Mock sample for your project: Amazon WorkMail API

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.

Amazon EC2 Auto Scaling Amazon EC2 Auto Scaling is designed to automatically launch or terminate EC2 instances based on user-defined scaling policies, scheduled actions, and health checks. For more information about Amazon EC2 Auto Scaling, see the Amazon EC2 Auto Scaling User Guide. For information about granting IAM users required permissions for calls to Amazon EC2 Auto Scaling, see Granting IAM users required permissions for Amazon EC2 Auto Scaling resources in the Amazon EC2 Auto Scaling API Reference.

Shield Advanced This is the Shield Advanced API Reference. This guide is for developers who need detailed information about the Shield Advanced API actions, data types, and errors. For detailed information about WAF and Shield Advanced features and an overview of how to use the WAF and Shield Advanced APIs, see the WAF and Shield Developer Guide.

The AWS Cost and Usage Report API enables you to programmatically create, query, and delete AWS Cost and Usage report definitions. AWS Cost and Usage reports track the monthly AWS costs and usage associated with your AWS account. The report contains line items for each unique combination of AWS product, usage type, and operation that your AWS account uses. You can configure the AWS Cost and Usage report to show only the data that you want, using the AWS Cost and Usage API. Service Endpoint The AWS Cost and Usage Report API provides the following endpoint: cur.us-east-1.amazonaws.com

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

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

Amazon Kinesis Data Firehose API Reference Amazon Kinesis Data Firehose is a fully managed service that delivers real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Elasticsearch Service (Amazon ES), Amazon Redshift, and Splunk.

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, .

This section provides documentation for the AWS RoboMaker API operations.

Amazon Route 53 is a highly available and scalable Domain Name System (DNS) web service.

Using the Amazon Cognito User Pools API, you can create a user pool to manage directories and users. You can authenticate a user to obtain tokens related to user identity and access policies. This API reference provides information about user pools in Amazon Cognito User Pools. For more information, see the Amazon Cognito Documentation.

Amazon Simple Workflow Service The Amazon Simple Workflow Service (Amazon SWF) makes it easy to build applications that use Amazon's cloud to coordinate work across distributed components. In Amazon SWF, a task represents a logical unit of work that is performed by a component of your workflow. Coordinating tasks in a workflow involves managing intertask dependencies, scheduling, and concurrency in accordance with the logical flow of the application. Amazon SWF gives you full control over implementing tasks and coordinating them without worrying about underlying complexities such as tracking their progress and maintaining their state. This documentation serves as reference only. For a broader overview of the Amazon SWF programming model, see the Amazon SWF Developer Guide .

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.

API to access NetBox

Transit Gateway Network Manager (Network Manager) enables you to create a global network, in which you can monitor your AWS and on-premises networks that are built around transit gateways. The Network Manager APIs are supported in the US West (Oregon) Region only. You must specify the us-west-2 Region in all requests made to Network Manager.

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 control plane for Amazon QLDB

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.

The Azure management API provides a RESTful set of web services that interact with Azure Key Vault.

This is the AWS Proton Service API Reference. It provides descriptions, syntax and usage examples for each of the actions and data types for the AWS Proton service. The documentation for each action shows the Query API request parameters and the XML response. Alternatively, you can use the AWS CLI to access an API. For more information, see the AWS Command Line Interface User Guide. The AWS Proton service is a two-pronged automation framework. Administrators create service templates to provide standardized infrastructure and deployment tooling for serverless and container based applications. Developers, in turn, select from the available service templates to automate their application or service deployments. Because administrators define the infrastructure and tooling that AWS Proton deploys and manages, they need permissions to use all of the listed API operations. When developers select a specific infrastructure and tooling set, AWS Proton deploys their applications. To monitor their applications that are running on AWS Proton, developers need permissions to the service create, list, update and delete API operations and the service instance list and update API operations. To learn more about AWS Proton administration, see the AWS Proton Administrator Guide. To learn more about deploying serverless and containerized applications on AWS Proton, see the AWS Proton User Guide. Ensuring Idempotency When you make a mutating API request, the request typically returns a result before the asynchronous workflows of the operation are complete. Operations might also time out or encounter other server issues before they're complete, even if the request already returned a result. This might make it difficult to determine whether the request succeeded. Moreover, you might need to retry the request multiple times to ensure that the operation completes successfully. However, if the original request and the subsequent retries are successful, the operation occurs multiple times. This means that you might create more resources than you intended. Idempotency ensures that an API request action completes no more than one time. With an idempotent request, if the original request action completes successfully, any subsequent retries complete successfully without performing any further actions. However, the result might contain updated information, such as the current creation status. The following lists of APIs are grouped according to methods that ensure idempotency. Idempotent create APIs with a client token The API actions in this list support idempotency with the use of a client token. The corresponding AWS CLI commands also support idempotency using a client token. A client token is a unique, case-sensitive string of up to 64 ASCII characters. To make an idempotent API request using one of these actions, specify a client token in the request. We recommend that you don't reuse the same client token for other API requests. If you don’t provide a client token for these APIs, a default client token is automatically provided by SDKs. Given a request action that has succeeded: If you retry the request using the same client token and the same parameters, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If you retry the request using the same client token, but one or more of the parameters are different, the retry throws a ValidationException with an IdempotentParameterMismatch error. Client tokens expire eight hours after a request is made. If you retry the request with the expired token, a new resource is created. If the original resource is deleted and you retry the request, a new resource is created. Idempotent create APIs with a client token: CreateEnvironmentTemplateVersion CreateServiceTemplateVersion CreateEnvironmentAccountConnection Idempotent create APIs Given a request action that has succeeded: If you retry the request with an API from this group, and the original resource hasn't been modified, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If the original resource has been modified, the retry throws a ConflictException. If you retry with different input parameters, the retry throws a ValidationException with an IdempotentParameterMismatch error. Idempotent create APIs: CreateEnvironmentTemplate CreateServiceTemplate CreateEnvironment CreateService Idempotent delete APIs Given a request action that has succeeded: When you retry the request with an API from this group and the resource was deleted, its metadata is returned in the response. If you retry and the resource doesn't exist, the response is empty. In both cases, the retry succeeds. Idempotent delete APIs: DeleteEnvironmentTemplate DeleteEnvironmentTemplateVersion DeleteServiceTemplate DeleteServiceTemplateVersion DeleteEnvironmentAccountConnection Asynchronous idempotent delete APIs Given a request action that has succeeded: If you retry the request with an API from this group, if the original request delete operation status is DELETEINPROGRESS, the retry returns the resource detail data in the response without performing any further actions. If the original request delete operation is complete, a retry returns an empty response. Asynchronous idempotent delete APIs: DeleteEnvironment DeleteService

The Amazon API Gateway Management API allows you to directly manage runtime aspects of your deployed APIs. To use it, you must explicitly set the SDK's endpoint to point to the endpoint of your deployed API. The endpoint will be of the form https://{api-id}.execute-api.{region}.amazonaws.com/{stage}, or will be the endpoint corresponding to your API's custom domain and base path, if applicable.