Mock sample for your project: Amazon Simple Email Service API

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.

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.

DAX is a managed caching service engineered for Amazon DynamoDB. DAX dramatically speeds up database reads by caching frequently-accessed data from DynamoDB, so applications can access that data with sub-millisecond latency. You can create a DAX cluster easily, using the AWS Management Console. With a few simple modifications to your code, your application can begin taking advantage of the DAX cluster and realize significant improvements in read performance.

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.

An AWS Elemental MediaStore container is a namespace that holds folders and objects. You use a container endpoint to create, read, and delete objects.

With Application Auto Scaling, you can configure automatic scaling for the following resources: Amazon AppStream 2.0 fleets Amazon Aurora Replicas Amazon Comprehend document classification and entity recognizer endpoints Amazon DynamoDB tables and global secondary indexes throughput capacity Amazon ECS services Amazon ElastiCache for Redis clusters (replication groups) Amazon EMR clusters Amazon Keyspaces (for Apache Cassandra) tables Lambda function provisioned concurrency Amazon Managed Streaming for Apache Kafka broker storage Amazon SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services API Summary The Application Auto Scaling service API includes three key sets of actions: Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets. Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history. Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

This is the Amazon Rekognition API reference.

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.

Amazon Kinesis Data Analytics is a fully managed service that you can use to process and analyze streaming data using Java, SQL, or Scala. The service enables you to quickly author and run Java, SQL, or Scala code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.

Compute Optimizer is a service that analyzes the configuration and utilization metrics of your Amazon Web Services compute resources, such as Amazon EC2 instances, Amazon EC2 Auto Scaling groups, Lambda functions, and Amazon EBS volumes. It reports whether your resources are optimal, and generates optimization recommendations to reduce the cost and improve the performance of your workloads. Compute Optimizer also provides recent utilization metric data, in addition to projected utilization metric data for the recommendations, which you can use to evaluate which recommendation provides the best price-performance trade-off. The analysis of your usage patterns can help you decide when to move or resize your running resources, and still meet your performance and capacity requirements. For more information about Compute Optimizer, including the required permissions to use the service, see the Compute Optimizer User Guide.

AWS Elemental MediaConvert

The User Subscription Management Client.

Amazon Cognito Federated Identities Amazon Cognito Federated Identities is a web service that delivers scoped temporary credentials to mobile devices and other untrusted environments. It uniquely identifies a device and supplies the user with a consistent identity over the lifetime of an application. Using Amazon Cognito Federated Identities, you can enable authentication with one or more third-party identity providers (Facebook, Google, or Login with Amazon) or an Amazon Cognito user pool, and you can also choose to support unauthenticated access from your app. Cognito delivers a unique identifier for each user and acts as an OpenID token provider trusted by AWS Security Token Service (STS) to access temporary, limited-privilege AWS credentials. For a description of the authentication flow from the Amazon Cognito Developer Guide see Authentication Flow. For more information see Amazon Cognito Federated Identities.

AWS Signer is a fully managed code signing service to help you ensure the trust and integrity of your code. AWS Signer supports the following applications: With code signing for AWS Lambda, you can sign AWS Lambda deployment packages. Integrated support is provided for Amazon S3, Amazon CloudWatch, and AWS CloudTrail. In order to sign code, you create a signing profile and then use Signer to sign Lambda zip files in S3. With code signing for IoT, you can sign code for any IoT device that is supported by AWS. IoT code signing is available for Amazon FreeRTOS and AWS IoT Device Management, and is integrated with AWS Certificate Manager (ACM). In order to sign code, you import a third-party code signing certificate using ACM, and use that to sign updates in Amazon FreeRTOS and AWS IoT Device Management. For more information about AWS Signer, see the AWS Signer Developer Guide.

Description of the new service

AWS OpsWorks CM AWS OpsWorks for configuration management (CM) is a service that runs and manages configuration management servers. You can use AWS OpsWorks CM to create and manage AWS OpsWorks for Chef Automate and AWS OpsWorks for Puppet Enterprise servers, and add or remove nodes for the servers to manage. Glossary of terms Server : A configuration management server that can be highly-available. The configuration management server runs on an Amazon Elastic Compute Cloud (EC2) instance, and may use various other AWS services, such as Amazon Relational Database Service (RDS) and Elastic Load Balancing. A server is a generic abstraction over the configuration manager that you want to use, much like Amazon RDS. In AWS OpsWorks CM, you do not start or stop servers. After you create servers, they continue to run until they are deleted. Engine : The engine is the specific configuration manager that you want to use. Valid values in this release include ChefAutomate and Puppet. Backup : This is an application-level backup of the data that the configuration manager stores. AWS OpsWorks CM creates an S3 bucket for backups when you launch the first server. A backup maintains a snapshot of a server's configuration-related attributes at the time the backup starts. Events : Events are always related to a server. Events are written during server creation, when health checks run, when backups are created, when system maintenance is performed, etc. When you delete a server, the server's events are also deleted. Account attributes : Every account has attributes that are assigned in the AWS OpsWorks CM database. These attributes store information about configuration limits (servers, backups, etc.) and your customer account. Endpoints AWS OpsWorks CM supports the following endpoints, all HTTPS. You must connect to one of the following endpoints. Your servers can only be accessed or managed within the endpoint in which they are created. opsworks-cm.us-east-1.amazonaws.com opsworks-cm.us-east-2.amazonaws.com opsworks-cm.us-west-1.amazonaws.com opsworks-cm.us-west-2.amazonaws.com opsworks-cm.ap-northeast-1.amazonaws.com opsworks-cm.ap-southeast-1.amazonaws.com opsworks-cm.ap-southeast-2.amazonaws.com opsworks-cm.eu-central-1.amazonaws.com opsworks-cm.eu-west-1.amazonaws.com For more information, see AWS OpsWorks endpoints and quotas in the AWS General Reference. Throttling limits All API operations allow for five requests per second with a burst of 10 requests per second.

AWS Service Catalog AWS Service Catalog enables organizations to create and manage catalogs of IT services that are approved for AWS. To get the most out of this documentation, you should be familiar with the terminology discussed in AWS Service Catalog Concepts.

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.

Contains all data plane API operations and data types for the Amazon SageMaker Feature Store. Use this API to put, delete, and retrieve (get) features from a feature store. Use the following operations to configure your OnlineStore and OfflineStore features, and to create and manage feature groups: CreateFeatureGroup DeleteFeatureGroup DescribeFeatureGroup ListFeatureGroups

This is the Amazon Fraud Detector API Reference. This guide is for developers who need detailed information about Amazon Fraud Detector API actions, data types, and errors. For more information about Amazon Fraud Detector features, see the Amazon Fraud Detector User Guide.

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.

DAX is a managed caching service engineered for Amazon DynamoDB. DAX dramatically speeds up database reads by caching frequently-accessed data from DynamoDB, so applications can access that data with sub-millisecond latency. You can create a DAX cluster easily, using the AWS Management Console. With a few simple modifications to your code, your application can begin taking advantage of the DAX cluster and realize significant improvements in read performance.

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.