Mock sample for your project: Amazon Simple Workflow Service API

Welcome to the Amazon SQS API Reference. Amazon SQS is a reliable, highly-scalable hosted queue for storing messages as they travel between applications or microservices. Amazon SQS moves data between distributed application components and helps you decouple these components. For information on the permissions you need to use this API, see Identity and access management in the Amazon SQS Developer Guide. You can use Amazon Web Services SDKs to access Amazon SQS using your favorite programming language. The SDKs perform tasks such as the following automatically: Cryptographically sign your service requests Retry requests Handle error responses Additional information Amazon SQS Product Page Amazon SQS Developer Guide Making API Requests Amazon SQS Message Attributes Amazon SQS Dead-Letter Queues Amazon SQS in the Command Line Interface Amazon Web Services General Reference Regions and Endpoints

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.

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.

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 SES API v2 Welcome to the Amazon SES API v2 Reference. This guide provides information about the Amazon SES API v2, including supported operations, data types, parameters, and schemas. Amazon SES is an AWS service that you can use to send email messages to your customers. If you're new to Amazon SES API v2, you might find it helpful to also review the Amazon Simple Email Service Developer Guide. The Amazon SES Developer Guide provides information and code samples that demonstrate how to use Amazon SES API v2 features programmatically. The Amazon SES API v2 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.

The AWS Budgets API enables you to use AWS Budgets to plan your service usage, service costs, and instance reservations. The API reference provides descriptions, syntax, and usage examples for each of the actions and data types for AWS Budgets. Budgets provide you with a way to see the following information: How close your plan is to your budgeted amount or to the free tier limits Your usage-to-date, including how much you've used of your Reserved Instances (RIs) Your current estimated charges from AWS, and how much your predicted usage will accrue in charges by the end of the month How much of your budget has been used AWS updates your budget status several times a day. Budgets track your unblended costs, subscriptions, refunds, and RIs. You can create the following types of budgets: Cost budgets - Plan how much you want to spend on a service. Usage budgets - Plan how much you want to use one or more services. RI utilization budgets - Define a utilization threshold, and receive alerts when your RI usage falls below that threshold. This lets you see if your RIs are unused or under-utilized. RI coverage budgets - Define a coverage threshold, and receive alerts when the number of your instance hours that are covered by RIs fall below that threshold. This lets you see how much of your instance usage is covered by a reservation. Service Endpoint The AWS Budgets API provides the following endpoint: https://budgets.amazonaws.com For information about costs that are associated with the AWS Budgets API, see AWS Cost Management Pricing.

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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 DynamoDB Amazon DynamoDB Streams provides API actions for accessing streams and processing stream records. To learn more about application development with Streams, see Capturing Table Activity with DynamoDB Streams in the Amazon DynamoDB Developer Guide.

Recovery Control Configuration API Reference for Amazon Route 53 Application Recovery Controller

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.

Amazon Web Services Single Sign On (SSO) is a cloud SSO service that makes it easy to centrally manage SSO access to multiple Amazon Web Services accounts and business applications. This guide provides information on SSO operations which could be used for access management of Amazon Web Services accounts. For information about Amazon Web Services SSO features, see the Amazon Web Services Single Sign-On User Guide. Many operations in the SSO APIs rely on identifiers for users and groups, known as principals. For more information about how to work with principals and principal IDs in Amazon Web Services SSO, see the Amazon Web Services SSO Identity Store API Reference.

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.

AWS AppConfig Use AWS AppConfig, a capability of AWS Systems Manager, to create, manage, and quickly deploy application configurations. AppConfig supports controlled deployments to applications of any size and includes built-in validation checks and monitoring. You can use AppConfig with applications hosted on Amazon EC2 instances, AWS Lambda, containers, mobile applications, or IoT devices. To prevent errors when deploying application configurations, especially for production systems where a simple typo could cause an unexpected outage, AppConfig includes validators. A validator provides a syntactic or semantic check to ensure that the configuration you want to deploy works as intended. To validate your application configuration data, you provide a schema or a Lambda function that runs against the configuration. The configuration deployment or update can only proceed when the configuration data is valid. During a configuration deployment, AppConfig monitors the application to ensure that the deployment is successful. If the system encounters an error, AppConfig rolls back the change to minimize impact for your application users. You can configure a deployment strategy for each application or environment that includes deployment criteria, including velocity, bake time, and alarms to monitor. Similar to error monitoring, if a deployment triggers an alarm, AppConfig automatically rolls back to the previous version. AppConfig supports multiple use cases. Here are some examples. Application tuning : Use AppConfig to carefully introduce changes to your application that can only be tested with production traffic. Feature toggle : Use AppConfig to turn on new features that require a timely deployment, such as a product launch or announcement. Allow list : Use AppConfig to allow premium subscribers to access paid content. Operational issues : Use AppConfig to reduce stress on your application when a dependency or other external factor impacts the system. This reference is intended to be used with the AWS AppConfig User Guide.

Amazon Web Services Certificate Manager You can use Amazon Web Services Certificate Manager (ACM) to manage SSL/TLS certificates for your Amazon Web Services-based websites and applications. For more information about using ACM, see the Amazon Web Services Certificate Manager User Guide.

This section provides documentation for the Amazon CodeGuru Profiler API operations. Amazon CodeGuru Profiler collects runtime performance data from your live applications, and provides recommendations that can help you fine-tune your application performance. Using machine learning algorithms, CodeGuru Profiler can help you find your most expensive lines of code and suggest ways you can improve efficiency and remove CPU bottlenecks. Amazon CodeGuru Profiler provides different visualizations of profiling data to help you identify what code is running on the CPU, see how much time is consumed, and suggest ways to reduce CPU utilization. Amazon CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python. While CodeGuru Profiler supports both visualizations and recommendations for applications written in Java, it can also generate visualizations and a subset of recommendations for applications written in other JVM languages and Python. For more information, see What is Amazon CodeGuru Profiler in the Amazon CodeGuru Profiler User Guide.

App Mesh is a service mesh based on the Envoy proxy that makes it easy to monitor and control microservices. App Mesh standardizes how your microservices communicate, giving you end-to-end visibility and helping to ensure high availability for your applications. App Mesh gives you consistent visibility and network traffic controls for every microservice in an application. You can use App Mesh with Amazon Web Services Fargate, Amazon ECS, Amazon EKS, Kubernetes on Amazon Web Services, and Amazon EC2. App Mesh supports microservice applications that use service discovery naming for their components. For more information about service discovery on Amazon ECS, see Service Discovery in the Amazon Elastic Container Service Developer Guide. Kubernetes kube-dns and coredns are supported. For more information, see DNS for Services and Pods in the Kubernetes documentation.

The FinSpace APIs let you take actions inside the FinSpace environment.

Amazon Mobile Analytics is a service for collecting, visualizing, and understanding app usage data at scale.

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.

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 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 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.