Mock sample for your project: AWS CodeDeploy API

Amazon Macie Classic Amazon Macie Classic is a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. Macie Classic recognizes sensitive data such as personally identifiable information (PII) or intellectual property, and provides you with dashboards and alerts that give visibility into how this data is being accessed or moved. For more information, see the Amazon Macie Classic User Guide.

Amazon Cognito Sync Amazon Cognito Sync provides an AWS service and client library that enable cross-device syncing of application-related user data. High-level client libraries are available for both iOS and Android. You can use these libraries to persist data locally so that it's available even if the device is offline. Developer credentials don't need to be stored on the mobile device to access the service. You can use Amazon Cognito to obtain a normalized user ID and credentials. User data is persisted in a dataset that can store up to 1 MB of key-value pairs, and you can have up to 20 datasets per user identity. With Amazon Cognito Sync, the data stored for each identity is accessible only to credentials assigned to that identity. In order to use the Cognito Sync service, you need to make API calls using credentials retrieved with Amazon Cognito Identity service. If you want to use Cognito Sync in an Android or iOS application, you will probably want to make API calls via the AWS Mobile SDK. To learn more, see the Developer Guide for Android and the Developer Guide for iOS.

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.

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.

Amazon Lex provides both build and runtime endpoints. Each endpoint provides a set of operations (API). Your conversational bot uses the runtime API to understand user utterances (user input text or voice). For example, suppose a user says "I want pizza", your bot sends this input to Amazon Lex using the runtime API. Amazon Lex recognizes that the user request is for the OrderPizza intent (one of the intents defined in the bot). Then Amazon Lex engages in user conversation on behalf of the bot to elicit required information (slot values, such as pizza size and crust type), and then performs fulfillment activity (that you configured when you created the bot). You use the build-time API to create and manage your Amazon Lex bot. For a list of build-time operations, see the build-time API, .

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.

When you create a VPC using Amazon VPC, you automatically get DNS resolution within the VPC from Route 53 Resolver. By default, Resolver answers DNS queries for VPC domain names such as domain names for EC2 instances or Elastic Load Balancing load balancers. Resolver performs recursive lookups against public name servers for all other domain names. You can also configure DNS resolution between your VPC and your network over a Direct Connect or VPN connection: Forward DNS queries from resolvers on your network to Route 53 Resolver DNS resolvers on your network can forward DNS queries to Resolver in a specified VPC. This allows your DNS resolvers to easily resolve domain names for Amazon Web Services resources such as EC2 instances or records in a Route 53 private hosted zone. For more information, see How DNS Resolvers on Your Network Forward DNS Queries to Route 53 Resolver in the Amazon Route 53 Developer Guide. Conditionally forward queries from a VPC to resolvers on your network You can configure Resolver to forward queries that it receives from EC2 instances in your VPCs to DNS resolvers on your network. To forward selected queries, you create Resolver rules that specify the domain names for the DNS queries that you want to forward (such as example.com), and the IP addresses of the DNS resolvers on your network that you want to forward the queries to. If a query matches multiple rules (example.com, acme.example.com), Resolver chooses the rule with the most specific match (acme.example.com) and forwards the query to the IP addresses that you specified in that rule. For more information, see How Route 53 Resolver Forwards DNS Queries from Your VPCs to Your Network in the Amazon Route 53 Developer Guide. Like Amazon VPC, Resolver is Regional. In each Region where you have VPCs, you can choose whether to forward queries from your VPCs to your network (outbound queries), from your network to your VPCs (inbound queries), or both.

AWS Data Exchange is a service that makes it easy for AWS customers to exchange data in the cloud. You can use the AWS Data Exchange APIs to create, update, manage, and access file-based data set in the AWS Cloud. As a subscriber, you can view and access the data sets that you have an entitlement to through a subscription. You can use the APIS to download or copy your entitled data sets to Amazon S3 for use across a variety of AWS analytics and machine learning services. As a provider, you can create and manage your data sets that you would like to publish to a product. Being able to package and provide your data sets into products requires a few steps to determine eligibility. For more information, visit the AWS Data Exchange User Guide. A data set is a collection of data that can be changed or updated over time. Data sets can be updated using revisions, which represent a new version or incremental change to a data set. A revision contains one or more assets. An asset in AWS Data Exchange is a piece of data that can be stored as an Amazon S3 object. The asset can be a structured data file, an image file, or some other data file. Jobs are asynchronous import or export operations used to create or copy assets.

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.

