Mock sample for your project: Synthetics API

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.

Direct Connect links your internal network to an Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an Direct Connect router. With this connection in place, you can create virtual interfaces directly to the Cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all Regions except the China (Beijing) and (China) Ningxia Regions. Amazon Web Services resources in the China Regions can only be accessed through locations associated with those Regions.

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.

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

Amazon ElastiCache Amazon ElastiCache is a web service that makes it easier to set up, operate, and scale a distributed cache in the cloud. With ElastiCache, customers get all of the benefits of a high-performance, in-memory cache with less of the administrative burden involved in launching and managing a distributed cache. The service makes setup, scaling, and cluster failure handling much simpler than in a self-managed cache deployment. In addition, through integration with Amazon CloudWatch, customers get enhanced visibility into the key performance statistics associated with their cache and can receive alarms if a part of their cache runs hot.

IoT data IoT data enables secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. It implements a broker for applications and things to publish messages over HTTP (Publish) and retrieve, update, and delete shadows. A shadow is a persistent representation of your things and their state in the Amazon Web Services cloud. Find the endpoint address for actions in IoT data by running this CLI command: aws iot describe-endpoint --endpoint-type iot:Data-ATS The service name used by Amazon Web ServicesSignature Version 4 to sign requests is: iotdevicegateway.

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

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.

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.

Config Config provides a way to keep track of the configurations of all the Amazon Web Services resources associated with your Amazon Web Services account. You can use Config to get the current and historical configurations of each Amazon Web Services resource and also to get information about the relationship between the resources. An Amazon Web Services resource can be an Amazon Compute Cloud (Amazon EC2) instance, an Elastic Block Store (EBS) volume, an elastic network Interface (ENI), or a security group. For a complete list of resources currently supported by Config, see Supported Amazon Web Services resources. You can access and manage Config through the Amazon Web Services Management Console, the Amazon Web Services Command Line Interface (Amazon Web Services CLI), the Config API, or the Amazon Web Services SDKs for Config. This reference guide contains documentation for the Config API and the Amazon Web Services CLI commands that you can use to manage Config. The Config API uses the Signature Version 4 protocol for signing requests. For more information about how to sign a request with this protocol, see Signature Version 4 Signing Process. For detailed information about Config features and their associated actions or commands, as well as how to work with Amazon Web Services Management Console, see What Is Config in the Config Developer Guide.

DAX is a managed caching service engineered for Amazon DynamoDB. DAX dramatically speeds up database reads by caching frequently-accessed data from DynamoDB, so applications can access that data with sub-millisecond latency. You can create a DAX cluster easily, using the AWS Management Console. With a few simple modifications to your code, your application can begin taking advantage of the DAX cluster and realize significant improvements in read performance.

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.

The Azure BatchAI Management API.

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.

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 retrieve a collection of Apis associated with a tag in Azure API Management deployment.

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.

Use these REST APIs to get the analytics reports associated with your Azure API Management deployment.

The WorkMail Message Flow API provides access to email messages as they are being sent and received by a WorkMail organization.

Pinpoint SMS and Voice Messaging public facing APIs

Amazon Connect Customer Profiles Welcome to the Amazon Connect Customer Profiles API Reference. This guide provides information about the Amazon Connect Customer Profiles API, including supported operations, data types, parameters, and schemas. Amazon Connect Customer Profiles is a unified customer profile for your contact center that has pre-built connectors powered by AppFlow that make it easy to combine customer information from third party applications, such as Salesforce (CRM), ServiceNow (ITSM), and your enterprise resource planning (ERP), with contact history from your Amazon Connect contact center. If you're new to Amazon Connect , you might find it helpful to also review the Amazon Connect Administrator Guide.

API for using the Azure IoT Hub Device Provisioning Service features.

Provides APIs for creating and managing Amazon Forecast resources.

The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.