Mock sample for your project: BlueprintClient API

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

BlueprintClient

azure.com

Version: 2018-11-01-preview


Use this API in your project

Integrate third-party APIs faster by using "BlueprintClient API" ready-to-use mock sample. Mocking this API will allow you to start working in no time. No more accounts to create, API keys to provision, accesses to configure, unplanned downtime, just work.
Improve your integration tests by mocking third-party APIs and cover more edge cases: slow response time, random failures, etc.

Description

Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

Other APIs by azure.com

StorageManagementClient

azure.com
The Azure Storage Management API.

Azure Location Based Services Resource Provider

azure.com
Resource Provider

SubscriptionsManagementClient

azure.com
The Admin Subscriptions Management Client.

FabricAdminClient

azure.com
Edge gateway pool operation endpoints and objects.

CommerceManagementClient

azure.com
The Admin Commerce Management Client.

StorageManagementClient

azure.com
The Admin Storage Management Client.

UpdateAdminClient

azure.com
Update location operation endpoints and objects.

azureactivedirectory

azure.com
Azure Active Directory Client.

CostManagementClient

azure.com

customproviders

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

Cosmos DB

azure.com
Azure Cosmos DB Database Service Resource Provider REST API

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.

Other APIs in the same category

ApiManagementClient

azure.com
Use these REST APIs for performing operations on NamedValue entity associated with your Azure API Management deployment. API Management policies are a powerful capability of the system that allow the publisher to change the behavior of the API through configuration. Policies are a collection of statements that are executed sequentially on the request or response of an API. Policy statements can be constructed using literal text values, policy expressions, and NamedValues. Each API Management service instance has a NamedValues collection of key/value pairs that are global to the service instance. These NamedValues can be used to manage constant string values across all API configuration and policies.

Amazon AppConfig

AWS AppConfig Use AWS AppConfig, a capability of AWS Systems Manager, to create, manage, and quickly deploy application configurations. AppConfig supports controlled deployments to applications of any size and includes built-in validation checks and monitoring. You can use AppConfig with applications hosted on Amazon EC2 instances, AWS Lambda, containers, mobile applications, or IoT devices. To prevent errors when deploying application configurations, especially for production systems where a simple typo could cause an unexpected outage, AppConfig includes validators. A validator provides a syntactic or semantic check to ensure that the configuration you want to deploy works as intended. To validate your application configuration data, you provide a schema or a Lambda function that runs against the configuration. The configuration deployment or update can only proceed when the configuration data is valid. During a configuration deployment, AppConfig monitors the application to ensure that the deployment is successful. If the system encounters an error, AppConfig rolls back the change to minimize impact for your application users. You can configure a deployment strategy for each application or environment that includes deployment criteria, including velocity, bake time, and alarms to monitor. Similar to error monitoring, if a deployment triggers an alarm, AppConfig automatically rolls back to the previous version. AppConfig supports multiple use cases. Here are some examples. Application tuning : Use AppConfig to carefully introduce changes to your application that can only be tested with production traffic. Feature toggle : Use AppConfig to turn on new features that require a timely deployment, such as a product launch or announcement. Allow list : Use AppConfig to allow premium subscribers to access paid content. Operational issues : Use AppConfig to reduce stress on your application when a dependency or other external factor impacts the system. This reference is intended to be used with the AWS AppConfig User Guide.

Amazon Connect Contact Lens

Contact Lens for Amazon Connect enables you to analyze conversations between customer and agents, by using speech transcription, natural language processing, and intelligent search capabilities. It performs sentiment analysis, detects issues, and enables you to automatically categorize contacts. Contact Lens for Amazon Connect provides both real-time and post-call analytics of customer-agent conversations. For more information, see Analyze conversations using Contact Lens in the Amazon Connect Administrator Guide.

Amazon Elastic Kubernetes Service

Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on Amazon Web Services without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS runs up-to-date versions of the open-source Kubernetes software, so you can use all the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or public clouds. This means that you can easily migrate any standard Kubernetes application to Amazon EKS without any code modification required.

AWS EC2 Instance Connect

Amazon EC2 Instance Connect enables system administrators to publish one-time use SSH public keys to EC2, providing users a simple and secure way to connect to their instances.

AuthorizationManagementClient

azure.com
Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These operations enable you to manage role assignments. A role assignment grants access to Azure Active Directory users.

BatchManagement

azure.com

DataLakeAnalyticsCatalogManagementClient

azure.com
Creates an Azure Data Lake Analytics catalog client.

AmazonApiGatewayManagementApi

The Amazon API Gateway Management API allows you to directly manage runtime aspects of your deployed APIs. To use it, you must explicitly set the SDK's endpoint to point to the endpoint of your deployed API. The endpoint will be of the form https://{api-id}.execute-api.{region}.amazonaws.com/{stage}, or will be the endpoint corresponding to your API's custom domain and base path, if applicable.

Amazon SageMaker Service

Provides APIs for creating and managing Amazon SageMaker resources. Other Resources: Amazon SageMaker Developer Guide Amazon Augmented AI Runtime API Reference

Amazon QuickSight

Amazon QuickSight API Reference Amazon QuickSight is a fully managed, serverless business intelligence service for the Amazon Web Services Cloud that makes it easy to extend data and insights to every user in your organization. This API reference contains documentation for a programming interface that you can use to manage Amazon QuickSight.

SqlManagementClient

azure.com
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.