Mock sample for your project: NetworkManagementClient API

Integrate with "NetworkManagementClient API" from azure.com in no time with Mockoon's ready to use mock sample

NetworkManagementClient

azure.com

Version: 2019-08-01


Use this API in your project

Speed up your application development by using "NetworkManagementClient API" ready-to-use mock sample. Mocking this API will help you accelerate your development lifecycles and allow you to stop relying on an external API to get the job done. No more API keys to provision, accesses to configure or unplanned downtime, just work.
Enhance your development infrastructure by mocking third party APIs during integrating testing.

Description

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.

Other APIs by azure.com

FabricAdminClient

azure.com
Storage subsystem operation endpoints and objects.

ExpressRouteCrossConnection REST APIs

azure.com
The Microsoft Azure ExpressRouteCrossConnection Resource Provider REST APIs describes the operations for the connectivity provider to provision ExpressRoute circuit, create and modify BGP peering entities and troubleshoot connectivity on customer's ExpressRoute circuit.

ContainerServiceClient

azure.com
The Container Service Client.

SharedImageGalleryServiceClient

azure.com
Shared Image Gallery Service Client.

CustomerInsightsManagementClient

azure.com
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.

Anomaly Detector Client

azure.com
The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.

HyperDrive

azure.com
HyperDrive REST API

Azure Data Catalog Resource Provider

azure.com
The Azure Data Catalog Resource Provider Services API.

Azure ML Commitment Plans Management Client

azure.com
These APIs allow end users to operate on Azure Machine Learning Commitment Plans resources and their child Commitment Association resources. They support CRUD operations for commitment plans, get and list operations for commitment associations, moving commitment associations between commitment plans, and retrieving commitment plan usage history.

StorageManagementClient

azure.com
The Admin Storage Management Client.

VirtualMachineImageTemplate

azure.com
Virtual Machine Image Template

DiskResourceProviderClient

azure.com
The Disk Resource Provider Client.

Other APIs in the same category

AWS IoT Analytics

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

Managed Streaming for Kafka

The operations for managing an Amazon MSK cluster.

FrontDoorManagementClient

azure.com
Use these APIs to manage Azure Front Door resources through the Azure Resource Manager. You must make sure that requests made to these resources are secure.

Security Center

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

PolicyEventsClient

azure.com

Mixed Reality

azure.com
Mixed Reality Resource Provider Proxy API

CognitiveServicesManagementClient

azure.com
Cognitive Services Management Client

AWS Import/Export

AWS Import/Export Service AWS Import/Export accelerates transferring large amounts of data between the AWS cloud and portable storage devices that you mail to us. AWS Import/Export transfers data directly onto and off of your storage devices using Amazon's high-speed internal network and bypassing the Internet. For large data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.

customproviders

azure.com
Allows extension of ARM control plane with custom resource providers.

Amazon Appflow

Welcome to the Amazon AppFlow API reference. This guide is for developers who need detailed information about the Amazon AppFlow API operations, data types, and errors. Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between software as a service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and Amazon Web Services like Amazon S3 and Amazon Redshift. Use the following links to get started on the Amazon AppFlow API: Actions : An alphabetical list of all Amazon AppFlow API operations. Data types : An alphabetical list of all Amazon AppFlow data types. Common parameters : Parameters that all Query operations can use. Common errors : Client and server errors that all operations can return. If you're new to Amazon AppFlow, we recommend that you review the Amazon AppFlow User Guide. Amazon AppFlow API users can use vendor-specific mechanisms for OAuth, and include applicable OAuth attributes (such as auth-code and redirecturi) with the connector-specific ConnectorProfileProperties when creating a new connector profile using Amazon AppFlow API operations. For example, Salesforce users can refer to the Authorize Apps with OAuth documentation.

AWS Lake Formation

AWS Lake Formation Defines the public endpoint for the AWS Lake Formation service.

MonitorManagementClient

azure.com