Mock sample for your project: Amazon GuardDuty API

This is AWS WAF Classic 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 Classic API Reference for using AWS WAF Classic with Amazon CloudFront. The AWS WAF Classic actions and data types listed in the reference are available for protecting Amazon CloudFront distributions. You can use these actions and data types via the endpoint waf.amazonaws.com. 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.

Doc Engage API - Amazon Pinpoint API

Introduction The Amazon Interactive Video Service (IVS) API is REST compatible, using a standard HTTP API and an AWS EventBridge event stream for responses. JSON is used for both requests and responses, including errors. The API is an AWS regional service, currently in these regions: us-west-2, us-east-1, and eu-west-1. All API request parameters and URLs are case sensitive. For a summary of notable documentation changes in each release, see Document History. Service Endpoints The following are the Amazon IVS service endpoints (all HTTPS): Region name: US West (Oregon) Region: us-west-2 Endpoint: ivs.us-west-2.amazonaws.com Region name: US East (Virginia) Region: us-east-1 Endpoint: ivs.us-east-1.amazonaws.com Region name: EU West (Dublin) Region: eu-west-1 Endpoint: ivs.eu-west-1.amazonaws.com Allowed Header Values Accept: application/json Accept-Encoding: gzip, deflate Content-Type: application/json Resources The following resources contain information about your IVS live stream (see Getting Started with Amazon IVS): Channel — Stores configuration data related to your live stream. You first create a channel and then use the channel’s stream key to start your live stream. See the Channel endpoints for more information. Stream key — An identifier assigned by Amazon IVS when you create a channel, which is then used to authorize streaming. See the StreamKey endpoints for more information. Treat the stream key like a secret, since it allows anyone to stream to the channel. Playback key pair — Video playback may be restricted using playback-authorization tokens, which use public-key encryption. A playback key pair is the public-private pair of keys used to sign and validate the playback-authorization token. See the PlaybackKeyPair endpoints for more information. Recording configuration — Stores configuration related to recording a live stream and where to store the recorded content. Multiple channels can reference the same recording configuration. See the Recording Configuration endpoints for more information. Tagging A tag is a metadata label that you assign to an AWS resource. A tag comprises a key and a value, both set by you. For example, you might set a tag as topic:nature to label a particular video category. See Tagging AWS Resources for more information, including restrictions that apply to tags. Tags can help you identify and organize your AWS resources. For example, you can use the same tag for different resources to indicate that they are related. You can also use tags to manage access (see Access Tags). The Amazon IVS API has these tag-related endpoints: TagResource, UntagResource, and ListTagsForResource. The following resources support tagging: Channels, Stream Keys, Playback Key Pairs, and Recording Configurations. Authentication versus Authorization Note the differences between these concepts: Authentication is about verifying identity. You need to be authenticated to sign Amazon IVS API requests. Authorization is about granting permissions. You need to be authorized to view Amazon IVS private channels. (Private channels are channels that are enabled for "playback authorization.") Authentication All Amazon IVS API requests must be authenticated with a signature. The AWS Command-Line Interface (CLI) and Amazon IVS Player SDKs take care of signing the underlying API calls for you. However, if your application calls the Amazon IVS API directly, it’s your responsibility to sign the requests. You generate a signature using valid AWS credentials that have permission to perform the requested action. For example, you must sign PutMetadata requests with a signature generated from an IAM user account that has the ivs:PutMetadata permission. For more information: Authentication and generating signatures — See Authenticating Requests (AWS Signature Version 4) in the AWS General Reference. Managing Amazon IVS permissions — See Identity and Access Management on the Security page of the Amazon IVS User Guide. Channel Endpoints CreateChannel — Creates a new channel and an associated stream key to start streaming. GetChannel — Gets the channel configuration for the specified channel ARN (Amazon Resource Name). BatchGetChannel — Performs GetChannel on multiple ARNs simultaneously. ListChannels — Gets summary information about all channels in your account, in the AWS region where the API request is processed. This list can be filtered to match a specified name or recording-configuration ARN. Filters are mutually exclusive and cannot be used together. If you try to use both filters, you will get an error (409 Conflict Exception). UpdateChannel — Updates a channel's configuration. This does not affect an ongoing stream of this channel. You must stop and restart the stream for the changes to take effect. DeleteChannel — Deletes the specified channel. StreamKey Endpoints CreateStreamKey — Creates a stream key, used to initiate a stream, for the specified channel ARN. GetStreamKey — Gets stream key information for the specified ARN. BatchGetStreamKey — Performs GetStreamKey on multiple ARNs simultaneously. ListStreamKeys — Gets summary information about stream keys for the specified channel. DeleteStreamKey — Deletes the stream key for the specified ARN, so it can no longer be used to stream. Stream Endpoints GetStream — Gets information about the active (live) stream on a specified channel. ListStreams — Gets summary information about live streams in your account, in the AWS region where the API request is processed. StopStream — Disconnects the incoming RTMPS stream for the specified channel. Can be used in conjunction with DeleteStreamKey to prevent further streaming to a channel. PutMetadata — Inserts metadata into the active stream of the specified channel. A maximum of 5 requests per second per channel is allowed, each with a maximum 1 KB payload. (If 5 TPS is not sufficient for your needs, we recommend batching your data into a single PutMetadata call.) PlaybackKeyPair Endpoints For more information, see Setting Up Private Channels in the Amazon IVS User Guide. ImportPlaybackKeyPair — Imports the public portion of a new key pair and returns its arn and fingerprint. The privateKey can then be used to generate viewer authorization tokens, to grant viewers access to private channels (channels enabled for playback authorization). GetPlaybackKeyPair — Gets a specified playback authorization key pair and returns the arn and fingerprint. The privateKey held by the caller can be used to generate viewer authorization tokens, to grant viewers access to private channels. ListPlaybackKeyPairs — Gets summary information about playback key pairs. DeletePlaybackKeyPair — Deletes a specified authorization key pair. This invalidates future viewer tokens generated using the key pair’s privateKey. RecordingConfiguration Endpoints CreateRecordingConfiguration — Creates a new recording configuration, used to enable recording to Amazon S3. GetRecordingConfiguration — Gets the recording-configuration metadata for the specified ARN. ListRecordingConfigurations — Gets summary information about all recording configurations in your account, in the AWS region where the API request is processed. DeleteRecordingConfiguration — Deletes the recording configuration for the specified ARN. AWS Tags Endpoints TagResource — Adds or updates tags for the AWS resource with the specified ARN. UntagResource — Removes tags from the resource with the specified ARN. ListTagsForResource — Gets information about AWS tags for the specified ARN.

