Mock sample for your project: Amazon CloudFront API

Doc Engage API - Amazon Pinpoint API

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 .

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.

AWS CodePipeline Overview This is the AWS CodePipeline API Reference. This guide provides descriptions of the actions and data types for AWS CodePipeline. Some functionality for your pipeline can only be configured through the API. For more information, see the AWS CodePipeline User Guide. You can use the AWS CodePipeline API to work with pipelines, stages, actions, and transitions. Pipelines are models of automated release processes. Each pipeline is uniquely named, and consists of stages, actions, and transitions. You can work with pipelines by calling: CreatePipeline, which creates a uniquely named pipeline. DeletePipeline, which deletes the specified pipeline. GetPipeline, which returns information about the pipeline structure and pipeline metadata, including the pipeline Amazon Resource Name (ARN). GetPipelineExecution, which returns information about a specific execution of a pipeline. GetPipelineState, which returns information about the current state of the stages and actions of a pipeline. ListActionExecutions, which returns action-level details for past executions. The details include full stage and action-level details, including individual action duration, status, any errors that occurred during the execution, and input and output artifact location details. ListPipelines, which gets a summary of all of the pipelines associated with your account. ListPipelineExecutions, which gets a summary of the most recent executions for a pipeline. StartPipelineExecution, which runs the most recent revision of an artifact through the pipeline. StopPipelineExecution, which stops the specified pipeline execution from continuing through the pipeline. UpdatePipeline, which updates a pipeline with edits or changes to the structure of the pipeline. Pipelines include stages. Each stage contains one or more actions that must complete before the next stage begins. A stage results in success or failure. If a stage fails, the pipeline stops at that stage and remains stopped until either a new version of an artifact appears in the source location, or a user takes action to rerun the most recent artifact through the pipeline. You can call GetPipelineState, which displays the status of a pipeline, including the status of stages in the pipeline, or GetPipeline, which returns the entire structure of the pipeline, including the stages of that pipeline. For more information about the structure of stages and actions, see AWS CodePipeline Pipeline Structure Reference. Pipeline stages include actions that are categorized into categories such as source or build actions performed in a stage of a pipeline. For example, you can use a source action to import artifacts into a pipeline from a source such as Amazon S3. Like stages, you do not work with actions directly in most cases, but you do define and interact with actions when working with pipeline operations such as CreatePipeline and GetPipelineState. Valid action categories are: Source Build Test Deploy Approval Invoke Pipelines also include transitions, which allow the transition of artifacts from one stage to the next in a pipeline after the actions in one stage complete. You can work with transitions by calling: DisableStageTransition, which prevents artifacts from transitioning to the next stage in a pipeline. EnableStageTransition, which enables transition of artifacts between stages in a pipeline. Using the API to integrate with AWS CodePipeline For third-party integrators or developers who want to create their own integrations with AWS CodePipeline, the expected sequence varies from the standard API user. To integrate with AWS CodePipeline, developers need to work with the following items: Jobs, which are instances of an action. For example, a job for a source action might import a revision of an artifact from a source. You can work with jobs by calling: AcknowledgeJob, which confirms whether a job worker has received the specified job. GetJobDetails, which returns the details of a job. PollForJobs, which determines whether there are any jobs to act on. PutJobFailureResult, which provides details of a job failure. PutJobSuccessResult, which provides details of a job success. Third party jobs, which are instances of an action created by a partner action and integrated into AWS CodePipeline. Partner actions are created by members of the AWS Partner Network. You can work with third party jobs by calling: AcknowledgeThirdPartyJob, which confirms whether a job worker has received the specified job. GetThirdPartyJobDetails, which requests the details of a job for a partner action. PollForThirdPartyJobs, which determines whether there are any jobs to act on. PutThirdPartyJobFailureResult, which provides details of a job failure. PutThirdPartyJobSuccessResult, which provides details of a job success.

For more information about AWS CloudHSM, see AWS CloudHSM and the AWS CloudHSM User Guide.

