azure Blockchain Service

REST APIs for Azure Advisor

AWS IoT Secure Tunneling AWS IoT Secure Tunnling enables you to create remote connections to devices deployed in the field. For more information about how AWS IoT Secure Tunneling works, see AWS IoT Secure Tunneling.

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.

Amazon CloudWatch monitors your Amazon Web Services (Amazon Web Services) resources and the applications you run on Amazon Web Services in real time. You can use CloudWatch to collect and track metrics, which are the variables you want to measure for your resources and applications. CloudWatch alarms send notifications or automatically change the resources you are monitoring based on rules that you define. For example, you can monitor the CPU usage and disk reads and writes of your Amazon EC2 instances. Then, use this data to determine whether you should launch additional instances to handle increased load. You can also use this data to stop under-used instances to save money. In addition to monitoring the built-in metrics that come with Amazon Web Services, you can monitor your own custom metrics. With CloudWatch, you gain system-wide visibility into resource utilization, application performance, and operational health.

Storage Gateway Service Storage Gateway is the service that connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration between an organization's on-premises IT environment and the Amazon Web Services storage infrastructure. The service enables you to securely upload data to the Cloud for cost effective backup and rapid disaster recovery. Use the following links to get started using the Storage Gateway Service API Reference : Storage Gateway required request headers : Describes the required headers that you must send with every POST request to Storage Gateway. Signing requests : Storage Gateway requires that you authenticate every request you send; this topic describes how sign such a request. Error responses : Provides reference information about Storage Gateway errors. Operations in Storage Gateway : Contains detailed descriptions of all Storage Gateway operations, their request parameters, response elements, possible errors, and examples of requests and responses. Storage Gateway endpoints and quotas : Provides a list of each Region and the endpoints available for use with Storage Gateway. Storage Gateway resource IDs are in uppercase. When you use these resource IDs with the Amazon EC2 API, EC2 expects resource IDs in lowercase. You must change your resource ID to lowercase to use it with the EC2 API. For example, in Storage Gateway the ID for a volume might be vol-AA22BB012345DAF670. When you use this ID with the EC2 API, you must change it to vol-aa22bb012345daf670. Otherwise, the EC2 API might not behave as expected. IDs for Storage Gateway volumes and Amazon EBS snapshots created from gateway volumes are changing to a longer format. Starting in December 2016, all new volumes and snapshots will be created with a 17-character string. Starting in April 2016, you will be able to use these longer IDs so you can test your systems with the new format. For more information, see Longer EC2 and EBS resource IDs. For example, a volume Amazon Resource Name (ARN) with the longer volume ID format looks like the following: arn:aws:storagegateway:us-west-2:111122223333:gateway/sgw-12A3456B/volume/vol-1122AABBCCDDEEFFG. A snapshot ID with the longer ID format looks like the following: snap-78e226633445566ee. For more information, see Announcement: Heads-up – Longer Storage Gateway volume and snapshot IDs coming in 2016.

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 .

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.

Amazon Mobile Analytics is a service for collecting, visualizing, and understanding app usage data at scale.

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.