Mock sample for your project: AWS Service Catalog API

AWS CodeStar Connections This AWS CodeStar Connections API Reference provides descriptions and usage examples of the operations and data types for the AWS CodeStar Connections API. You can use the connections API to work with connections and installations. Connections are configurations that you use to connect AWS resources to external code repositories. Each connection is a resource that can be given to services such as CodePipeline to connect to a third-party repository such as Bitbucket. For example, you can add the connection in CodePipeline so that it triggers your pipeline when a code change is made to your third-party code repository. Each connection is named and associated with a unique ARN that is used to reference the connection. When you create a connection, the console initiates a third-party connection handshake. Installations are the apps that are used to conduct this handshake. For example, the installation for the Bitbucket provider type is the Bitbucket app. When you create a connection, you can choose an existing installation or create one. When you want to create a connection to an installed provider type such as GitHub Enterprise Server, you create a host for your connections. You can work with connections by calling: CreateConnection, which creates a uniquely named connection that can be referenced by services such as CodePipeline. DeleteConnection, which deletes the specified connection. GetConnection, which returns information about the connection, including the connection status. ListConnections, which lists the connections associated with your account. You can work with hosts by calling: CreateHost, which creates a host that represents the infrastructure where your provider is installed. DeleteHost, which deletes the specified host. GetHost, which returns information about the host, including the setup status. ListHosts, which lists the hosts associated with your account. You can work with tags in AWS CodeStar Connections by calling the following: ListTagsForResource, which gets information about AWS tags for a specified Amazon Resource Name (ARN) in AWS CodeStar Connections. TagResource, which adds or updates tags for a resource in AWS CodeStar Connections. UntagResource, which removes tags for a resource in AWS CodeStar Connections. For information about how to use AWS CodeStar Connections, see the Developer Tools User Guide.

Amazon Pinpoint Email Service Welcome to the Amazon Pinpoint Email API Reference. This guide provides information about the Amazon Pinpoint Email API (version 1.0), including supported operations, data types, parameters, and schemas. Amazon Pinpoint is an AWS service that you can use to engage with your customers across multiple messaging channels. You can use Amazon Pinpoint to send email, SMS text messages, voice messages, and push notifications. The Amazon Pinpoint Email API provides programmatic access to options that are unique to the email channel and supplement the options provided by the Amazon Pinpoint API. If you're new to Amazon Pinpoint, you might find it helpful to also review the Amazon Pinpoint Developer Guide. The Amazon Pinpoint Developer Guide provides tutorials, code samples, and procedures that demonstrate how to use Amazon Pinpoint features programmatically and how to integrate Amazon Pinpoint functionality into mobile apps and other types of applications. The guide also provides information about key topics such as Amazon Pinpoint integration with other AWS services and the limits that apply to using the service. The Amazon Pinpoint Email API is available in several AWS Regions and it provides an endpoint for each of these Regions. For a list of all the Regions and endpoints where the API is currently available, see AWS Service Endpoints in the Amazon Web Services General Reference. To learn more about AWS Regions, see Managing AWS Regions in the Amazon Web Services General Reference. In each Region, AWS maintains multiple Availability Zones. These Availability Zones are physically isolated from each other, but are united by private, low-latency, high-throughput, and highly redundant network connections. These Availability Zones enable us to provide very high levels of availability and redundancy, while also minimizing latency. To learn more about the number of Availability Zones that are available in each Region, see AWS Global Infrastructure.

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.

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.

Amazon CloudSearch Configuration Service You use the Amazon CloudSearch configuration service to create, configure, and manage search domains. Configuration service requests are submitted using the AWS Query protocol. AWS Query requests are HTTP or HTTPS requests submitted via HTTP GET or POST with a query parameter named Action. The endpoint for configuration service requests is region-specific: cloudsearch. region.amazonaws.com. For example, cloudsearch.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints.

Amazon Kinesis Analytics Overview This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation. This is the Amazon Kinesis Analytics v1 API Reference. The Amazon Kinesis Analytics Developer Guide provides additional information.

Suite of geospatial services including Maps, Places, Routes, Tracking, and Geofencing

Amazon Kinesis Data Streams Service API Reference Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.

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.

Definition of the public APIs exposed by Amazon Machine Learning

Amazon Kendra is a service for indexing large document sets.

Catalog API actions allow you to manage your entities through list, describe, and update capabilities. An entity can be a product or an offer on AWS Marketplace. You can automate your entity update process by integrating the AWS Marketplace Catalog API with your AWS Marketplace product build or deployment pipelines. You can also create your own applications on top of the Catalog API to manage your products on AWS Marketplace.

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.

The REST API specification for Ably.

You use the AmazonCloudSearch2013 API to upload documents to a search domain and search those documents. The endpoints for submitting UploadDocuments, Search, and Suggest requests are domain-specific. To get the endpoints for your domain, use the Amazon CloudSearch configuration service DescribeDomains action. The domain endpoints are also displayed on the domain dashboard in the Amazon CloudSearch console. You submit suggest requests to the search endpoint. For more information, see the Amazon CloudSearch Developer Guide.

Storage system operation endpoints and objects.

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.

Elastic Load Balancing A load balancer can distribute incoming traffic across your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered instances and ensures that it routes traffic only to healthy instances. You configure your load balancer to accept incoming traffic by specifying one or more listeners, which are configured with a protocol and port number for connections from clients to the load balancer and a protocol and port number for connections from the load balancer to the instances. Elastic Load Balancing supports three types of load balancers: Application Load Balancers, Network Load Balancers, and Classic Load Balancers. You can select a load balancer based on your application needs. For more information, see the Elastic Load Balancing User Guide. This reference covers the 2012-06-01 API, which supports Classic Load Balancers. The 2015-12-01 API supports Application Load Balancers and Network Load Balancers. To get started, create a load balancer with one or more listeners using CreateLoadBalancer. Register your instances with the load balancer using RegisterInstancesWithLoadBalancer. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds with a 200 OK response code.

Use the Control API to manage your applications, namespaces, keys, queues, rules, and more.
Detailed information on using this API can be found in the Ably developer documentation.
Control API is currently in Beta.

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

Amazon Athena is an interactive query service that lets you use standard SQL to analyze data directly in Amazon S3. You can point Athena at your data in Amazon S3 and run ad-hoc queries and get results in seconds. Athena is serverless, so there is no infrastructure to set up or manage. You pay only for the queries you run. Athena scales automatically—executing queries in parallel—so results are fast, even with large datasets and complex queries. For more information, see What is Amazon Athena in the Amazon Athena User Guide. If you connect to Athena using the JDBC driver, use version 1.1.0 of the driver or later with the Amazon Athena API. Earlier version drivers do not support the API. For more information and to download the driver, see Accessing Amazon Athena with JDBC. For code samples using the Amazon Web Services SDK for Java, see Examples and Code Samples in the Amazon Athena User Guide.

AWS Single Sign-On Portal is a web service that makes it easy for you to assign user access to AWS SSO resources such as the user portal. Users can get AWS account applications and roles assigned to them and get federated into the application. For general information about AWS SSO, see What is AWS Single Sign-On? in the AWS SSO User Guide. This API reference guide describes the AWS SSO Portal operations that you can call programatically and includes detailed information on data types and errors. AWS provides SDKs that consist of libraries and sample code for various programming languages and platforms, such as Java, Ruby, .Net, iOS, or Android. The SDKs provide a convenient way to create programmatic access to AWS SSO and other AWS services. For more information about the AWS SDKs, including how to download and install them, see Tools for Amazon Web Services.