Amazon Connect Customer Profiles Welcome to the Amazon Connect Customer Profiles API Reference. This guide provides information about the Amazon Connect Customer Profiles API, including supported operations, data types, parameters, and schemas. Amazon Connect Customer Profiles is a unified customer profile for your contact center that has pre-built connectors powered by AppFlow that make it easy to combine customer information from third party applications, such as Salesforce (CRM), ServiceNow (ITSM), and your enterprise resource planning (ERP), with contact history from your Amazon Connect contact center. If you're new to Amazon Connect , you might find it helpful to also review the Amazon Connect Administrator Guide.

Using the Amazon Cognito User Pools API, you can create a user pool to manage directories and users. You can authenticate a user to obtain tokens related to user identity and access policies. This API reference provides information about user pools in Amazon Cognito User Pools. For more information, see the Amazon Cognito Documentation.

Config Config provides a way to keep track of the configurations of all the Amazon Web Services resources associated with your Amazon Web Services account. You can use Config to get the current and historical configurations of each Amazon Web Services resource and also to get information about the relationship between the resources. An Amazon Web Services resource can be an Amazon Compute Cloud (Amazon EC2) instance, an Elastic Block Store (EBS) volume, an elastic network Interface (ENI), or a security group. For a complete list of resources currently supported by Config, see Supported Amazon Web Services resources. You can access and manage Config through the Amazon Web Services Management Console, the Amazon Web Services Command Line Interface (Amazon Web Services CLI), the Config API, or the Amazon Web Services SDKs for Config. This reference guide contains documentation for the Config API and the Amazon Web Services CLI commands that you can use to manage Config. The Config API uses the Signature Version 4 protocol for signing requests. For more information about how to sign a request with this protocol, see Signature Version 4 Signing Process. For detailed information about Config features and their associated actions or commands, as well as how to work with Amazon Web Services Management Console, see What Is Config in the Config Developer Guide.

Amazon Comprehend Medical extracts structured information from unstructured clinical text. Use these actions to gain insight in your documents.

AWS Application Discovery Service AWS Application Discovery Service helps you plan application migration projects. It automatically identifies servers, virtual machines (VMs), and network dependencies in your on-premises data centers. For more information, see the AWS Application Discovery Service FAQ. Application Discovery Service offers three ways of performing discovery and collecting data about your on-premises servers: Agentless discovery is recommended for environments that use VMware vCenter Server. This mode doesn't require you to install an agent on each host. It does not work in non-VMware environments. Agentless discovery gathers server information regardless of the operating systems, which minimizes the time required for initial on-premises infrastructure assessment. Agentless discovery doesn't collect information about network dependencies, only agent-based discovery collects that information. Agent-based discovery collects a richer set of data than agentless discovery by using the AWS Application Discovery Agent, which you install on one or more hosts in your data center. The agent captures infrastructure and application information, including an inventory of running processes, system performance information, resource utilization, and network dependencies. The information collected by agents is secured at rest and in transit to the Application Discovery Service database in the cloud. AWS Partner Network (APN) solutions integrate with Application Discovery Service, enabling you to import details of your on-premises environment directly into Migration Hub without using the discovery connector or discovery agent. Third-party application discovery tools can query AWS Application Discovery Service, and they can write to the Application Discovery Service database using the public API. In this way, you can import data into Migration Hub and view it, so that you can associate applications with servers and track migrations. Recommendations We recommend that you use agent-based discovery for non-VMware environments, and whenever you want to collect information about network dependencies. You can run agent-based and agentless discovery simultaneously. Use agentless discovery to complete the initial infrastructure assessment quickly, and then install agents on select hosts to collect additional information. Working With This Guide This API reference provides descriptions, syntax, and usage examples for each of the actions and data types for Application Discovery Service. The topic for each action shows the API request parameters and the response. Alternatively, you can use one of the AWS SDKs to access an API that is tailored to the programming language or platform that you're using. For more information, see AWS SDKs. Remember that you must set your Migration Hub home region before you call any of these APIs. You must make API calls for write actions (create, notify, associate, disassociate, import, or put) while in your home region, or a HomeRegionNotSetException error is returned. API calls for read actions (list, describe, stop, and delete) are permitted outside of your home region. Although it is unlikely, the Migration Hub home region could change. If you call APIs outside the home region, an InvalidInputException is returned. You must call GetHomeRegion to obtain the latest Migration Hub home region. This guide is intended for use with the AWS Application Discovery Service User Guide. All data is handled according to the AWS Privacy Policy. You can operate Application Discovery Service offline to inspect collected data before it is shared with the service.

