Mock sample for your project: Amazon Neptune API

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Amazon Neptune

amazonaws.com

Version: 2014-10-31


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Description

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.

Other APIs by amazonaws.com

AWS Direct Connect

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 Elastic Kubernetes Service

Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on Amazon Web Services without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS runs up-to-date versions of the open-source Kubernetes software, so you can use all the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or public clouds. This means that you can easily migrate any standard Kubernetes application to Amazon EKS without any code modification required.

Amazon Simple Email Service

Amazon Simple Email Service This document contains reference information for the Amazon Simple Email Service (Amazon SES) API, version 2010-12-01. This document is best used in conjunction with the Amazon SES Developer Guide. For a list of Amazon SES endpoints to use in service requests, see Regions and Amazon SES in the Amazon SES Developer Guide.

Amazon CloudWatch

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.

Managed Streaming for Kafka

The operations for managing an Amazon MSK cluster.

AWS Global Accelerator

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.

Amazon Timestream Write

Amazon Timestream is a fast, scalable, fully managed time series database service that makes it easy to store and analyze trillions of time series data points per day. With Timestream, you can easily store and analyze IoT sensor data to derive insights from your IoT applications. You can analyze industrial telemetry to streamline equipment management and maintenance. You can also store and analyze log data and metrics to improve the performance and availability of your applications. Timestream is built from the ground up to effectively ingest, process, and store time series data. It organizes data to optimize query processing. It automatically scales based on the volume of data ingested and on the query volume to ensure you receive optimal performance while inserting and querying data. As your data grows over time, Timestream’s adaptive query processing engine spans across storage tiers to provide fast analysis while reducing costs.

Amazon Glacier

Amazon S3 Glacier (Glacier) is a storage solution for "cold data." Glacier is an extremely low-cost storage service that provides secure, durable, and easy-to-use storage for data backup and archival. With Glacier, customers can store their data cost effectively for months, years, or decades. Glacier also enables customers to offload the administrative burdens of operating and scaling storage to AWS, so they don't have to worry about capacity planning, hardware provisioning, data replication, hardware failure and recovery, or time-consuming hardware migrations. Glacier is a great storage choice when low storage cost is paramount and your data is rarely retrieved. If your application requires fast or frequent access to your data, consider using Amazon S3. For more information, see Amazon Simple Storage Service (Amazon S3). You can store any kind of data in any format. There is no maximum limit on the total amount of data you can store in Glacier. If you are a first-time user of Glacier, we recommend that you begin by reading the following sections in the Amazon S3 Glacier Developer Guide : What is Amazon S3 Glacier - This section of the Developer Guide describes the underlying data model, the operations it supports, and the AWS SDKs that you can use to interact with the service. Getting Started with Amazon S3 Glacier - The Getting Started section walks you through the process of creating a vault, uploading archives, creating jobs to download archives, retrieving the job output, and deleting archives.

AWS Auto Scaling Plans

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.
IoT IoT provides secure, bi-directional communication between Internet-connected devices (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. You can discover your custom IoT-Data endpoint to communicate with, configure rules for data processing and integration with other services, organize resources associated with each device (Registry), configure logging, and create and manage policies and credentials to authenticate devices. The service endpoints that expose this API are listed in Amazon Web Services IoT Core Endpoints and Quotas. You must use the endpoint for the region that has the resources you want to access. The service name used by Amazon Web Services Signature Version 4 to sign the request is: execute-api. For more information about how IoT works, see the Developer Guide. For information about how to use the credentials provider for IoT, see Authorizing Direct Calls to Amazon Web Services Services.

