Mock sample for your project: SqlManagementClient API

Azure Maintenance Management Client

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These calls handle provider operations.

File share operation endpoints and objects.

Azure Application Insights client for saved items.

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

Alert operation endpoints and objects.

APIs for managing software update configurations.

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.

The OpenALPR CarCheck API allows you to send images to the cloud for processing.
The image will be analyzed for license plates and vehicle make/models. The results
are returned in JSON format

AWS Fault Injection Simulator is a managed service that enables you to perform fault injection experiments on your AWS workloads. For more information, see the AWS Fault Injection Simulator User Guide.

Contact Lens for Amazon Connect enables you to analyze conversations between customer and agents, by using speech transcription, natural language processing, and intelligent search capabilities. It performs sentiment analysis, detects issues, and enables you to automatically categorize contacts. Contact Lens for Amazon Connect provides both real-time and post-call analytics of customer-agent conversations. For more information, see Analyze conversations using Contact Lens in the Amazon Connect Administrator Guide.

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.

An AWS Elemental MediaStore asset is an object, similar to an object in the Amazon S3 service. Objects are the fundamental entities that are stored in AWS Elemental MediaStore.

API for AWS Elemental MediaConnect

The FinSpace management service provides the APIs for managing the FinSpace environments.

AWS Lake Formation Defines the public endpoint for the AWS Lake Formation service.

Detective uses machine learning and purpose-built visualizations to help you analyze and investigate security issues across your Amazon Web Services (AWS) workloads. Detective automatically extracts time-based events such as login attempts, API calls, and network traffic from AWS CloudTrail and Amazon Virtual Private Cloud (Amazon VPC) flow logs. It also extracts findings detected by Amazon GuardDuty. The Detective API primarily supports the creation and management of behavior graphs. A behavior graph contains the extracted data from a set of member accounts, and is created and managed by an administrator account. Every behavior graph is specific to a Region. You can only use the API to manage graphs that belong to the Region that is associated with the currently selected endpoint. A Detective administrator account can use the Detective API to do the following: Enable and disable Detective. Enabling Detective creates a new behavior graph. View the list of member accounts in a behavior graph. Add member accounts to a behavior graph. Remove member accounts from a behavior graph. A member account can use the Detective API to do the following: View the list of behavior graphs that they are invited to. Accept an invitation to contribute to a behavior graph. Decline an invitation to contribute to a behavior graph. Remove their account from a behavior graph. All API actions are logged as CloudTrail events. See Logging Detective API Calls with CloudTrail. We replaced the term "master account" with the term "administrator account." An administrator account is used to centrally manage multiple accounts. In the case of Detective, the administrator account manages the accounts in their behavior graph.

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.

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.