This section provides documentation for the Amazon CodeGuru Profiler API operations. Amazon CodeGuru Profiler collects runtime performance data from your live applications, and provides recommendations that can help you fine-tune your application performance. Using machine learning algorithms, CodeGuru Profiler can help you find your most expensive lines of code and suggest ways you can improve efficiency and remove CPU bottlenecks. Amazon CodeGuru Profiler provides different visualizations of profiling data to help you identify what code is running on the CPU, see how much time is consumed, and suggest ways to reduce CPU utilization. Amazon CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python. While CodeGuru Profiler supports both visualizations and recommendations for applications written in Java, it can also generate visualizations and a subset of recommendations for applications written in other JVM languages and Python. For more information, see What is Amazon CodeGuru Profiler in the Amazon CodeGuru Profiler User Guide.

Amazon EventBridge helps you to respond to state changes in your Amazon Web Services resources. When your resources change state, they automatically send events to an event stream. You can create rules that match selected events in the stream and route them to targets to take action. You can also use rules to take action on a predetermined schedule. For example, you can configure rules to: Automatically invoke an Lambda function to update DNS entries when an event notifies you that Amazon EC2 instance enters the running state. Direct specific API records from CloudTrail to an Amazon Kinesis data stream for detailed analysis of potential security or availability risks. Periodically invoke a built-in target to create a snapshot of an Amazon EBS volume. For more information about the features of Amazon EventBridge, see the Amazon EventBridge User Guide.

