Mock sample for your project: Security Center API

The Azure Management Groups API enables consolidation of multiple
subscriptions/resources into an organizational hierarchy and centrally
manage access control, policies, alerting and reporting for those resources.

Mixed Reality Resource Provider REST API

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

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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, encryption keys, active directory administrator and configurations.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

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.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

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

REST API for Azure VirtualWAN As a Service.

The Admin Subscriptions Management Client.

Service Map API Reference

The Admin Subscriptions Management Client.

Amazon Inspector Amazon Inspector enables you to analyze the behavior of your AWS resources and to identify potential security issues. For more information, see Amazon Inspector User Guide.

Azure Application Insights workbook template type.

Amazon Managed Workflows for Apache Airflow This section contains the Amazon Managed Workflows for Apache Airflow (MWAA) API reference documentation. For more information, see What Is Amazon MWAA?.

The Amazon Chime SDK Messaging APIs in this section allow software developers to send and receive messages in custom messaging applications. These APIs depend on the frameworks provided by the Amazon Chime SDK Identity APIs. For more information about the messaging APIs, see Amazon Chime SDK messaging

Logical network operation endpoints and objects.

Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS. Macie automates the discovery of sensitive data, such as PII and intellectual property, to provide you with insight into the data that your organization stores in AWS. Macie also provides an inventory of your Amazon S3 buckets, which it continually monitors for you. If Macie detects sensitive data or potential data access issues, it generates detailed findings for you to review and act upon as necessary.

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.