Mock sample for your project: Azure DevOps API

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.

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.

Storage operation results.

Mixed Reality Resource Provider Remote Rendering Resource API

Azure Log Analytics API reference

Azure Feature Exposure Control (AFEC) provides a mechanism for the resource providers to control feature exposure to users. Resource providers typically use this mechanism to provide public/private preview for new features prior to making them generally available. Users need to explicitly register for AFEC features to get access to such functionality.

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

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.

Provides read functionality for Azure SQL Database Backups

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.

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 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 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.

The AAD Domain Services API.

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS. Amazon EMR containers is the API name for Amazon EMR on EKS. The emr-containers prefix is used in the following scenarios: It is the prefix in the CLI commands for Amazon EMR on EKS. For example, aws emr-containers start-job-run. It is the prefix before IAM policy actions for Amazon EMR on EKS. For example,"Action": [ "emr-containers:StartJobRun"]. For more information, see Policy actions for Amazon EMR on EKS. It is the prefix used in Amazon EMR on EKS service endpoints. For example, emr-containers.us-east-2.amazonaws.com. For more information, see Amazon EMR on EKS Service Endpoints.

Deployment Admin Client.

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.

Describes the interface for the per-tenant enclave service.

CloudTrail This is the CloudTrail API Reference. It provides descriptions of actions, data types, common parameters, and common errors for CloudTrail. CloudTrail is a web service that records Amazon Web Services API calls for your Amazon Web Services account and delivers log files to an Amazon S3 bucket. The recorded information includes the identity of the user, the start time of the Amazon Web Services API call, the source IP address, the request parameters, and the response elements returned by the service. As an alternative to the API, you can use one of the Amazon Web Services SDKs, which consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .NET, iOS, Android, etc.). The SDKs provide programmatic access to CloudTrail. For example, the SDKs handle cryptographically signing requests, managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools to Build on Amazon Web Services. See the CloudTrail User Guide for information about the data that is included with each Amazon Web Services API call listed in the log files.

Use these REST APIs for performing retrieving a collection of policy snippets available in Azure API Management deployment.

Use the Control API to manage your applications, namespaces, keys, queues, rules, and more.
Detailed information on using this API can be found in the Ably developer documentation.
Control API is currently in Beta.