Mock sample for your project: Amazon Neptune API

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.

AWS Marketplace Metering Service This reference provides descriptions of the low-level AWS Marketplace Metering Service API. AWS Marketplace sellers can use this API to submit usage data for custom usage dimensions. For information on the permissions you need to use this API, see AWS Marketing metering and entitlement API permissions in the AWS Marketplace Seller Guide. Submitting Metering Records MeterUsage - Submits the metering record for a Marketplace product. MeterUsage is called from an EC2 instance or a container running on EKS or ECS. BatchMeterUsage - Submits the metering record for a set of customers. BatchMeterUsage is called from a software-as-a-service (SaaS) application. Accepting New Customers ResolveCustomer - Called by a SaaS application during the registration process. When a buyer visits your website during the registration process, the buyer submits a Registration Token through the browser. The Registration Token is resolved through this API to obtain a CustomerIdentifier and Product Code. Entitlement and Metering for Paid Container Products Paid container software products sold through AWS Marketplace must integrate with the AWS Marketplace Metering Service and call the RegisterUsage operation for software entitlement and metering. Free and BYOL products for Amazon ECS or Amazon EKS aren't required to call RegisterUsage, but you can do so if you want to receive usage data in your seller reports. For more information on using the RegisterUsage operation, see Container-Based Products. BatchMeterUsage API calls are captured by AWS CloudTrail. You can use Cloudtrail to verify that the SaaS metering records that you sent are accurate by searching for records with the eventName of BatchMeterUsage. You can also use CloudTrail to audit records over time. For more information, see the AWS CloudTrail User Guide .

Amazon Lex Build-Time Actions Amazon Lex is an AWS service for building conversational voice and text interfaces. Use these actions to create, update, and delete conversational bots for new and existing client applications.

Amazon Relational Database Service Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, resizeable capacity for an industry-standard relational database and manages common database administration tasks, freeing up developers to focus on what makes their applications and businesses unique. Amazon RDS gives you access to the capabilities of a MySQL, MariaDB, PostgreSQL, Microsoft SQL Server, Oracle, or Amazon Aurora database server. These capabilities mean that the code, applications, and tools you already use today with your existing databases work with Amazon RDS without modification. Amazon RDS automatically backs up your database and maintains the database software that powers your DB instance. Amazon RDS is flexible: you can scale your DB instance's compute resources and storage capacity to meet your application's demand. As with all Amazon Web Services, there are no up-front investments, and you pay only for the resources you use. This interface reference for Amazon RDS contains documentation for a programming or command line interface you can use to manage Amazon RDS. Amazon RDS 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 API Reference For the alphabetical list of API actions, see API Actions. For the alphabetical list of data types, see Data Types. For a list of common query parameters, see Common Parameters. For descriptions of the error codes, see Common Errors. Amazon RDS User Guide For a summary of the Amazon RDS interfaces, see Available RDS Interfaces. For more information about how to use the Query API, see Using the Query API.

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

Amazon Kinesis Data Streams Service API Reference Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.

Provides APIs for creating and managing Amazon Forecast resources.

This is the Firewall Manager API Reference. This guide is for developers who need detailed information about the Firewall Manager API actions, data types, and errors. For detailed information about Firewall Manager features, see the Firewall Manager Developer Guide. Some API actions require explicit resource permissions. For information, see the developer guide topic Firewall Manager required permissions for API actions.

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

AWS Mobile Service provides mobile app and website developers with capabilities required to configure AWS resources and bootstrap their developer desktop projects with the necessary SDKs, constants, tools and samples to make use of those resources.

Direct Connect links your internal network to an Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an Direct Connect router. With this connection in place, you can create virtual interfaces directly to the Cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all Regions except the China (Beijing) and (China) Ningxia Regions. Amazon Web Services resources in the China Regions can only be accessed through locations associated with those Regions.

