Mock sample for your project: AWS Signer API

Amazon Redshift Overview This is an interface reference for Amazon Redshift. It contains documentation for one of the programming or command line interfaces you can use to manage Amazon Redshift clusters. Note that Amazon Redshift is asynchronous, which means that some interfaces may require techniques, such as polling or asynchronous callback handlers, to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a change is applied immediately, on the next instance reboot, or during the next maintenance window. For a summary of the Amazon Redshift cluster management interfaces, go to Using the Amazon Redshift Management Interfaces. Amazon Redshift manages all the work of setting up, operating, and scaling a data warehouse: provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine. You can focus on using your data to acquire new insights for your business and customers. If you are a first-time user of Amazon Redshift, we recommend that you begin by reading the Amazon Redshift Getting Started Guide. If you are a database developer, the Amazon Redshift Database Developer Guide explains how to design, build, query, and maintain the databases that make up your data warehouse.

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.

With Service Quotas, you can view and manage your quotas easily as your AWS workloads grow. Quotas, also referred to as limits, are the maximum number of resources that you can create in your AWS account. For more information, see the Service Quotas User Guide.

Amazon EventBridge Schema Registry

AWS Support The AWS Support API Reference is intended for programmers who need detailed information about the AWS Support operations and data types. You can use the API to manage your support cases programmatically. The AWS Support API uses HTTP methods that return results in JSON format. You must have a Business or Enterprise Support plan to use the AWS Support API. If you call the AWS Support API from an account that does not have a Business or Enterprise Support plan, the SubscriptionRequiredException error message appears. For information about changing your support plan, see AWS Support. The AWS Support service also exposes a set of AWS Trusted Advisor features. You can retrieve a list of checks and their descriptions, get check results, specify checks to refresh, and get the refresh status of checks. The following list describes the AWS Support case management operations: Service names, issue categories, and available severity levels - The DescribeServices and DescribeSeverityLevels operations return AWS service names, service codes, service categories, and problem severity levels. You use these values when you call the CreateCase operation. Case creation, case details, and case resolution - The CreateCase, DescribeCases, DescribeAttachment, and ResolveCase operations create AWS Support cases, retrieve information about cases, and resolve cases. Case communication - The DescribeCommunications, AddCommunicationToCase, and AddAttachmentsToSet operations retrieve and add communications and attachments to AWS Support cases. The following list describes the operations available from the AWS Support service for Trusted Advisor: DescribeTrustedAdvisorChecks returns the list of checks that run against your AWS resources. Using the checkId for a specific check returned by DescribeTrustedAdvisorChecks, you can call DescribeTrustedAdvisorCheckResult to obtain the results for the check that you specified. DescribeTrustedAdvisorCheckSummaries returns summarized results for one or more Trusted Advisor checks. RefreshTrustedAdvisorCheck requests that Trusted Advisor rerun a specified check. DescribeTrustedAdvisorCheckRefreshStatuses reports the refresh status of one or more checks. For authentication of requests, AWS Support uses Signature Version 4 Signing Process. See About the AWS Support API in the AWS Support User Guide for information about how to use this service to create and manage your support cases, and how to call Trusted Advisor for results of checks on your resources.

Amazon Mechanical Turk API Reference

Amazon RDS Data Service Amazon RDS provides an HTTP endpoint to run SQL statements on an Amazon Aurora Serverless DB cluster. To run these statements, you work with the Data Service API. For more information about the Data Service API, see Using the Data API for Aurora Serverless in the Amazon Aurora User Guide.

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.

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.

AWS Resource Groups AWS Resource Groups lets you organize AWS resources such as Amazon EC2 instances, Amazon Relational Database Service databases, and Amazon S3 buckets into groups using criteria that you define as tags. A resource group is a collection of resources that match the resource types specified in a query, and share one or more tags or portions of tags. You can create a group of resources based on their roles in your cloud infrastructure, lifecycle stages, regions, application layers, or virtually any criteria. Resource Groups enable you to automate management tasks, such as those in AWS Systems Manager Automation documents, on tag-related resources in AWS Systems Manager. Groups of tagged resources also let you quickly view a custom console in AWS Systems Manager that shows AWS Config compliance and other monitoring data about member resources. To create a resource group, build a resource query, and specify tags that identify the criteria that members of the group have in common. Tags are key-value pairs. For more information about Resource Groups, see the AWS Resource Groups User Guide. AWS Resource Groups uses a REST-compliant API that you can use to perform the following types of operations. Create, Read, Update, and Delete (CRUD) operations on resource groups and resource query entities Applying, editing, and removing tags from resource groups Resolving resource group member ARNs so they can be returned as search results Getting data about resources that are members of a group Searching AWS resources based on a resource query

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

AWS Mobile Service provides mobile app and website developers with capabilities required to configure AWS resources and bootstrap their developer desktop projects with the necessary SDKs, constants, tools and samples to make use of those resources.

Amplify enables developers to develop and deploy cloud-powered mobile and web apps. The Amplify Console provides a continuous delivery and hosting service for web applications. For more information, see the Amplify Console User Guide. The Amplify Framework is a comprehensive set of SDKs, libraries, tools, and documentation for client app development. For more information, see the Amplify Framework.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.

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.

Amazon Kendra is a service for indexing large document sets.

AWS Import/Export Service AWS Import/Export accelerates transferring large amounts of data between the AWS cloud and portable storage devices that you mail to us. AWS Import/Export transfers data directly onto and off of your storage devices using Amazon's high-speed internal network and bypassing the Internet. For large data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.

Amazon Connect Customer Profiles Welcome to the Amazon Connect Customer Profiles API Reference. This guide provides information about the Amazon Connect Customer Profiles API, including supported operations, data types, parameters, and schemas. Amazon Connect Customer Profiles is a unified customer profile for your contact center that has pre-built connectors powered by AppFlow that make it easy to combine customer information from third party applications, such as Salesforce (CRM), ServiceNow (ITSM), and your enterprise resource planning (ERP), with contact history from your Amazon Connect contact center. If you're new to Amazon Connect , you might find it helpful to also review the Amazon Connect Administrator Guide.

You can use the Cost Explorer API to programmatically query your cost and usage data. You can query for aggregated data such as total monthly costs or total daily usage. You can also query for granular data. This might include the number of daily write operations for Amazon DynamoDB database tables in your production environment. Service Endpoint The Cost Explorer API provides the following endpoint: https://ce.us-east-1.amazonaws.com For information about the costs that are associated with the Cost Explorer API, see Amazon Web Services Cost Management Pricing.

AWS IoT Events monitors your equipment or device fleets for failures or changes in operation, and triggers actions when such events occur. You can use AWS IoT Events Data API commands to send inputs to detectors, list detectors, and view or update a detector's status. For more information, see What is AWS IoT Events? in the AWS IoT Events Developer Guide.