Mock sample for your project: AWS OpsWorks API

Storage Gateway Service Storage Gateway is the service that connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration between an organization's on-premises IT environment and the Amazon Web Services storage infrastructure. The service enables you to securely upload data to the Cloud for cost effective backup and rapid disaster recovery. Use the following links to get started using the Storage Gateway Service API Reference : Storage Gateway required request headers : Describes the required headers that you must send with every POST request to Storage Gateway. Signing requests : Storage Gateway requires that you authenticate every request you send; this topic describes how sign such a request. Error responses : Provides reference information about Storage Gateway errors. Operations in Storage Gateway : Contains detailed descriptions of all Storage Gateway operations, their request parameters, response elements, possible errors, and examples of requests and responses. Storage Gateway endpoints and quotas : Provides a list of each Region and the endpoints available for use with Storage Gateway. Storage Gateway resource IDs are in uppercase. When you use these resource IDs with the Amazon EC2 API, EC2 expects resource IDs in lowercase. You must change your resource ID to lowercase to use it with the EC2 API. For example, in Storage Gateway the ID for a volume might be vol-AA22BB012345DAF670. When you use this ID with the EC2 API, you must change it to vol-aa22bb012345daf670. Otherwise, the EC2 API might not behave as expected. IDs for Storage Gateway volumes and Amazon EBS snapshots created from gateway volumes are changing to a longer format. Starting in December 2016, all new volumes and snapshots will be created with a 17-character string. Starting in April 2016, you will be able to use these longer IDs so you can test your systems with the new format. For more information, see Longer EC2 and EBS resource IDs. For example, a volume Amazon Resource Name (ARN) with the longer volume ID format looks like the following: arn:aws:storagegateway:us-west-2:111122223333:gateway/sgw-12A3456B/volume/vol-1122AABBCCDDEEFFG. A snapshot ID with the longer ID format looks like the following: snap-78e226633445566ee. For more information, see Announcement: Heads-up – Longer Storage Gateway volume and snapshot IDs coming in 2016.

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.

Amazon API Gateway V2

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

Backup Backup is a unified backup service designed to protect Amazon Web Services services and their associated data. Backup simplifies the creation, migration, restoration, and deletion of backups, while also providing reporting and auditing.

The AWS Single Sign-On (SSO) Identity Store service provides a single place to retrieve all of your identities (users and groups). For more information about AWS, see the AWS Single Sign-On User Guide.

Describes all of the AWS IoT 1-Click device-related API operations for the service.
Also provides sample requests, responses, and errors for the supported web services
protocols.

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 Inspector Amazon Inspector enables you to analyze the behavior of your AWS resources and to identify potential security issues. For more information, see Amazon Inspector User Guide.

AWS CodeDeploy AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances running in your own facility, serverless AWS Lambda functions, or applications in an Amazon ECS service. You can deploy a nearly unlimited variety of application content, such as an updated Lambda function, updated applications in an Amazon ECS service, code, web and configuration files, executables, packages, scripts, multimedia files, and so on. AWS CodeDeploy can deploy application content stored in Amazon S3 buckets, GitHub repositories, or Bitbucket repositories. You do not need to make changes to your existing code before you can use AWS CodeDeploy. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications, without many of the risks associated with error-prone manual deployments. AWS CodeDeploy Components Use the information in this guide to help you work with the following AWS CodeDeploy components: Application : A name that uniquely identifies the application you want to deploy. AWS CodeDeploy uses this name, which functions as a container, to ensure the correct combination of revision, deployment configuration, and deployment group are referenced during a deployment. Deployment group : A set of individual instances, CodeDeploy Lambda deployment configuration settings, or an Amazon ECS service and network details. A Lambda deployment group specifies how to route traffic to a new version of a Lambda function. An Amazon ECS deployment group specifies the service created in Amazon ECS to deploy, a load balancer, and a listener to reroute production traffic to an updated containerized application. An EC2/On-premises deployment group contains individually tagged instances, Amazon EC2 instances in Amazon EC2 Auto Scaling groups, or both. All deployment groups can specify optional trigger, alarm, and rollback settings. Deployment configuration : A set of deployment rules and deployment success and failure conditions used by AWS CodeDeploy during a deployment. Deployment : The process and the components used when updating a Lambda function, a containerized application in an Amazon ECS service, or of installing content on one or more instances. Application revisions : For an AWS Lambda deployment, this is an AppSpec file that specifies the Lambda function to be updated and one or more functions to validate deployment lifecycle events. For an Amazon ECS deployment, this is an AppSpec file that specifies the Amazon ECS task definition, container, and port where production traffic is rerouted. For an EC2/On-premises deployment, this is an archive file that contains source content—source code, webpages, executable files, and deployment scripts—along with an AppSpec file. Revisions are stored in Amazon S3 buckets or GitHub repositories. For Amazon S3, a revision is uniquely identified by its Amazon S3 object key and its ETag, version, or both. For GitHub, a revision is uniquely identified by its commit ID. This guide also contains information to help you get details about the instances in your deployments, to make on-premises instances available for AWS CodeDeploy deployments, to get details about a Lambda function deployment, and to get details about Amazon ECS service deployments. AWS CodeDeploy Information Resources AWS CodeDeploy User Guide AWS CodeDeploy API Reference Guide AWS CLI Reference for AWS CodeDeploy AWS CodeDeploy Developer Forum