Amazon Lightsail is the easiest way to get started with Amazon Web Services (AWS) for developers who need to build websites or web applications. It includes everything you need to launch your project quickly - instances (virtual private servers), container services, storage buckets, managed databases, SSD-based block storage, static IP addresses, load balancers, content delivery network (CDN) distributions, DNS management of registered domains, and resource snapshots (backups) - for a low, predictable monthly price. You can manage your Lightsail resources using the Lightsail console, Lightsail API, AWS Command Line Interface (AWS CLI), or SDKs. For more information about Lightsail concepts and tasks, see the Amazon Lightsail Developer Guide. This API Reference provides detailed information about the actions, data types, parameters, and errors of the Lightsail service. For more information about the supported AWS Regions, endpoints, and service quotas of the Lightsail service, see Amazon Lightsail Endpoints and Quotas in the AWS General Reference.

These APIs allow end users to operate on Azure Machine Learning Workspace resources.

AWS IoT Wireless API documentation

AWS IoT Greengrass seamlessly extends AWS onto physical devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. AWS IoT Greengrass ensures your devices can respond quickly to local events and operate with intermittent connectivity. AWS IoT Greengrass minimizes the cost of transmitting data to the cloud by allowing you to author AWS Lambda functions that execute locally.

AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data. AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management. AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.

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.

Amazon Kinesis Data Firehose API Reference Amazon Kinesis Data Firehose is a fully managed service that delivers real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Elasticsearch Service (Amazon ES), Amazon Redshift, and Splunk.

Amazon Simple Workflow Service The Amazon Simple Workflow Service (Amazon SWF) makes it easy to build applications that use Amazon's cloud to coordinate work across distributed components. In Amazon SWF, a task represents a logical unit of work that is performed by a component of your workflow. Coordinating tasks in a workflow involves managing intertask dependencies, scheduling, and concurrency in accordance with the logical flow of the application. Amazon SWF gives you full control over implementing tasks and coordinating them without worrying about underlying complexities such as tracking their progress and maintaining their state. This documentation serves as reference only. For a broader overview of the Amazon SWF programming model, see the Amazon SWF Developer Guide .

Azure Application Insights client for Continuous Export of a component.

DataSync DataSync is a managed data transfer service that makes it simpler for you to automate moving data between on-premises storage and Amazon Simple Storage Service (Amazon S3) or Amazon Elastic File System (Amazon EFS). This API interface reference for DataSync contains documentation for a programming interface that you can use to manage DataSync.

