Mock sample for your project: iotHubClient API

Creates an Azure Data Lake Store filesystem client.

The APIs listed in this specification can be used to manage Deployment Scripts resource through the Azure Resource Manager.

These APIs allow end users to operate on Azure Machine Learning Workspace resources.

The Admin Infrastructure Insights Management Client.

REST APIs for orchestrating deployments using the Azure Deployment Manager (ADM). See https://docs.microsoft.com/en-us/azure/azure-resource-manager/deployment-manager-overview for more information.

The HDInsight Management Client.

Azure Digital Twins Client for managing DigitalTwinsInstance

Use these REST APIs for performing operations on Global Policies in Azure API Management deployment.

The HDInsight Management Client.

This Swagger was generated by the API Framework.

Service Map API Reference

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.

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.

Use these REST APIs to get the analytics reports associated with your Azure API Management deployment.

Azure Application Insights client for saved items.

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.

Identity and Access Management Access Analyzer helps identify potential resource-access risks by enabling you to identify any policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview and validate public and cross-account access to your resources before deploying permissions changes. This guide describes the Identity and Access Management Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide. To start using IAM Access Analyzer, you first need to create an analyzer.

Use these REST APIs for performing operations on Property 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 properties. Each API Management service instance has a properties collection of key/value pairs that are global to the service instance. These properties can be used to manage constant string values across all API configuration and policies.

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.

With Service Quotas, you can view and manage your quotas easily as your AWS workloads grow. Quotas, also referred to as limits, are the maximum number of resources that you can create in your AWS account. For more information, see the Service Quotas User Guide.

Use these REST APIs for performing operations on Group entity in your Azure API Management deployment. Groups are used to manage the visibility of products to developers. Each API Management service instance comes with the following immutable system groups whose membership is automatically managed by API Management. - Administrators - Azure subscription administrators are members of this group. - Developers - Authenticated developer portal users fall into this group. - Guests - Unauthenticated developer portal users are placed into this group. In addition to these system groups, administrators can create custom groups or leverage external groups in associated Azure Active Directory tenants. Custom and external groups can be used alongside system groups in giving developers visibility and access to API products. For example, you could create one custom group for developers affiliated with a specific partner organization and allow them access to the APIs from a product containing relevant APIs only. A user can be a member of more than one group.

Use these REST APIs for performing operations to retrieve Products by Tags in Azure API Management deployment.

Azure Application Insights client for work item configurations for a component.