Amazon AppStream

Amazon AppStream 2.0 This is the Amazon AppStream 2.0 API Reference. This documentation provides descriptions and syntax for each of the actions and data types in AppStream 2.0. AppStream 2.0 is a fully managed, secure application streaming service that lets you stream desktop applications to users without rewriting applications. AppStream 2.0 manages the AWS resources that are required to host and run your applications, scales automatically, and provides access to your users on demand. You can call the AppStream 2.0 API operations by using an interface VPC endpoint (interface endpoint). For more information, see Access AppStream 2.0 API Operations and CLI Commands Through an Interface VPC Endpoint in the Amazon AppStream 2.0 Administration Guide. To learn more about AppStream 2.0, see the following resources: Amazon AppStream 2.0 product page Amazon AppStream 2.0 documentation

AWS IoT Wireless

AWS IoT Wireless API documentation

Other APIs in the same category

FeatureClient

azure.com
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.

AWS Certificate Manager

Amazon Web Services Certificate Manager You can use Amazon Web Services Certificate Manager (ACM) to manage SSL/TLS certificates for your Amazon Web Services-based websites and applications. For more information about using ACM, see the Amazon Web Services Certificate Manager User Guide.

AWS Key Management Service

Key Management Service Key Management Service (KMS) is an encryption and key management web service. This guide describes the KMS operations that you can call programmatically. For general information about KMS, see the Key Management Service Developer Guide . KMS is replacing the term customer master key (CMK) with KMS key and KMS key. The concept has not changed. To prevent breaking changes, KMS is keeping some variations of this term. Amazon Web Services provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, macOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to KMS and other Amazon Web Services services. For example, the SDKs take care of tasks such as signing requests (see below), managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools for Amazon Web Services. We recommend that you use the Amazon Web Services SDKs to make programmatic API calls to KMS. Clients must support TLS (Transport Layer Security) 1.0. We recommend TLS 1.2. Clients must also support cipher suites with Perfect Forward Secrecy (PFS) such as Ephemeral Diffie-Hellman (DHE) or Elliptic Curve Ephemeral Diffie-Hellman (ECDHE). Most modern systems such as Java 7 and later support these modes. Signing Requests Requests must be signed by using an access key ID and a secret access key. We strongly recommend that you do not use your Amazon Web Services account (root) access key ID and secret key for everyday work with KMS. Instead, use the access key ID and secret access key for an IAM user. You can also use the Amazon Web Services Security Token Service to generate temporary security credentials that you can use to sign requests. All KMS operations require Signature Version 4. Logging API Requests KMS supports CloudTrail, a service that logs Amazon Web Services API calls and related events for your Amazon Web Services account and delivers them to an Amazon S3 bucket that you specify. By using the information collected by CloudTrail, you can determine what requests were made to KMS, who made the request, when it was made, and so on. To learn more about CloudTrail, including how to turn it on and find your log files, see the CloudTrail User Guide. Additional Resources For more information about credentials and request signing, see the following: Amazon Web Services Security Credentials - This topic provides general information about the types of credentials used to access Amazon Web Services. Temporary Security Credentials - This section of the IAM User Guide describes how to create and use temporary security credentials. Signature Version 4 Signing Process - This set of topics walks you through the process of signing a request using an access key ID and a secret access key. Commonly Used API Operations Of the API operations discussed in this guide, the following will prove the most useful for most applications. You will likely perform operations other than these, such as creating keys and assigning policies, by using the console. Encrypt Decrypt GenerateDataKey GenerateDataKeyWithoutPlaintext

