Mock sample for your project: Elastic Load Balancing API

Amazon FSx is a fully managed service that makes it easy for storage and application administrators to launch and use shared file storage.

AWS Step Functions AWS Step Functions is a service that lets you coordinate the components of distributed applications and microservices using visual workflows. You can use Step Functions to build applications from individual components, each of which performs a discrete function, or task, allowing you to scale and change applications quickly. Step Functions provides a console that helps visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step, and retries steps when there are errors, so your application executes predictably and in the right order every time. Step Functions logs the state of each step, so you can quickly diagnose and debug any issues. Step Functions manages operations and underlying infrastructure to ensure your application is available at any scale. You can run tasks on AWS, your own servers, or any system that has access to AWS. You can access and use Step Functions using the console, the AWS SDKs, or an HTTP API. For more information about Step Functions, see the AWS Step Functions Developer Guide .

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 HealthLake is a HIPAA eligibile service that allows customers to store, transform, query, and analyze their FHIR-formatted data in a consistent fashion in the cloud.

CloudTrail This is the CloudTrail API Reference. It provides descriptions of actions, data types, common parameters, and common errors for CloudTrail. CloudTrail is a web service that records Amazon Web Services API calls for your Amazon Web Services account and delivers log files to an Amazon S3 bucket. The recorded information includes the identity of the user, the start time of the Amazon Web Services API call, the source IP address, the request parameters, and the response elements returned by the service. As an alternative to the API, you can use one of the Amazon Web Services SDKs, which consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .NET, iOS, Android, etc.). The SDKs provide programmatic access to CloudTrail. For example, the SDKs handle cryptographically signing requests, managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools to Build on Amazon Web Services. See the CloudTrail User Guide for information about the data that is included with each Amazon Web Services API call listed in the log files.

Operations and objects for transcribing speech to text.

Describes all of the AWS IoT 1-Click device-related API operations for the service.
Also provides sample requests, responses, and errors for the supported web services
protocols.

Amazon CloudWatch Synthetics You can use Amazon CloudWatch Synthetics to continually monitor your services. You can create and manage canaries, which are modular, lightweight scripts that monitor your endpoints and APIs from the outside-in. You can set up your canaries to run 24 hours a day, once per minute. The canaries help you check the availability and latency of your web services and troubleshoot anomalies by investigating load time data, screenshots of the UI, logs, and metrics. The canaries seamlessly integrate with CloudWatch ServiceLens to help you trace the causes of impacted nodes in your applications. For more information, see Using ServiceLens to Monitor the Health of Your Applications in the Amazon CloudWatch User Guide. Before you create and manage canaries, be aware of the security considerations. For more information, see Security Considerations for Synthetics Canaries.

The AWS Migration Hub API methods help to obtain server and application migration status and integrate your resource-specific migration tool by providing a programmatic interface to Migration Hub. Remember that you must set your AWS Migration Hub home region before you call any of these APIs, or a HomeRegionNotSetException error will be returned. Also, you must make the API calls while in your home region.

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 Simple Workflow Service The Amazon Simple Workflow Service (Amazon SWF) makes it easy to build applications that use Amazon's cloud to coordinate work across distributed components. In Amazon SWF, a task represents a logical unit of work that is performed by a component of your workflow. Coordinating tasks in a workflow involves managing intertask dependencies, scheduling, and concurrency in accordance with the logical flow of the application. Amazon SWF gives you full control over implementing tasks and coordinating them without worrying about underlying complexities such as tracking their progress and maintaining their state. This documentation serves as reference only. For a broader overview of the Amazon SWF programming model, see the Amazon SWF Developer Guide .

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 Admin Compute Disk Management Client.

Amazon Polly is a web service that makes it easy to synthesize speech from text. The Amazon Polly service provides API operations for synthesizing high-quality speech from plain text and Speech Synthesis Markup Language (SSML), along with managing pronunciations lexicons that enable you to get the best results for your application domain.

Amazon Elastic Container Registry Public Amazon Elastic Container Registry (Amazon ECR) is a managed container image registry service. Amazon ECR provides both public and private registries to host your container images. You can use the familiar Docker CLI, or their preferred client, to push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry for your Docker or Open Container Initiative (OCI) images. Amazon ECR supports public repositories with this API. For information about the Amazon ECR API for private repositories, see Amazon Elastic Container Registry API Reference.

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.

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

This is the Amazon Lookout for Vision API Reference. It provides descriptions of actions, data types, common parameters, and common errors. Amazon Lookout for Vision enables you to find visual defects in industrial products, accurately and at scale. It uses computer vision to identify missing components in an industrial product, damage to vehicles or structures, irregularities in production lines, and even minuscule defects in silicon wafers — or any other physical item where quality is important such as a missing capacitor on printed circuit boards.

Welcome to the AWS Ground Station API Reference. AWS Ground Station is a fully managed service that enables you to control satellite communications, downlink and process satellite data, and scale your satellite operations efficiently and cost-effectively without having to build or manage your own ground station infrastructure.

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS. Amazon EMR containers is the API name for Amazon EMR on EKS. The emr-containers prefix is used in the following scenarios: It is the prefix in the CLI commands for Amazon EMR on EKS. For example, aws emr-containers start-job-run. It is the prefix before IAM policy actions for Amazon EMR on EKS. For example,"Action": [ "emr-containers:StartJobRun"]. For more information, see Policy actions for Amazon EMR on EKS. It is the prefix used in Amazon EMR on EKS service endpoints. For example, emr-containers.us-east-2.amazonaws.com. For more information, see Amazon EMR on EKS Service Endpoints.

Amazon Cloud Directory Amazon Cloud Directory is a component of the AWS Directory Service that simplifies the development and management of cloud-scale web, mobile, and IoT applications. This guide describes the Cloud Directory operations that you can call programmatically and includes detailed information on data types and errors. For information about Cloud Directory features, see AWS Directory Service and the Amazon Cloud Directory Developer Guide.

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.

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.