Mock sample for your project: Amazon Cognito Identity Provider API

Glue Defines the public endpoint for the Glue service.

AWS IoT Core Device Advisor is a cloud-based, fully managed test capability for validating IoT devices during device software development. Device Advisor provides pre-built tests that you can use to validate IoT devices for reliable and secure connectivity with AWS IoT Core before deploying devices to production. By using Device Advisor, you can confirm that your devices can connect to AWS IoT Core, follow security best practices and, if applicable, receive software updates from IoT Device Management. You can also download signed qualification reports to submit to the AWS Partner Network to get your device qualified for the AWS Partner Device Catalog without the need to send your device in and wait for it to be tested.

AWS IoT Greengrass seamlessly extends AWS onto physical devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. AWS IoT Greengrass ensures your devices can respond quickly to local events and operate with intermittent connectivity. AWS IoT Greengrass minimizes the cost of transmitting data to the cloud by allowing you to author AWS Lambda functions that execute locally.

The Amazon Chime SDK Identity APIs in this section allow software developers to create and manage unique instances of their messaging applications. These APIs provide the overarching framework for creating and sending messages. For more information about the identity APIs, refer to Amazon Chime SDK identity.

AWS IoT Things Graph AWS IoT Things Graph provides an integrated set of tools that enable developers to connect devices and services that use different standards, such as units of measure and communication protocols. AWS IoT Things Graph makes it possible to build IoT applications with little to no code by connecting devices and services and defining how they interact at an abstract level. For more information about how AWS IoT Things Graph works, see the User Guide.

When you create a VPC using Amazon VPC, you automatically get DNS resolution within the VPC from Route 53 Resolver. By default, Resolver answers DNS queries for VPC domain names such as domain names for EC2 instances or Elastic Load Balancing load balancers. Resolver performs recursive lookups against public name servers for all other domain names. You can also configure DNS resolution between your VPC and your network over a Direct Connect or VPN connection: Forward DNS queries from resolvers on your network to Route 53 Resolver DNS resolvers on your network can forward DNS queries to Resolver in a specified VPC. This allows your DNS resolvers to easily resolve domain names for Amazon Web Services resources such as EC2 instances or records in a Route 53 private hosted zone. For more information, see How DNS Resolvers on Your Network Forward DNS Queries to Route 53 Resolver in the Amazon Route 53 Developer Guide. Conditionally forward queries from a VPC to resolvers on your network You can configure Resolver to forward queries that it receives from EC2 instances in your VPCs to DNS resolvers on your network. To forward selected queries, you create Resolver rules that specify the domain names for the DNS queries that you want to forward (such as example.com), and the IP addresses of the DNS resolvers on your network that you want to forward the queries to. If a query matches multiple rules (example.com, acme.example.com), Resolver chooses the rule with the most specific match (acme.example.com) and forwards the query to the IP addresses that you specified in that rule. For more information, see How Route 53 Resolver Forwards DNS Queries from Your VPCs to Your Network in the Amazon Route 53 Developer Guide. Like Amazon VPC, Resolver is Regional. In each Region where you have VPCs, you can choose whether to forward queries from your VPCs to your network (outbound queries), from your network to your VPCs (inbound queries), or both.

Amazon Web Services Secrets Manager Amazon Web Services Secrets Manager provides a service to enable you to store, manage, and retrieve, secrets. This guide provides descriptions of the Secrets Manager API. For more information about using this service, see the Amazon Web Services Secrets Manager User Guide. API Version This version of the Secrets Manager API Reference documents the Secrets Manager API version 2017-10-17. As an alternative to using 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 such as Java, Ruby, .NET, iOS, and Android. The SDKs provide a convenient way to create programmatic access to Amazon Web Services Secrets Manager. For example, the SDKs provide cryptographically signing requests, managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including downloading and installing them, see Tools for Amazon Web Services. We recommend you use the Amazon Web Services SDKs to make programmatic API calls to Secrets Manager. However, you also can use the Secrets Manager HTTP Query API to make direct calls to the Secrets Manager web service. To learn more about the Secrets Manager HTTP Query API, see Making Query Requests in the Amazon Web Services Secrets Manager User Guide. Secrets Manager API supports GET and POST requests for all actions, and doesn't require you to use GET for some actions and POST for others. However, GET requests are subject to the limitation size of a URL. Therefore, for operations that require larger sizes, use a POST request. Support and Feedback for Amazon Web Services Secrets Manager We welcome your feedback. Send your comments to [email protected], or post your feedback and questions in the Amazon Web Services Secrets Manager Discussion Forum. For more information about the Amazon Web Services Discussion Forums, see Forums Help. How examples are presented The JSON that Amazon Web Services Secrets Manager expects as your request parameters and the service returns as a response to HTTP query requests contain single, long strings without line breaks or white space formatting. The JSON shown in the examples displays the code formatted with both line breaks and white space to improve readability. When example input parameters can also cause long strings extending beyond the screen, you can insert line breaks to enhance readability. You should always submit the input as a single JSON text string. Logging API Requests Amazon Web Services Secrets Manager supports Amazon Web Services CloudTrail, a service that records Amazon Web Services API calls for your Amazon Web Services account and delivers log files to an Amazon S3 bucket. By using information that's collected by Amazon Web Services CloudTrail, you can determine the requests successfully made to Secrets Manager, who made the request, when it was made, and so on. For more about Amazon Web Services Secrets Manager and support for Amazon Web Services CloudTrail, see Logging Amazon Web Services Secrets Manager Events with Amazon Web Services CloudTrail in the Amazon Web Services Secrets Manager User Guide. To learn more about CloudTrail, including enabling it and find your log files, see the Amazon Web Services CloudTrail User 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 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 Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on Amazon Web Services without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS runs up-to-date versions of the open-source Kubernetes software, so you can use all the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or public clouds. This means that you can easily migrate any standard Kubernetes application to Amazon EKS without any code modification required.

Amazon SimpleDB is a web service providing the core database functions of data indexing and querying in the cloud. By offloading the time and effort associated with building and operating a web-scale database, SimpleDB provides developers the freedom to focus on application development. A traditional, clustered relational database requires a sizable upfront capital outlay, is complex to design, and often requires extensive and repetitive database administration. Amazon SimpleDB is dramatically simpler, requiring no schema, automatically indexing your data and providing a simple API for storage and access. This approach eliminates the administrative burden of data modeling, index maintenance, and performance tuning. Developers gain access to this functionality within Amazon's proven computing environment, are able to scale instantly, and pay only for what they use. Visit http://aws.amazon.com/simpledb/ for more information.

Amazon Route 53 API actions let you register domain names and perform related operations.

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.

This API describe Azure Reservation

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, .

Amazon Neptune Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. This interface reference for Amazon Neptune contains documentation for a programming or command line interface you can use to manage Amazon Neptune. Note that Amazon Neptune 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.

Welcome to the IoT SiteWise API Reference. IoT SiteWise is an Amazon Web Services service that connects Industrial Internet of Things (IIoT) devices to the power of the Amazon Web Services Cloud. For more information, see the IoT SiteWise User Guide. For information about IoT SiteWise quotas, see Quotas in the IoT SiteWise User Guide.

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.

Azure Log Analytics API reference for Query Packs management.

The Admin Subscriptions Management Client.

Application operation results.

Compute operation results.