Mock sample for your project: AWS Service Catalog API

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AWS Service Catalog

amazonaws.com

Version: 2015-12-10


Use this API in your project

Integrate third-party APIs faster by using "AWS Service Catalog API" ready-to-use mock sample. Mocking this API will help you accelerate your development lifecycles and improves your integration tests' quality and reliability by accounting for random failures, slow response time, etc.
It also helps reduce your dependency on third-party APIs: no more accounts to create, API keys to provision, accesses to configure, unplanned downtime, etc.

Description

AWS Service Catalog AWS Service Catalog enables organizations to create and manage catalogs of IT services that are approved for AWS. To get the most out of this documentation, you should be familiar with the terminology discussed in AWS Service Catalog Concepts.

Other APIs by amazonaws.com

AWS Support

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.

AWS IoT 1-Click Projects Service

The AWS IoT 1-Click Projects API Reference

Amazon Honeycode

Amazon Honeycode is a fully managed service that allows you to quickly build mobile and web apps for teams—without programming. Build Honeycode apps for managing almost anything, like projects, customers, operations, approvals, resources, and even your team.

Amazon GameLift

Amazon GameLift Service GameLift provides solutions for hosting session-based multiplayer game servers in the cloud, including tools for deploying, operating, and scaling game servers. Built on AWS global computing infrastructure, GameLift helps you deliver high-performance, high-reliability, low-cost game servers while dynamically scaling your resource usage to meet player demand. About GameLift solutions Get more information on these GameLift solutions in the GameLift Developer Guide. GameLift managed hosting -- GameLift offers a fully managed service to set up and maintain computing machines for hosting, manage game session and player session life cycle, and handle security, storage, and performance tracking. You can use automatic scaling tools to balance player demand and hosting costs, configure your game session management to minimize player latency, and add FlexMatch for matchmaking. Managed hosting with Realtime Servers -- With GameLift Realtime Servers, you can quickly configure and set up ready-to-go game servers for your game. Realtime Servers provides a game server framework with core GameLift infrastructure already built in. Then use the full range of GameLift managed hosting features, including FlexMatch, for your game. GameLift FleetIQ -- Use GameLift FleetIQ as a standalone service while hosting your games using EC2 instances and Auto Scaling groups. GameLift FleetIQ provides optimizations for game hosting, including boosting the viability of low-cost Spot Instances gaming. For a complete solution, pair the GameLift FleetIQ and FlexMatch standalone services. GameLift FlexMatch -- Add matchmaking to your game hosting solution. FlexMatch is a customizable matchmaking service for multiplayer games. Use FlexMatch as integrated with GameLift managed hosting or incorporate FlexMatch as a standalone service into your own hosting solution. About this API Reference This reference guide describes the low-level service API for Amazon GameLift. With each topic in this guide, you can find links to language-specific SDK guides and the AWS CLI reference. Useful links: GameLift API operations listed by tasks GameLift tools and resources

AWS IoT Greengrass V2

IoT Greengrass brings local compute, messaging, data management, sync, and ML inference capabilities to edge devices. This enables devices to collect and analyze data closer to the source of information, react autonomously to local events, and communicate securely with each other on local networks. Local devices can also communicate securely with Amazon Web Services IoT Core and export IoT data to the Amazon Web Services Cloud. IoT Greengrass developers can use Lambda functions and components to create and deploy applications to fleets of edge devices for local operation. IoT Greengrass Version 2 provides a new major version of the IoT Greengrass Core software, new APIs, and a new console. Use this API reference to learn how to use the IoT Greengrass V2 API operations to manage components, manage deployments, and core devices. For more information, see What is IoT Greengrass? in the IoT Greengrass V2 Developer Guide.

AWS IoT Events Data

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.

Amazon FSx

Amazon FSx is a fully managed service that makes it easy for storage and application administrators to launch and use shared file storage.

AWS IoT Analytics

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 EMR

Amazon EMR is a web service that makes it easier to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several Amazon Web Services services to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehouse management.

Amazon Elastic Container Registry Public

Amazon Elastic Container Registry Public Amazon Elastic Container Registry (Amazon ECR) is a managed container image registry service. Amazon ECR provides both public and private registries to host your container images. You can use the familiar Docker CLI, or their preferred client, to push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry for your Docker or Open Container Initiative (OCI) images. Amazon ECR supports public repositories with this API. For information about the Amazon ECR API for private repositories, see Amazon Elastic Container Registry API Reference.

Amazon Kinesis

Amazon Kinesis Data Streams Service API Reference Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.
Amazon MQ is a managed message broker service for Apache ActiveMQ and RabbitMQ that makes it easy to set up and operate message brokers in the cloud. A message broker allows software applications and components to communicate using various programming languages, operating systems, and formal messaging protocols.