AWS CodeCommit This is the AWS CodeCommit API Reference. This reference provides descriptions of the operations and data types for AWS CodeCommit API along with usage examples. You can use the AWS CodeCommit API to work with the following objects: Repositories, by calling the following: BatchGetRepositories, which returns information about one or more repositories associated with your AWS account. CreateRepository, which creates an AWS CodeCommit repository. DeleteRepository, which deletes an AWS CodeCommit repository. GetRepository, which returns information about a specified repository. ListRepositories, which lists all AWS CodeCommit repositories associated with your AWS account. UpdateRepositoryDescription, which sets or updates the description of the repository. UpdateRepositoryName, which changes the name of the repository. If you change the name of a repository, no other users of that repository can access it until you send them the new HTTPS or SSH URL to use. Branches, by calling the following: CreateBranch, which creates a branch in a specified repository. DeleteBranch, which deletes the specified branch in a repository unless it is the default branch. GetBranch, which returns information about a specified branch. ListBranches, which lists all branches for a specified repository. UpdateDefaultBranch, which changes the default branch for a repository. Files, by calling the following: DeleteFile, which deletes the content of a specified file from a specified branch. GetBlob, which returns the base-64 encoded content of an individual Git blob object in a repository. GetFile, which returns the base-64 encoded content of a specified file. GetFolder, which returns the contents of a specified folder or directory. PutFile, which adds or modifies a single file in a specified repository and branch. Commits, by calling the following: BatchGetCommits, which returns information about one or more commits in a repository. CreateCommit, which creates a commit for changes to a repository. GetCommit, which returns information about a commit, including commit messages and author and committer information. GetDifferences, which returns information about the differences in a valid commit specifier (such as a branch, tag, HEAD, commit ID, or other fully qualified reference). Merges, by calling the following: BatchDescribeMergeConflicts, which returns information about conflicts in a merge between commits in a repository. CreateUnreferencedMergeCommit, which creates an unreferenced commit between two branches or commits for the purpose of comparing them and identifying any potential conflicts. DescribeMergeConflicts, which returns information about merge conflicts between the base, source, and destination versions of a file in a potential merge. GetMergeCommit, which returns information about the merge between a source and destination commit. GetMergeConflicts, which returns information about merge conflicts between the source and destination branch in a pull request. GetMergeOptions, which returns information about the available merge options between two branches or commit specifiers. MergeBranchesByFastForward, which merges two branches using the fast-forward merge option. MergeBranchesBySquash, which merges two branches using the squash merge option. MergeBranchesByThreeWay, which merges two branches using the three-way merge option. Pull requests, by calling the following: CreatePullRequest, which creates a pull request in a specified repository. CreatePullRequestApprovalRule, which creates an approval rule for a specified pull request. DeletePullRequestApprovalRule, which deletes an approval rule for a specified pull request. DescribePullRequestEvents, which returns information about one or more pull request events. EvaluatePullRequestApprovalRules, which evaluates whether a pull request has met all the conditions specified in its associated approval rules. GetCommentsForPullRequest, which returns information about comments on a specified pull request. GetPullRequest, which returns information about a specified pull request. GetPullRequestApprovalStates, which returns information about the approval states for a specified pull request. GetPullRequestOverrideState, which returns information about whether approval rules have been set aside (overriden) for a pull request, and if so, the Amazon Resource Name (ARN) of the user or identity that overrode the rules and their requirements for the pull request. ListPullRequests, which lists all pull requests for a repository. MergePullRequestByFastForward, which merges the source destination branch of a pull request into the specified destination branch for that pull request using the fast-forward merge option. MergePullRequestBySquash, which merges the source destination branch of a pull request into the specified destination branch for that pull request using the squash merge option. MergePullRequestByThreeWay. which merges the source destination branch of a pull request into the specified destination branch for that pull request using the three-way merge option. OverridePullRequestApprovalRules, which sets aside all approval rule requirements for a pull request. PostCommentForPullRequest, which posts a comment to a pull request at the specified line, file, or request. UpdatePullRequestApprovalRuleContent, which updates the structure of an approval rule for a pull request. UpdatePullRequestApprovalState, which updates the state of an approval on a pull request. UpdatePullRequestDescription, which updates the description of a pull request. UpdatePullRequestStatus, which updates the status of a pull request. UpdatePullRequestTitle, which updates the title of a pull request. Approval rule templates, by calling the following: AssociateApprovalRuleTemplateWithRepository, which associates a template with a specified repository. After the template is associated with a repository, AWS CodeCommit creates approval rules that match the template conditions on every pull request created in the specified repository. BatchAssociateApprovalRuleTemplateWithRepositories, which associates a template with one or more specified repositories. After the template is associated with a repository, AWS CodeCommit creates approval rules that match the template conditions on every pull request created in the specified repositories. BatchDisassociateApprovalRuleTemplateFromRepositories, which removes the association between a template and specified repositories so that approval rules based on the template are not automatically created when pull requests are created in those repositories. CreateApprovalRuleTemplate, which creates a template for approval rules that can then be associated with one or more repositories in your AWS account. DeleteApprovalRuleTemplate, which deletes the specified template. It does not remove approval rules on pull requests already created with the template. DisassociateApprovalRuleTemplateFromRepository, which removes the association between a template and a repository so that approval rules based on the template are not automatically created when pull requests are created in the specified repository. GetApprovalRuleTemplate, which returns information about an approval rule template. ListApprovalRuleTemplates, which lists all approval rule templates in the AWS Region in your AWS account. ListAssociatedApprovalRuleTemplatesForRepository, which lists all approval rule templates that are associated with a specified repository. ListRepositoriesForApprovalRuleTemplate, which lists all repositories associated with the specified approval rule template. UpdateApprovalRuleTemplateDescription, which updates the description of an approval rule template. UpdateApprovalRuleTemplateName, which updates the name of an approval rule template. UpdateApprovalRuleTemplateContent, which updates the content of an approval rule template. Comments in a repository, by calling the following: DeleteCommentContent, which deletes the content of a comment on a commit in a repository. GetComment, which returns information about a comment on a commit. GetCommentReactions, which returns information about emoji reactions to comments. GetCommentsForComparedCommit, which returns information about comments on the comparison between two commit specifiers in a repository. PostCommentForComparedCommit, which creates a comment on the comparison between two commit specifiers in a repository. PostCommentReply, which creates a reply to a comment. PutCommentReaction, which creates or updates an emoji reaction to a comment. UpdateComment, which updates the content of a comment on a commit in a repository. Tags used to tag resources in AWS CodeCommit (not Git tags), by calling the following: ListTagsForResource, which gets information about AWS tags for a specified Amazon Resource Name (ARN) in AWS CodeCommit. TagResource, which adds or updates tags for a resource in AWS CodeCommit. UntagResource, which removes tags for a resource in AWS CodeCommit. Triggers, by calling the following: GetRepositoryTriggers, which returns information about triggers configured for a repository. PutRepositoryTriggers, which replaces all triggers for a repository and can be used to create or delete triggers. TestRepositoryTriggers, which tests the functionality of a repository trigger by sending data to the trigger target. For information about how to use AWS CodeCommit, see the AWS CodeCommit User Guide.

Amazon Route 53 API actions let you register domain names and perform related operations.

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.

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.

Deployment Admin Client.

Provides APIs for creating and managing Amazon SageMaker resources. Other Resources: Amazon SageMaker Developer Guide Amazon Augmented AI Runtime API Reference

Identity and Access Management Identity and Access Management (IAM) is a web service for securely controlling access to Amazon Web Services services. With IAM, you can centrally manage users, security credentials such as access keys, and permissions that control which Amazon Web Services resources users and applications can access. For more information about IAM, see Identity and Access Management (IAM) and the Identity and Access Management User Guide.

AWS IoT Secure Tunneling AWS IoT Secure Tunnling enables you to create remote connections to devices deployed in the field. For more information about how AWS IoT Secure Tunneling works, see AWS IoT Secure Tunneling.

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 DynamoDB Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database, so that you don't have to worry about hardware provisioning, setup and configuration, replication, software patching, or cluster scaling. With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic. You can scale up or scale down your tables' throughput capacity without downtime or performance degradation, and use the AWS Management Console to monitor resource utilization and performance metrics. DynamoDB automatically spreads the data and traffic for your tables over a sufficient number of servers to handle your throughput and storage requirements, while maintaining consistent and fast performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across multiple Availability Zones in an AWS region, providing built-in high availability and data durability.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

Allows extension of ARM control plane with custom resource providers.

You can use the Amazon Elastic Block Store (Amazon EBS) direct APIs to create Amazon EBS snapshots, write data directly to your snapshots, read data on your snapshots, and identify the differences or changes between two snapshots. If you’re an independent software vendor (ISV) who offers backup services for Amazon EBS, the EBS direct APIs make it more efficient and cost-effective to track incremental changes on your Amazon EBS volumes through snapshots. This can be done without having to create new volumes from snapshots, and then use Amazon Elastic Compute Cloud (Amazon EC2) instances to compare the differences. You can create incremental snapshots directly from data on-premises into volumes and the cloud to use for quick disaster recovery. With the ability to write and read snapshots, you can write your on-premises data to an snapshot during a disaster. Then after recovery, you can restore it back to Amazon Web Services or on-premises from the snapshot. You no longer need to build and maintain complex mechanisms to copy data to and from Amazon EBS. This API reference provides detailed information about the actions, data types, parameters, and errors of the EBS direct APIs. For more information about the elements that make up the EBS direct APIs, and examples of how to use them effectively, see Accessing the Contents of an Amazon EBS Snapshot in the Amazon Elastic Compute Cloud User Guide. For more information about the supported Amazon Web Services Regions, endpoints, and service quotas for the EBS direct APIs, see Amazon Elastic Block Store Endpoints and Quotas in the Amazon Web Services General Reference.

APIs to manage web application firewall rules for Azure CDN