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.

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

The transactional data APIs for Amazon QLDB Instead of interacting directly with this API, we recommend using the QLDB driver or the QLDB shell to execute data transactions on a ledger. If you are working with an AWS SDK, use the QLDB driver. The driver provides a high-level abstraction layer above this QLDB Session data plane and manages SendCommand API calls for you. For information and a list of supported programming languages, see Getting started with the driver in the Amazon QLDB Developer Guide. If you are working with the AWS Command Line Interface (AWS CLI), use the QLDB shell. The shell is a command line interface that uses the QLDB driver to interact with a ledger. For information, see Accessing Amazon QLDB using the QLDB shell.

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

Glue DataBrew is a visual, cloud-scale data-preparation service. DataBrew simplifies data preparation tasks, targeting data issues that are hard to spot and time-consuming to fix. DataBrew empowers users of all technical levels to visualize the data and perform one-click data transformations, with no coding required.

Identity and Access Management Access Analyzer helps identify potential resource-access risks by enabling you to identify any policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview and validate public and cross-account access to your resources before deploying permissions changes. This guide describes the Identity and Access Management Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide. To start using IAM Access Analyzer, you first need to create an analyzer.

The WorkMail Message Flow API provides access to email messages as they are being sent and received by a WorkMail organization.

This is AWS WAF Classic Regional documentation. For more information, see AWS WAF Classic in the developer guide. For the latest version of AWS WAF, use the AWS WAFV2 API and see the AWS WAF Developer Guide. With the latest version, AWS WAF has a single set of endpoints for regional and global use. This is the AWS WAF Regional Classic API Reference for using AWS WAF Classic with the AWS resources, Elastic Load Balancing (ELB) Application Load Balancers and API Gateway APIs. The AWS WAF Classic actions and data types listed in the reference are available for protecting Elastic Load Balancing (ELB) Application Load Balancers and API Gateway APIs. You can use these actions and data types by means of the endpoints listed in AWS Regions and Endpoints. This guide is for developers who need detailed information about the AWS WAF Classic API actions, data types, and errors. For detailed information about AWS WAF Classic features and an overview of how to use the AWS WAF Classic API, see the AWS WAF Classic in the developer guide.

APIs for Azure Smart Detector Alert Rules CRUD operations.

Amazon S3 on Outposts provides access to S3 on Outposts operations.

Amazon API Gateway Amazon API Gateway helps developers deliver robust, secure, and scalable mobile and web application back ends. API Gateway allows developers to securely connect mobile and web applications to APIs that run on AWS Lambda, Amazon EC2, or other publicly addressable web services that are hosted outside of AWS.

AWS Elemental MediaPackage VOD

Amazon RDS Performance Insights Amazon RDS Performance Insights enables you to monitor and explore different dimensions of database load based on data captured from a running DB instance. The guide provides detailed information about Performance Insights data types, parameters and errors. When Performance Insights is enabled, the Amazon RDS Performance Insights API provides visibility into the performance of your DB instance. Amazon CloudWatch provides the authoritative source for AWS service-vended monitoring metrics. Performance Insights offers a domain-specific view of DB load. DB load is measured as Average Active Sessions. Performance Insights provides the data to API consumers as a two-dimensional time-series dataset. The time dimension provides DB load data for each time point in the queried time range. Each time point decomposes overall load in relation to the requested dimensions, measured at that time point. Examples include SQL, Wait event, User, and Host. To learn more about Performance Insights and Amazon Aurora DB instances, go to the Amazon Aurora User Guide. To learn more about Performance Insights and Amazon RDS DB instances, go to the Amazon RDS User Guide.