Other APIs in the same category

AWS Secrets Manager

Amazon Web Services Secrets Manager Amazon Web Services Secrets Manager provides a service to enable you to store, manage, and retrieve, secrets. This guide provides descriptions of the Secrets Manager API. For more information about using this service, see the Amazon Web Services Secrets Manager User Guide. API Version This version of the Secrets Manager API Reference documents the Secrets Manager API version 2017-10-17. As an alternative to using the API, you can use one of the Amazon Web Services SDKs, which consist of libraries and sample code for various programming languages and platforms such as Java, Ruby, .NET, iOS, and Android. The SDKs provide a convenient way to create programmatic access to Amazon Web Services Secrets Manager. For example, the SDKs provide cryptographically signing requests, managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including downloading and installing them, see Tools for Amazon Web Services. We recommend you use the Amazon Web Services SDKs to make programmatic API calls to Secrets Manager. However, you also can use the Secrets Manager HTTP Query API to make direct calls to the Secrets Manager web service. To learn more about the Secrets Manager HTTP Query API, see Making Query Requests in the Amazon Web Services Secrets Manager User Guide. Secrets Manager API supports GET and POST requests for all actions, and doesn't require you to use GET for some actions and POST for others. However, GET requests are subject to the limitation size of a URL. Therefore, for operations that require larger sizes, use a POST request. Support and Feedback for Amazon Web Services Secrets Manager We welcome your feedback. Send your comments to [email protected], or post your feedback and questions in the Amazon Web Services Secrets Manager Discussion Forum. For more information about the Amazon Web Services Discussion Forums, see Forums Help. How examples are presented The JSON that Amazon Web Services Secrets Manager expects as your request parameters and the service returns as a response to HTTP query requests contain single, long strings without line breaks or white space formatting. The JSON shown in the examples displays the code formatted with both line breaks and white space to improve readability. When example input parameters can also cause long strings extending beyond the screen, you can insert line breaks to enhance readability. You should always submit the input as a single JSON text string. Logging API Requests Amazon Web Services Secrets Manager supports Amazon Web Services CloudTrail, a service that records Amazon Web Services API calls for your Amazon Web Services account and delivers log files to an Amazon S3 bucket. By using information that's collected by Amazon Web Services CloudTrail, you can determine the requests successfully made to Secrets Manager, who made the request, when it was made, and so on. For more about Amazon Web Services Secrets Manager and support for Amazon Web Services CloudTrail, see Logging Amazon Web Services Secrets Manager Events with Amazon Web Services CloudTrail in the Amazon Web Services Secrets Manager User Guide. To learn more about CloudTrail, including enabling it and find your log files, see the Amazon Web Services CloudTrail User Guide.

Custom Vision Training Client

microsoft.com

Amazon SageMaker Service

Provides APIs for creating and managing Amazon SageMaker resources. Other Resources: Amazon SageMaker Developer Guide Amazon Augmented AI Runtime API Reference

Amazon QuickSight

Amazon QuickSight API Reference Amazon QuickSight is a fully managed, serverless business intelligence service for the Amazon Web Services Cloud that makes it easy to extend data and insights to every user in your organization. This API reference contains documentation for a programming interface that you can use to manage Amazon QuickSight.

Amazon MemoryDB

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.

AWS Elemental MediaStore

An AWS Elemental MediaStore container is a namespace that holds folders and objects. You use a container endpoint to create, read, and delete objects.

Amazon Import/Export Snowball

AWS Snow Family is a petabyte-scale data transport solution that uses secure devices to transfer large amounts of data between your on-premises data centers and Amazon Simple Storage Service (Amazon S3). The Snow commands described here provide access to the same functionality that is available in the AWS Snow Family Management Console, which enables you to create and manage jobs for a Snow device. To transfer data locally with a Snow device, you'll need to use the Snowball Edge client or the Amazon S3 API Interface for Snowball or AWS OpsHub for Snow Family. For more information, see the User Guide.

FabricAdminClient

azure.com
Infrastructure role operation endpoints and objects.

AutomationManagement

azure.com

DiskResourceProviderClient

azure.com
The Disk Resource Provider Client.

Amazon CloudWatch

Amazon CloudWatch monitors your Amazon Web Services (Amazon Web Services) resources and the applications you run on Amazon Web Services in real time. You can use CloudWatch to collect and track metrics, which are the variables you want to measure for your resources and applications. CloudWatch alarms send notifications or automatically change the resources you are monitoring based on rules that you define. For example, you can monitor the CPU usage and disk reads and writes of your Amazon EC2 instances. Then, use this data to determine whether you should launch additional instances to handle increased load. You can also use this data to stop under-used instances to save money. In addition to monitoring the built-in metrics that come with Amazon Web Services, you can monitor your own custom metrics. With CloudWatch, you gain system-wide visibility into resource utilization, application performance, and operational health.

Text Analytics Client

The Text Analytics API is a suite of text analytics web services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. No training data is needed to use this API; just bring your text data. This API uses advanced natural language processing techniques to deliver best in class predictions. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview