Mock sample for your project: Azure SQL Database disaster recovery configurations API

Cognitive Services Management Client

Deployment Admin Client.

The Container Service Client.

The Text Analytics API is a suite of text analytics web services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. No training data is needed to use this API; just bring your text data. This API uses advanced natural language processing techniques to deliver best in class predictions. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

The Admin Commerce Management Client.

The Admin Gallery Management Client.

APIs for managing software update configurations.

The Container Service Client.

The Container Service Client.

The Admin Subscriptions Management Client.

AWS Organizations is a web service that enables you to consolidate your multiple AWS accounts into an organization and centrally manage your accounts and their resources. This guide provides descriptions of the Organizations operations. For more information about using this service, see the AWS Organizations User Guide. Support and feedback for AWS Organizations We welcome your feedback. Send your comments to [email protected] or post your feedback and questions in the AWS Organizations support forum. For more information about the AWS support forums, see Forums Help. Endpoint to call When using the AWS CLI or the AWS SDK For the current release of Organizations, specify the us-east-1 region for all AWS API and AWS CLI calls made from the commercial AWS Regions outside of China. If calling from one of the AWS Regions in China, then specify cn-northwest-1. You can do this in the AWS CLI by using these parameters and commands: Use the following parameter with each command to specify both the endpoint and its region: --endpoint-url https://organizations.us-east-1.amazonaws.com (from commercial AWS Regions outside of China) or --endpoint-url https://organizations.cn-northwest-1.amazonaws.com.cn (from AWS Regions in China) Use the default endpoint, but configure your default region with this command: aws configure set default.region us-east-1 (from commercial AWS Regions outside of China) or aws configure set default.region cn-northwest-1 (from AWS Regions in China) Use the following parameter with each command to specify the endpoint: --region us-east-1 (from commercial AWS Regions outside of China) or --region cn-northwest-1 (from AWS Regions in China) Recording API Requests AWS Organizations supports AWS CloudTrail, a service that records AWS API calls for your AWS account and delivers log files to an Amazon S3 bucket. By using information collected by AWS CloudTrail, you can determine which requests the Organizations service received, who made the request and when, and so on. For more about AWS Organizations and its support for AWS CloudTrail, see Logging AWS Organizations Events with AWS CloudTrail in the AWS Organizations User Guide. To learn more about AWS CloudTrail, including how to turn it on and find your log files, see the AWS CloudTrail User Guide.

The AWS IoT 1-Click Projects API Reference

Elastic Load Balancing A load balancer distributes incoming traffic across targets, such as your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered targets and ensures that it routes traffic only to healthy targets. You configure your load balancer to accept incoming traffic by specifying one or more listeners, which are configured with a protocol and port number for connections from clients to the load balancer. You configure a target group with a protocol and port number for connections from the load balancer to the targets, and with health check settings to be used when checking the health status of the targets. Elastic Load Balancing supports the following types of load balancers: Application Load Balancers, Network Load Balancers, Gateway Load Balancers, and Classic Load Balancers. This reference covers the following load balancer types: Application Load Balancer - Operates at the application layer (layer 7) and supports HTTP and HTTPS. Network Load Balancer - Operates at the transport layer (layer 4) and supports TCP, TLS, and UDP. Gateway Load Balancer - Operates at the network layer (layer 3). For more information, see the Elastic Load Balancing User Guide. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds.

IoT data IoT data enables secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. It implements a broker for applications and things to publish messages over HTTP (Publish) and retrieve, update, and delete shadows. A shadow is a persistent representation of your things and their state in the Amazon Web Services cloud. Find the endpoint address for actions in IoT data by running this CLI command: aws iot describe-endpoint --endpoint-type iot:Data-ATS The service name used by Amazon Web ServicesSignature Version 4 to sign requests is: iotdevicegateway.

AWS Resource Groups AWS Resource Groups lets you organize AWS resources such as Amazon EC2 instances, Amazon Relational Database Service databases, and Amazon S3 buckets into groups using criteria that you define as tags. A resource group is a collection of resources that match the resource types specified in a query, and share one or more tags or portions of tags. You can create a group of resources based on their roles in your cloud infrastructure, lifecycle stages, regions, application layers, or virtually any criteria. Resource Groups enable you to automate management tasks, such as those in AWS Systems Manager Automation documents, on tag-related resources in AWS Systems Manager. Groups of tagged resources also let you quickly view a custom console in AWS Systems Manager that shows AWS Config compliance and other monitoring data about member resources. To create a resource group, build a resource query, and specify tags that identify the criteria that members of the group have in common. Tags are key-value pairs. For more information about Resource Groups, see the AWS Resource Groups User Guide. AWS Resource Groups uses a REST-compliant API that you can use to perform the following types of operations. Create, Read, Update, and Delete (CRUD) operations on resource groups and resource query entities Applying, editing, and removing tags from resource groups Resolving resource group member ARNs so they can be returned as search results Getting data about resources that are members of a group Searching AWS resources based on a resource query

Elastic Inference public APIs.

AWS Elastic Transcoder Service The AWS Elastic Transcoder Service.

Amazon Elasticsearch Configuration Service Use the Amazon Elasticsearch Configuration API to create, configure, and manage Elasticsearch domains. For sample code that uses the Configuration API, see the Amazon Elasticsearch Service Developer Guide. The guide also contains sample code for sending signed HTTP requests to the Elasticsearch APIs. The endpoint for configuration service requests is region-specific: es. region.amazonaws.com. For example, es.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints.

Amazon Connect is a cloud-based contact center solution that makes it easy to set up and manage a customer contact center and provide reliable customer engagement at any scale. Amazon Connect enables customer contacts through voice or chat. The APIs described here are used by chat participants, such as agents and customers.

Amazon GuardDuty is a continuous security monitoring service that analyzes and processes the following data sources: VPC Flow Logs, AWS CloudTrail event logs, and DNS logs. It uses threat intelligence feeds (such as lists of malicious IPs and domains) and machine learning to identify unexpected, potentially unauthorized, and malicious activity within your AWS environment. This can include issues like escalations of privileges, uses of exposed credentials, or communication with malicious IPs, URLs, or domains. For example, GuardDuty can detect compromised EC2 instances that serve malware or mine bitcoin. GuardDuty also monitors AWS account access behavior for signs of compromise. Some examples of this are unauthorized infrastructure deployments such as EC2 instances deployed in a Region that has never been used, or unusual API calls like a password policy change to reduce password strength. GuardDuty informs you of the status of your AWS environment by producing security findings that you can view in the GuardDuty console or through Amazon CloudWatch events. For more information, see the Amazon GuardDuty User Guide .

Amazon Managed Blockchain is a fully managed service for creating and managing blockchain networks using open-source frameworks. Blockchain allows you to build applications where multiple parties can securely and transparently run transactions and share data without the need for a trusted, central authority. Managed Blockchain supports the Hyperledger Fabric and Ethereum open-source frameworks. Because of fundamental differences between the frameworks, some API actions or data types may only apply in the context of one framework and not the other. For example, actions related to Hyperledger Fabric network members such as CreateMember and DeleteMember do not apply to Ethereum. The description for each action indicates the framework or frameworks to which it applies. Data types and properties that apply only in the context of a particular framework are similarly indicated.

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.