Mock sample for your project: Amazon CloudWatch API

Amazon Route 53 is a highly available and scalable Domain Name System (DNS) web service.

Systems Manager Incident Manager is an incident management console designed to help users mitigate and recover from incidents affecting their Amazon Web Services-hosted applications. An incident is any unplanned interruption or reduction in quality of services. Incident Manager increases incident resolution by notifying responders of impact, highlighting relevant troubleshooting data, and providing collaboration tools to get services back up and running. To achieve the primary goal of reducing the time-to-resolution of critical incidents, Incident Manager automates response plans and enables responder team escalation.

Amazon Timestream is a fast, scalable, fully managed time series database service that makes it easy to store and analyze trillions of time series data points per day. With Timestream, you can easily store and analyze IoT sensor data to derive insights from your IoT applications. You can analyze industrial telemetry to streamline equipment management and maintenance. You can also store and analyze log data and metrics to improve the performance and availability of your applications. Timestream is built from the ground up to effectively ingest, process, and store time series data. It organizes data to optimize query processing. It automatically scales based on the volume of data ingested and on the query volume to ensure you receive optimal performance while inserting and querying data. As your data grows over time, Timestream’s adaptive query processing engine spans across storage tiers to provide fast analysis while reducing costs.

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, .

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.

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

Provides translation between one source language and another of the same set of languages.

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.

Cloud9 Cloud9 is a collection of tools that you can use to code, build, run, test, debug, and release software in the cloud. For more information about Cloud9, see the Cloud9 User Guide. Cloud9 supports these operations: CreateEnvironmentEC2 : Creates an Cloud9 development environment, launches an Amazon EC2 instance, and then connects from the instance to the environment. CreateEnvironmentMembership : Adds an environment member to an environment. DeleteEnvironment : Deletes an environment. If an Amazon EC2 instance is connected to the environment, also terminates the instance. DeleteEnvironmentMembership : Deletes an environment member from an environment. DescribeEnvironmentMemberships : Gets information about environment members for an environment. DescribeEnvironments : Gets information about environments. DescribeEnvironmentStatus : Gets status information for an environment. ListEnvironments : Gets a list of environment identifiers. ListTagsForResource : Gets the tags for an environment. TagResource : Adds tags to an environment. UntagResource : Removes tags from an environment. UpdateEnvironment : Changes the settings of an existing environment. UpdateEnvironmentMembership : Changes the settings of an existing environment member for an environment.

Amazon WorkSpaces Service Amazon WorkSpaces enables you to provision virtual, cloud-based Microsoft Windows and Amazon Linux desktops for your users.

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.

Amazon Web Services X-Ray provides APIs for managing debug traces and retrieving service maps and other data created by processing those traces.

Allows extension of ARM control plane with custom resource providers.

To manage and control access to your resources, you can define customized policies and assign them at a scope.

Creates an Azure Data Lake Store account management client.

REST API for Azure VirtualWAN As a Service.

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.

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.

PowerBI Dedicated Web API provides a RESTful set of web services that enables users to create, retrieve, update, and delete Power BI dedicated capacities

API for using the Azure IoT Hub Device Provisioning Service features.

Resource Groups Tagging API

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.

Amazon S3 Glacier (Glacier) is a storage solution for "cold data." Glacier is an extremely low-cost storage service that provides secure, durable, and easy-to-use storage for data backup and archival. With Glacier, customers can store their data cost effectively for months, years, or decades. Glacier also enables customers to offload the administrative burdens of operating and scaling storage to AWS, so they don't have to worry about capacity planning, hardware provisioning, data replication, hardware failure and recovery, or time-consuming hardware migrations. Glacier is a great storage choice when low storage cost is paramount and your data is rarely retrieved. If your application requires fast or frequent access to your data, consider using Amazon S3. For more information, see Amazon Simple Storage Service (Amazon S3). You can store any kind of data in any format. There is no maximum limit on the total amount of data you can store in Glacier. If you are a first-time user of Glacier, we recommend that you begin by reading the following sections in the Amazon S3 Glacier Developer Guide : What is Amazon S3 Glacier - This section of the Developer Guide describes the underlying data model, the operations it supports, and the AWS SDKs that you can use to interact with the service. Getting Started with Amazon S3 Glacier - The Getting Started section walks you through the process of creating a vault, uploading archives, creating jobs to download archives, retrieving the job output, and deleting archives.

Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide. Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).