Mock sample for your project: GalleryManagementClient API

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

GalleryManagementClient

azure.com

Version: 2015-04-01


Use this API in your project

Integrate third-party APIs faster by using "GalleryManagementClient API" ready-to-use mock sample. Mocking this API will help you accelerate your development lifecycles and improves your integration tests' quality and reliability by accounting for random failures, slow response time, etc.
It also helps reduce your dependency on third-party APIs: no more accounts to create, API keys to provision, accesses to configure, unplanned downtime, etc.

Description

The Admin Gallery Management Client.

Other APIs by azure.com

MonitorManagementClient

azure.com

Face Client

azure.com
An API for face detection, verification, and identification.

ApplicationInsightsManagementClient

azure.com
Apis for customer in enterprise agreement migrate to new pricing model or rollback to legacy pricing model.

WorkbookClient

azure.com
Azure client for Workbook.

AutomationManagement

azure.com

AutomationManagementClient

azure.com

AutomationManagement

azure.com

AutomationManagement

azure.com

AutomationManagement

azure.com

Machine Learning Workspaces Management Client

azure.com
These APIs allow end users to operate on Azure Machine Learning Workspace resources. They support CRUD operations for Azure Machine Learning Workspaces.

ApplicationInsightsManagementClient

azure.com
Azure Application Insights client for favorites.

ApiManagementClient

azure.com
Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

Other APIs in the same category

AWSServerlessApplicationRepository

The AWS Serverless Application Repository makes it easy for developers and enterprises to quickly find
and deploy serverless applications in the AWS Cloud. For more information about serverless applications,
see Serverless Computing and Applications on the AWS website. The AWS Serverless Application Repository is deeply integrated with the AWS Lambda console, so that developers of
all levels can get started with serverless computing without needing to learn anything new. You can use category
keywords to browse for applications such as web and mobile backends, data processing applications, or chatbots.
You can also search for applications by name, publisher, or event source. To use an application, you simply choose it,
configure any required fields, and deploy it with a few clicks. You can also easily publish applications, sharing them publicly with the community at large, or privately
within your team or across your organization. To publish a serverless application (or app), you can use the
AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs to upload the code. Along with the
code, you upload a simple manifest file, also known as the AWS Serverless Application Model (AWS SAM) template.
For more information about AWS SAM, see AWS Serverless Application Model (AWS SAM) on the AWS Labs
GitHub repository. The AWS Serverless Application Repository Developer Guide contains more information about the two developer
experiences available:
Consuming Applications – Browse for applications and view information about them, including
source code and readme files. Also install, configure, and deploy applications of your choosing.
Publishing Applications – Configure and upload applications to make them available to other
developers, and publish new versions of applications.

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.

Security Center

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

Azure Media Services

azure.com
This Swagger was generated by the API Framework.

Microsoft NetApp

azure.com
Microsoft NetApp Azure Resource Provider specification

MySQLManagementClient

azure.com
The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MySQL resources including servers, databases, firewall rules, VNET rules, security alert policies, log files and configurations with new business model.

MariaDBManagementClient

azure.com
The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MariaDB resources including servers, databases, firewall rules, VNET rules, security alert policies, log files and configurations with new business model.

MonitorManagementClient

azure.com

MonitorManagementClient

azure.com

MonitorManagementClient

azure.com

Azure Maps Resource Provider

azure.com
Resource Provider

MonitorManagementClient

azure.com