Mock sample for your project: AzureDigitalTwinsManagementClient API

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

AzureDigitalTwinsManagementClient

azure.com

Version: 2020-03-01-preview


Use this API in your project

Speed up your application development by using "AzureDigitalTwinsManagementClient 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

Azure Digital Twins Client for managing DigitalTwinsInstance

Other APIs by azure.com

Security Center

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

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.

UpdateAdminClient

azure.com
Update location operation endpoints and objects.

Azure Machine Learning Datastore Management Client

azure.com

HanaManagementClient

azure.com
The SAP HANA on Azure Management Client.

SubscriptionsManagementClient

azure.com
The Admin Subscriptions Management Client.

AutomationManagement

azure.com

BillingManagementClient

azure.com
Billing client provides access to billing resources for Azure subscriptions.

FabricAdminClient

azure.com
Logical subnet operation endpoints and objects.

ComputeDiskAdminManagementClient

azure.com
The Admin Compute Disk Management Client.

DataLakeStoreFileSystemManagementClient

azure.com
Creates an Azure Data Lake Store filesystem client.

MonitorManagementClient

azure.com
Azure Monitor client to create/update/delete metric based alerts.

Other APIs in the same category

AWS Lambda

Lambda Overview This is the Lambda API Reference. The Lambda Developer Guide provides additional information. For the service overview, see What is Lambda, and for information about how the service works, see Lambda: How it Works in the Lambda Developer Guide.

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 definitions and role assignments. A role definition describes the set of actions that can be performed on resources. A role assignment grants access to Azure Active Directory users.

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.

ConsumptionManagementClient

azure.com
Consumption management client provides access to consumption resources for Azure Enterprise Subscriptions.

ApiManagementClient

azure.com
Use these REST APIs for performing operations on Cache entity in your Azure API Management deployment. Azure API Management also allows for caching responses in an external Azure Cache for Redis. For more information refer to External Redis Cache in ApiManagement.

Amazon Prometheus Service

Amazon Managed Service for Prometheus

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.

ApiManagementClient

azure.com
Use these REST APIs for performing operations on entities like API, Product, and Subscription associated with your Azure API Management deployment.

Amazon Cognito Sync

Amazon Cognito Sync Amazon Cognito Sync provides an AWS service and client library that enable cross-device syncing of application-related user data. High-level client libraries are available for both iOS and Android. You can use these libraries to persist data locally so that it's available even if the device is offline. Developer credentials don't need to be stored on the mobile device to access the service. You can use Amazon Cognito to obtain a normalized user ID and credentials. User data is persisted in a dataset that can store up to 1 MB of key-value pairs, and you can have up to 20 datasets per user identity. With Amazon Cognito Sync, the data stored for each identity is accessible only to credentials assigned to that identity. In order to use the Cognito Sync service, you need to make API calls using credentials retrieved with Amazon Cognito Identity service. If you want to use Cognito Sync in an Android or iOS application, you will probably want to make API calls via the AWS Mobile SDK. To learn more, see the Developer Guide for Android and the Developer Guide for iOS.

Application Auto Scaling

With Application Auto Scaling, you can configure automatic scaling for the following resources: Amazon AppStream 2.0 fleets Amazon Aurora Replicas Amazon Comprehend document classification and entity recognizer endpoints Amazon DynamoDB tables and global secondary indexes throughput capacity Amazon ECS services Amazon ElastiCache for Redis clusters (replication groups) Amazon EMR clusters Amazon Keyspaces (for Apache Cassandra) tables Lambda function provisioned concurrency Amazon Managed Streaming for Apache Kafka broker storage Amazon SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services API Summary The Application Auto Scaling service API includes three key sets of actions: Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets. Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history. Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

UpdateAdminClient

azure.com
Update run operation endpoints and objects.

BatchAI

azure.com
The Azure BatchAI Management API.