Mock sample for your project: Engagement.ManagementClient API

Virtual Network admin operation endpoints and objects.

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.

Use these REST APIs for performing operations on logger entity Azure API Management deployment.The Logger entity in API Management represents an event sink that you can use to log API Management events. Currently the Logger entity supports logging API Management events to Azure EventHub.

These APIs allow end users to manage Azure Machine Learning Models, Images, Profiles, and Services.

The Container Service Client.

The Azure BatchAI Management API.

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.

This Swagger was generated by the API Framework.

Billing client provides access to billing resources for Azure subscriptions.

The Container Service Client.

APIs to manage web application firewall rules.

Systems Manager Incident Manager is an incident management console designed to help users mitigate and recover from incidents affecting their Amazon Web Services-hosted applications. An incident is any unplanned interruption or reduction in quality of services. Incident Manager increases incident resolution by notifying responders of impact, highlighting relevant troubleshooting data, and providing collaboration tools to get services back up and running. To achieve the primary goal of reducing the time-to-resolution of critical incidents, Incident Manager automates response plans and enables responder team escalation.

Amazon Redshift Overview This is an interface reference for Amazon Redshift. It contains documentation for one of the programming or command line interfaces you can use to manage Amazon Redshift clusters. Note that Amazon Redshift is asynchronous, which means that some interfaces may require techniques, such as polling or asynchronous callback handlers, to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a change is applied immediately, on the next instance reboot, or during the next maintenance window. For a summary of the Amazon Redshift cluster management interfaces, go to Using the Amazon Redshift Management Interfaces. Amazon Redshift manages all the work of setting up, operating, and scaling a data warehouse: provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine. You can focus on using your data to acquire new insights for your business and customers. If you are a first-time user of Amazon Redshift, we recommend that you begin by reading the Amazon Redshift Getting Started Guide. If you are a database developer, the Amazon Redshift Database Developer Guide explains how to design, build, query, and maintain the databases that make up your data warehouse.

The WorkDocs API is designed for the following use cases: File Migration: File migration applications are supported for users who want to migrate their files from an on-premises or off-premises file system or service. Users can insert files into a user directory structure, as well as allow for basic metadata changes, such as modifications to the permissions of files. Security: Support security applications are supported for users who have additional security needs, such as antivirus or data loss prevention. The API actions, along with AWS CloudTrail, allow these applications to detect when changes occur in Amazon WorkDocs. Then, the application can take the necessary actions and replace the target file. If the target file violates the policy, the application can also choose to email the user. eDiscovery/Analytics: General administrative applications are supported, such as eDiscovery and analytics. These applications can choose to mimic or record the actions in an Amazon WorkDocs site, along with AWS CloudTrail, to replicate data for eDiscovery, backup, or analytical applications. All Amazon WorkDocs API actions are Amazon authenticated and certificate-signed. They not only require the use of the AWS SDK, but also allow for the exclusive use of IAM users and roles to help facilitate access, trust, and permission policies. By creating a role and allowing an IAM user to access the Amazon WorkDocs site, the IAM user gains full administrative visibility into the entire Amazon WorkDocs site (or as set in the IAM policy). This includes, but is not limited to, the ability to modify file permissions and upload any file to any user. This allows developers to perform the three use cases above, as well as give users the ability to grant access on a selective basis using the IAM model.

Suite of geospatial services including Maps, Places, Routes, Tracking, and Geofencing

The Admin Subscriptions Management Client.

Network operation results.

Amazon Neptune Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. This interface reference for Amazon Neptune contains documentation for a programming or command line interface you can use to manage Amazon Neptune. Note that Amazon Neptune is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide.

Amazon RDS Performance Insights Amazon RDS Performance Insights enables you to monitor and explore different dimensions of database load based on data captured from a running DB instance. The guide provides detailed information about Performance Insights data types, parameters and errors. When Performance Insights is enabled, the Amazon RDS Performance Insights API provides visibility into the performance of your DB instance. Amazon CloudWatch provides the authoritative source for AWS service-vended monitoring metrics. Performance Insights offers a domain-specific view of DB load. DB load is measured as Average Active Sessions. Performance Insights provides the data to API consumers as a two-dimensional time-series dataset. The time dimension provides DB load data for each time point in the queried time range. Each time point decomposes overall load in relation to the requested dimensions, measured at that time point. Examples include SQL, Wait event, User, and Host. To learn more about Performance Insights and Amazon Aurora DB instances, go to the Amazon Aurora User Guide. To learn more about Performance Insights and Amazon RDS DB instances, go to the Amazon RDS User Guide.