AWSServerlessApplicationRepository

The AWS Serverless Application Repository makes it easy for developers and enterprises to quickly find
and deploy serverless applications in the AWS Cloud. For more information about serverless applications,
see Serverless Computing and Applications on the AWS website. The AWS Serverless Application Repository is deeply integrated with the AWS Lambda console, so that developers of
all levels can get started with serverless computing without needing to learn anything new. You can use category
keywords to browse for applications such as web and mobile backends, data processing applications, or chatbots.
You can also search for applications by name, publisher, or event source. To use an application, you simply choose it,
configure any required fields, and deploy it with a few clicks. You can also easily publish applications, sharing them publicly with the community at large, or privately
within your team or across your organization. To publish a serverless application (or app), you can use the
AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs to upload the code. Along with the
code, you upload a simple manifest file, also known as the AWS Serverless Application Model (AWS SAM) template.
For more information about AWS SAM, see AWS Serverless Application Model (AWS SAM) on the AWS Labs
GitHub repository. The AWS Serverless Application Repository Developer Guide contains more information about the two developer
experiences available:
Consuming Applications – Browse for applications and view information about them, including
source code and readme files. Also install, configure, and deploy applications of your choosing.
Publishing Applications – Configure and upload applications to make them available to other
developers, and publish new versions of applications.

AWS CodeStar

AWS CodeStar This is the API reference for AWS CodeStar. This reference provides descriptions of the operations and data types for the AWS CodeStar API along with usage examples. You can use the AWS CodeStar API to work with: Projects and their resources, by calling the following: DeleteProject, which deletes a project. DescribeProject, which lists the attributes of a project. ListProjects, which lists all projects associated with your AWS account. ListResources, which lists the resources associated with a project. ListTagsForProject, which lists the tags associated with a project. TagProject, which adds tags to a project. UntagProject, which removes tags from a project. UpdateProject, which updates the attributes of a project. Teams and team members, by calling the following: AssociateTeamMember, which adds an IAM user to the team for a project. DisassociateTeamMember, which removes an IAM user from the team for a project. ListTeamMembers, which lists all the IAM users in the team for a project, including their roles and attributes. UpdateTeamMember, which updates a team member's attributes in a project. Users, by calling the following: CreateUserProfile, which creates a user profile that contains data associated with the user across all projects. DeleteUserProfile, which deletes all user profile information across all projects. DescribeUserProfile, which describes the profile of a user. ListUserProfiles, which lists all user profiles. UpdateUserProfile, which updates the profile for a user.

AWS IoT Events

AWS IoT Events monitors your equipment or device fleets for failures or changes in operation, and triggers actions when such events occur. You can use AWS IoT Events API operations to create, read, update, and delete inputs and detector models, and to list their versions.

AWS CodeBuild

CodeBuild CodeBuild is a fully managed build service in the cloud. CodeBuild compiles your source code, runs unit tests, and produces artifacts that are ready to deploy. CodeBuild eliminates the need to provision, manage, and scale your own build servers. It provides prepackaged build environments for the most popular programming languages and build tools, such as Apache Maven, Gradle, and more. You can also fully customize build environments in CodeBuild to use your own build tools. CodeBuild scales automatically to meet peak build requests. You pay only for the build time you consume. For more information about CodeBuild, see the CodeBuild User Guide.

Azure Enterprise Knowledge Graph Service

azure.com
Azure Enterprise Knowledge Graph Service is a platform for creating knowledge graphs at scale.

SubscriptionsManagementClient

azure.com
The Admin Subscriptions Management Client.

Azure Alerts Management Service Resource Provider

azure.com
APIs for Azure Smart Detector Alert Rules CRUD operations.

Amazon CodeGuru Reviewer

This section provides documentation for the Amazon CodeGuru Reviewer API operations. CodeGuru Reviewer is a service that uses program analysis and machine learning to detect potential defects that are difficult for developers to find and recommends fixes in your Java and Python code. By proactively detecting and providing recommendations for addressing code defects and implementing best practices, CodeGuru Reviewer improves the overall quality and maintainability of your code base during the code review stage. For more information about CodeGuru Reviewer, see the Amazon CodeGuru Reviewer User Guide. To improve the security of your CodeGuru Reviewer API calls, you can establish a private connection between your VPC and CodeGuru Reviewer by creating an interface VPC endpoint. For more information, see CodeGuru Reviewer and interface VPC endpoints (Amazon Web Services PrivateLink) in the Amazon CodeGuru Reviewer User Guide.

Amazon Simple Workflow Service

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 .