Mock sample for your project: Amazon WorkMail API

AWS Amplify Admin API

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.

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.

Compute Optimizer is a service that analyzes the configuration and utilization metrics of your Amazon Web Services compute resources, such as Amazon EC2 instances, Amazon EC2 Auto Scaling groups, Lambda functions, and Amazon EBS volumes. It reports whether your resources are optimal, and generates optimization recommendations to reduce the cost and improve the performance of your workloads. Compute Optimizer also provides recent utilization metric data, in addition to projected utilization metric data for the recommendations, which you can use to evaluate which recommendation provides the best price-performance trade-off. The analysis of your usage patterns can help you decide when to move or resize your running resources, and still meet your performance and capacity requirements. For more information about Compute Optimizer, including the required permissions to use the service, see the Compute Optimizer User Guide.

This is the ACM Private CA API Reference. It provides descriptions, syntax, and usage examples for each of the actions and data types involved in creating and managing private certificate authorities (CA) for your organization. The documentation for each action shows the Query API request parameters and the XML response. Alternatively, you can use one of the AWS SDKs to access an API that's tailored to the programming language or platform that you're using. For more information, see AWS SDKs. Each ACM Private CA API operation has a quota that determines the number of times the operation can be called per second. ACM Private CA throttles API requests at different rates depending on the operation. Throttling means that ACM Private CA rejects an otherwise valid request because the request exceeds the operation's quota for the number of requests per second. When a request is throttled, ACM Private CA returns a ThrottlingException error. ACM Private CA does not guarantee a minimum request rate for APIs. To see an up-to-date list of your ACM Private CA quotas, or to request a quota increase, log into your AWS account and visit the Service Quotas console.

Welcome to the AWS Device Farm API documentation, which contains APIs for: Testing on desktop browsers Device Farm makes it possible for you to test your web applications on desktop browsers using Selenium. The APIs for desktop browser testing contain TestGrid in their names. For more information, see Testing Web Applications on Selenium with Device Farm. Testing on real mobile devices Device Farm makes it possible for you to test apps on physical phones, tablets, and other devices in the cloud. For more information, see the Device Farm Developer Guide.

CodeBuild CodeBuild is a fully managed build service in the cloud. CodeBuild compiles your source code, runs unit tests, and produces artifacts that are ready to deploy. CodeBuild eliminates the need to provision, manage, and scale your own build servers. It provides prepackaged build environments for the most popular programming languages and build tools, such as Apache Maven, Gradle, and more. You can also fully customize build environments in CodeBuild to use your own build tools. CodeBuild scales automatically to meet peak build requests. You pay only for the build time you consume. For more information about CodeBuild, see the CodeBuild User Guide.

AppSync provides API actions for creating and interacting with data sources using GraphQL from your application.

AWS IoT Wireless API documentation

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

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 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.

Savings Plans are a pricing model that offer significant savings on AWS usage (for example, on Amazon EC2 instances). You commit to a consistent amount of usage, in USD per hour, for a term of 1 or 3 years, and receive a lower price for that usage. For more information, see the AWS Savings Plans User Guide.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

MemoryDB for Redis is a fully managed, Redis-compatible, in-memory database that delivers ultra-fast performance and Multi-AZ durability for modern applications built using microservices architectures. MemoryDB stores the entire database in-memory, enabling low latency and high throughput data access. It is compatible with Redis, a popular open source data store, enabling you to leverage Redis’ flexible and friendly data structures, APIs, and commands.

The User Subscription Management Client.

The OpenALPR CarCheck API allows you to send images to the cloud for processing.
The image will be analyzed for license plates and vehicle make/models. The results
are returned in JSON format

Pinpoint SMS and Voice Messaging public facing APIs

A Storage Cache provides scalable caching service for NAS clients, serving data from either NFSv3 or Blob at-rest storage (referred to as "Storage Targets"). These operations allow you to manage Caches.

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.

Use these REST APIs for performing operations on Diagnostic entity associated with your Azure API Management deployment. Diagnostics are used to log requests/responses in the APIM proxy.