AWS Global Accelerator This is the AWS Global Accelerator API Reference. This guide is for developers who need detailed information about AWS Global Accelerator API actions, data types, and errors. For more information about Global Accelerator features, see the AWS Global Accelerator Developer Guide. AWS Global Accelerator is a service in which you create accelerators to improve the performance of your applications for local and global users. Depending on the type of accelerator you choose, you can gain additional benefits. By using a standard accelerator, you can improve availability of your internet applications that are used by a global audience. With a standard accelerator, Global Accelerator directs traffic to optimal endpoints over the AWS global network. For other scenarios, you might choose a custom routing accelerator. With a custom routing accelerator, you can use application logic to directly map one or more users to a specific endpoint among many endpoints. Global Accelerator is a global service that supports endpoints in multiple AWS Regions but you must specify the US West (Oregon) Region to create or update accelerators. By default, Global Accelerator provides you with two static IP addresses that you associate with your accelerator. With a standard accelerator, instead of using the IP addresses that Global Accelerator provides, you can configure these entry points to be IPv4 addresses from your own IP address ranges that you bring to Global Accelerator. The static IP addresses are anycast from the AWS edge network. For a standard accelerator, they distribute incoming application traffic across multiple endpoint resources in multiple AWS Regions, which increases the availability of your applications. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses that are located in one AWS Region or multiple Regions. For custom routing accelerators, you map traffic that arrives to the static IP addresses to specific Amazon EC2 servers in endpoints that are virtual private cloud (VPC) subnets. The static IP addresses remain assigned to your accelerator for as long as it exists, even if you disable the accelerator and it no longer accepts or routes traffic. However, when you delete an accelerator, you lose the static IP addresses that are assigned to it, so you can no longer route traffic by using them. You can use IAM policies like tag-based permissions with Global Accelerator to limit the users who have permissions to delete an accelerator. For more information, see Tag-based policies. For standard accelerators, Global Accelerator uses the AWS global network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure. The service reacts instantly to changes in health or configuration to ensure that internet traffic from clients is always directed to healthy endpoints. For a list of the AWS Regions where Global Accelerator and other services are currently supported, see the AWS Region Table. AWS Global Accelerator includes the following components: Static IP addresses Global Accelerator provides you with a set of two static IP addresses that are anycast from the AWS edge network. If you bring your own IP address range to AWS (BYOIP) to use with a standard accelerator, you can instead assign IP addresses from your own pool to use with your accelerator. For more information, see Bring your own IP addresses (BYOIP) in AWS Global Accelerator. The IP addresses serve as single fixed entry points for your clients. If you already have Elastic Load Balancing load balancers, Amazon EC2 instances, or Elastic IP address resources set up for your applications, you can easily add those to a standard accelerator in Global Accelerator. This allows Global Accelerator to use static IP addresses to access the resources. The static IP addresses remain assigned to your accelerator for as long as it exists, even if you disable the accelerator and it no longer accepts or routes traffic. However, when you delete an accelerator, you lose the static IP addresses that are assigned to it, so you can no longer route traffic by using them. You can use IAM policies like tag-based permissions with Global Accelerator to delete an accelerator. For more information, see Tag-based policies. Accelerator An accelerator directs traffic to endpoints over the AWS global network to improve the performance of your internet applications. Each accelerator includes one or more listeners. There are two types of accelerators: A standard accelerator directs traffic to the optimal AWS endpoint based on several factors, including the user’s location, the health of the endpoint, and the endpoint weights that you configure. This improves the availability and performance of your applications. Endpoints can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses. A custom routing accelerator directs traffic to one of possibly thousands of Amazon EC2 instances running in a single or multiple virtual private clouds (VPCs). With custom routing, listener ports are mapped to statically associate port ranges with VPC subnets, which allows Global Accelerator to determine an EC2 instance IP address at the time of connection. By default, all port mapping destinations in a VPC subnet can't receive traffic. You can choose to configure all destinations in the subnet to receive traffic, or to specify individual port mappings that can receive traffic. For more information, see Types of accelerators. DNS name Global Accelerator assigns each accelerator a default Domain Name System (DNS) name, similar to a1234567890abcdef.awsglobalaccelerator.com, that points to the static IP addresses that Global Accelerator assigns to you or that you choose from your own IP address range. Depending on the use case, you can use your accelerator's static IP addresses or DNS name to route traffic to your accelerator, or set up DNS records to route traffic using your own custom domain name. Network zone A network zone services the static IP addresses for your accelerator from a unique IP subnet. Similar to an AWS Availability Zone, a network zone is an isolated unit with its own set of physical infrastructure. When you configure an accelerator, by default, Global Accelerator allocates two IPv4 addresses for it. If one IP address from a network zone becomes unavailable due to IP address blocking by certain client networks, or network disruptions, then client applications can retry on the healthy static IP address from the other isolated network zone. Listener A listener processes inbound connections from clients to Global Accelerator, based on the port (or port range) and protocol (or protocols) that you configure. A listener can be configured for TCP, UDP, or both TCP and UDP protocols. Each listener has one or more endpoint groups associated with it, and traffic is forwarded to endpoints in one of the groups. You associate endpoint groups with listeners by specifying the Regions that you want to distribute traffic to. With a standard accelerator, traffic is distributed to optimal endpoints within the endpoint groups associated with a listener. Endpoint group Each endpoint group is associated with a specific AWS Region. Endpoint groups include one or more endpoints in the Region. With a standard accelerator, you can increase or reduce the percentage of traffic that would be otherwise directed to an endpoint group by adjusting a setting called a traffic dial. The traffic dial lets you easily do performance testing or blue/green deployment testing, for example, for new releases across different AWS Regions. Endpoint An endpoint is a resource that Global Accelerator directs traffic to. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses. An Application Load Balancer endpoint can be internet-facing or internal. Traffic for standard accelerators is routed to endpoints based on the health of the endpoint along with configuration options that you choose, such as endpoint weights. For each endpoint, you can configure weights, which are numbers that you can use to specify the proportion of traffic to route to each one. This can be useful, for example, to do performance testing within a Region. Endpoints for custom routing accelerators are virtual private cloud (VPC) subnets with one or many EC2 instances.