Amazon Comprehend is an AWS service for gaining insight into the content of documents. Use these actions to determine the topics contained in your documents, the topics they discuss, the predominant sentiment expressed in them, the predominant language used, and more.

The AWS Migration Hub API methods help to obtain server and application migration status and integrate your resource-specific migration tool by providing a programmatic interface to Migration Hub. Remember that you must set your AWS Migration Hub home region before you call any of these APIs, or a HomeRegionNotSetException error will be returned. Also, you must make the API calls while in your home region.

Azure resources can be locked to prevent other users in your organization from deleting or modifying resources.

Lambda Overview This is the Lambda API Reference. The Lambda Developer Guide provides additional information. For the service overview, see What is Lambda, and for information about how the service works, see Lambda: How it Works in the Lambda Developer Guide.

Use this REST API to get all the issues across an Azure Api Management service.

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.

This section provides documentation for the Amazon CodeGuru Reviewer API operations. CodeGuru Reviewer is a service that uses program analysis and machine learning to detect potential defects that are difficult for developers to find and recommends fixes in your Java and Python code. By proactively detecting and providing recommendations for addressing code defects and implementing best practices, CodeGuru Reviewer improves the overall quality and maintainability of your code base during the code review stage. For more information about CodeGuru Reviewer, see the Amazon CodeGuru Reviewer User Guide. To improve the security of your CodeGuru Reviewer API calls, you can establish a private connection between your VPC and CodeGuru Reviewer by creating an interface VPC endpoint. For more information, see CodeGuru Reviewer and interface VPC endpoints (Amazon Web Services PrivateLink) in the Amazon CodeGuru Reviewer User Guide.

The Admin Infrastructure Insights Management Client.

Amazon WorkMail is a secure, managed business email and calendaring service with support for existing desktop and mobile email clients. You can access your email, contacts, and calendars using Microsoft Outlook, your browser, or other native iOS and Android email applications. You can integrate WorkMail with your existing corporate directory and control both the keys that encrypt your data and the location in which your data is stored. The WorkMail API is designed for the following scenarios: Listing and describing organizations Managing users Managing groups Managing resources All WorkMail API operations are Amazon-authenticated and certificate-signed. They not only require the use of the AWS SDK, but also allow for the exclusive use of AWS Identity and Access Management users and roles to help facilitate access, trust, and permission policies. By creating a role and allowing an IAM user to access the WorkMail site, the IAM user gains full administrative visibility into the entire WorkMail organization (or as set in the IAM policy). This includes, but is not limited to, the ability to create, update, and delete users, groups, and resources. This allows developers to perform the scenarios listed above, as well as give users the ability to grant access on a selective basis using the IAM model.

Catalog API actions allow you to manage your entities through list, describe, and update capabilities. An entity can be a product or an offer on AWS Marketplace. You can automate your entity update process by integrating the AWS Marketplace Catalog API with your AWS Marketplace product build or deployment pipelines. You can also create your own applications on top of the Catalog API to manage your products on AWS Marketplace.

Use these REST APIs for performing retrieving a collection of policy snippets available in Azure API Management deployment.

Amazon Kinesis Data Analytics is a fully managed service that you can use to process and analyze streaming data using Java, SQL, or Scala. The service enables you to quickly author and run Java, SQL, or Scala code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.

Azure Application Insights client for Annotations for a component.