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

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

AWS CodeDeploy AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances running in your own facility, serverless AWS Lambda functions, or applications in an Amazon ECS service. You can deploy a nearly unlimited variety of application content, such as an updated Lambda function, updated applications in an Amazon ECS service, code, web and configuration files, executables, packages, scripts, multimedia files, and so on. AWS CodeDeploy can deploy application content stored in Amazon S3 buckets, GitHub repositories, or Bitbucket repositories. You do not need to make changes to your existing code before you can use AWS CodeDeploy. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications, without many of the risks associated with error-prone manual deployments. AWS CodeDeploy Components Use the information in this guide to help you work with the following AWS CodeDeploy components: Application : A name that uniquely identifies the application you want to deploy. AWS CodeDeploy uses this name, which functions as a container, to ensure the correct combination of revision, deployment configuration, and deployment group are referenced during a deployment. Deployment group : A set of individual instances, CodeDeploy Lambda deployment configuration settings, or an Amazon ECS service and network details. A Lambda deployment group specifies how to route traffic to a new version of a Lambda function. An Amazon ECS deployment group specifies the service created in Amazon ECS to deploy, a load balancer, and a listener to reroute production traffic to an updated containerized application. An EC2/On-premises deployment group contains individually tagged instances, Amazon EC2 instances in Amazon EC2 Auto Scaling groups, or both. All deployment groups can specify optional trigger, alarm, and rollback settings. Deployment configuration : A set of deployment rules and deployment success and failure conditions used by AWS CodeDeploy during a deployment. Deployment : The process and the components used when updating a Lambda function, a containerized application in an Amazon ECS service, or of installing content on one or more instances. Application revisions : For an AWS Lambda deployment, this is an AppSpec file that specifies the Lambda function to be updated and one or more functions to validate deployment lifecycle events. For an Amazon ECS deployment, this is an AppSpec file that specifies the Amazon ECS task definition, container, and port where production traffic is rerouted. For an EC2/On-premises deployment, this is an archive file that contains source content—source code, webpages, executable files, and deployment scripts—along with an AppSpec file. Revisions are stored in Amazon S3 buckets or GitHub repositories. For Amazon S3, a revision is uniquely identified by its Amazon S3 object key and its ETag, version, or both. For GitHub, a revision is uniquely identified by its commit ID. This guide also contains information to help you get details about the instances in your deployments, to make on-premises instances available for AWS CodeDeploy deployments, to get details about a Lambda function deployment, and to get details about Amazon ECS service deployments. AWS CodeDeploy Information Resources AWS CodeDeploy User Guide AWS CodeDeploy API Reference Guide AWS CLI Reference for AWS CodeDeploy AWS CodeDeploy Developer Forum

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.

Amazon Relational Database Service Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, resizeable capacity for an industry-standard relational database and manages common database administration tasks, freeing up developers to focus on what makes their applications and businesses unique. Amazon RDS gives you access to the capabilities of a MySQL, MariaDB, PostgreSQL, Microsoft SQL Server, Oracle, or Amazon Aurora database server. These capabilities mean that the code, applications, and tools you already use today with your existing databases work with Amazon RDS without modification. Amazon RDS automatically backs up your database and maintains the database software that powers your DB instance. Amazon RDS is flexible: you can scale your DB instance's compute resources and storage capacity to meet your application's demand. As with all Amazon Web Services, there are no up-front investments, and you pay only for the resources you use. This interface reference for Amazon RDS contains documentation for a programming or command line interface you can use to manage Amazon RDS. Amazon RDS is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide. Amazon RDS API Reference For the alphabetical list of API actions, see API Actions. For the alphabetical list of data types, see Data Types. For a list of common query parameters, see Common Parameters. For descriptions of the error codes, see Common Errors. Amazon RDS User Guide For a summary of the Amazon RDS interfaces, see Available RDS Interfaces. For more information about how to use the Query API, see Using the Query API.

Amazon Managed Workflows for Apache Airflow This section contains the Amazon Managed Workflows for Apache Airflow (MWAA) API reference documentation. For more information, see What Is Amazon MWAA?.

The Admin Storage Management Client.

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.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

The Container Service Client.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

The Container Service Client.

Creates an Azure Data Lake Analytics job client.

This API exposes Azure Log Analytics query capabilities