Mock sample for your project: AWS Outposts API

AWS CloudHSM Service This is documentation for AWS CloudHSM Classic. For more information, see AWS CloudHSM Classic FAQs, the AWS CloudHSM Classic User Guide, and the AWS CloudHSM Classic API Reference. For information about the current version of AWS CloudHSM, see AWS CloudHSM, the AWS CloudHSM User Guide, and the AWS CloudHSM API Reference.

Amazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance.

Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide. Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).

This is the Amazon Lookout for Metrics API Reference. For an introduction to the service with tutorials for getting started, visit Amazon Lookout for Metrics Developer Guide.

Kinesis Video Streams Signaling Service is a intermediate service that establishes a communication channel for discovering peers, transmitting offers and answers in order to establish peer-to-peer connection in webRTC technology.

AWS Elemental MediaPackage VOD

API for AWS Elemental MediaLive

The AWS Serverless Application Repository makes it easy for developers and enterprises to quickly find
and deploy serverless applications in the AWS Cloud. For more information about serverless applications,
see Serverless Computing and Applications on the AWS website. The AWS Serverless Application Repository is deeply integrated with the AWS Lambda console, so that developers of
all levels can get started with serverless computing without needing to learn anything new. You can use category
keywords to browse for applications such as web and mobile backends, data processing applications, or chatbots.
You can also search for applications by name, publisher, or event source. To use an application, you simply choose it,
configure any required fields, and deploy it with a few clicks. You can also easily publish applications, sharing them publicly with the community at large, or privately
within your team or across your organization. To publish a serverless application (or app), you can use the
AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs to upload the code. Along with the
code, you upload a simple manifest file, also known as the AWS Serverless Application Model (AWS SAM) template.
For more information about AWS SAM, see AWS Serverless Application Model (AWS SAM) on the AWS Labs
GitHub repository. The AWS Serverless Application Repository Developer Guide contains more information about the two developer
experiences available:
Consuming Applications – Browse for applications and view information about them, including
source code and readme files. Also install, configure, and deploy applications of your choosing.
Publishing Applications – Configure and upload applications to make them available to other
developers, and publish new versions of applications.

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.

Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS. Macie automates the discovery of sensitive data, such as PII and intellectual property, to provide you with insight into the data that your organization stores in AWS. Macie also provides an inventory of your Amazon S3 buckets, which it continually monitors for you. If Macie detects sensitive data or potential data access issues, it generates detailed findings for you to review and act upon as necessary.

AWS Elastic Beanstalk AWS Elastic Beanstalk makes it easy for you to create, deploy, and manage scalable, fault-tolerant applications running on the Amazon Web Services cloud. For more information about this product, go to the AWS Elastic Beanstalk details page. The location of the latest AWS Elastic Beanstalk WSDL is https://elasticbeanstalk.s3.amazonaws.com/doc/2010-12-01/AWSElasticBeanstalk.wsdl. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that enable you to access the API, go to Tools for Amazon Web Services. Endpoints For a list of region-specific endpoints that AWS Elastic Beanstalk supports, go to Regions and Endpoints in the Amazon Web Services Glossary.

Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS. Macie automates the discovery of sensitive data, such as PII and intellectual property, to provide you with insight into the data that your organization stores in AWS. Macie also provides an inventory of your Amazon S3 buckets, which it continually monitors for you. If Macie detects sensitive data or potential data access issues, it generates detailed findings for you to review and act upon as necessary.

The Amazon AppIntegrations service enables you to configure and reuse connections to external applications. For information about how you can use external applications with Amazon Connect, see Set up pre-built integrations in the Amazon Connect Administrator Guide.

Creates an Azure Data Lake Store filesystem client.

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 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.

Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.

Azure Bot Service is a platform for creating smart conversational agents.