Mock sample for your project: AWS MediaTailor API

Integrate with "AWS MediaTailor API" from amazonaws.com in no time with Mockoon's ready to use mock sample

AWS MediaTailor

amazonaws.com

Version: 2018-04-23


Use this API in your project

Integrate third-party APIs faster by using "AWS MediaTailor 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

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).

Other APIs by amazonaws.com

Amazon AppConfig

AWS AppConfig Use AWS AppConfig, a capability of AWS Systems Manager, to create, manage, and quickly deploy application configurations. AppConfig supports controlled deployments to applications of any size and includes built-in validation checks and monitoring. You can use AppConfig with applications hosted on Amazon EC2 instances, AWS Lambda, containers, mobile applications, or IoT devices. To prevent errors when deploying application configurations, especially for production systems where a simple typo could cause an unexpected outage, AppConfig includes validators. A validator provides a syntactic or semantic check to ensure that the configuration you want to deploy works as intended. To validate your application configuration data, you provide a schema or a Lambda function that runs against the configuration. The configuration deployment or update can only proceed when the configuration data is valid. During a configuration deployment, AppConfig monitors the application to ensure that the deployment is successful. If the system encounters an error, AppConfig rolls back the change to minimize impact for your application users. You can configure a deployment strategy for each application or environment that includes deployment criteria, including velocity, bake time, and alarms to monitor. Similar to error monitoring, if a deployment triggers an alarm, AppConfig automatically rolls back to the previous version. AppConfig supports multiple use cases. Here are some examples. Application tuning : Use AppConfig to carefully introduce changes to your application that can only be tested with production traffic. Feature toggle : Use AppConfig to turn on new features that require a timely deployment, such as a product launch or announcement. Allow list : Use AppConfig to allow premium subscribers to access paid content. Operational issues : Use AppConfig to reduce stress on your application when a dependency or other external factor impacts the system. This reference is intended to be used with the AWS AppConfig User Guide.

AWS Price List Service

Amazon Web Services Price List Service API (Amazon Web Services Price List Service) is a centralized and convenient way to programmatically query Amazon Web Services for services, products, and pricing information. The Amazon Web Services Price List Service uses standardized product attributes such as Location, Storage Class, and Operating System, and provides prices at the SKU level. You can use the Amazon Web Services Price List Service to build cost control and scenario planning tools, reconcile billing data, forecast future spend for budgeting purposes, and provide cost benefit analysis that compare your internal workloads with Amazon Web Services. Use GetServices without a service code to retrieve the service codes for all AWS services, then GetServices with a service code to retreive the attribute names for that service. After you have the service code and attribute names, you can use GetAttributeValues to see what values are available for an attribute. With the service code and an attribute name and value, you can use GetProducts to find specific products that you're interested in, such as an AmazonEC2 instance, with a Provisioned IOPS volumeType. Service Endpoint Amazon Web Services Price List Service API provides the following two endpoints: https://api.pricing.us-east-1.amazonaws.com https://api.pricing.ap-south-1.amazonaws.com

Amazon Augmented AI Runtime

Amazon Augmented AI (Amazon A2I) adds the benefit of human judgment to any machine learning application. When an AI application can't evaluate data with a high degree of confidence, human reviewers can take over. This human review is called a human review workflow. To create and start a human review workflow, you need three resources: a worker task template, a flow definition, and a human loop. For information about these resources and prerequisites for using Amazon A2I, see Get Started with Amazon Augmented AI in the Amazon SageMaker Developer Guide. This API reference includes information about API actions and data types that you can use to interact with Amazon A2I programmatically. Use this guide to: Start a human loop with the StartHumanLoop operation when using Amazon A2I with a custom task type. To learn more about the difference between custom and built-in task types, see Use Task Types. To learn how to start a human loop using this API, see Create and Start a Human Loop for a Custom Task Type in the Amazon SageMaker Developer Guide. Manage your human loops. You can list all human loops that you have created, describe individual human loops, and stop and delete human loops. To learn more, see Monitor and Manage Your Human Loop in the Amazon SageMaker Developer Guide. Amazon A2I integrates APIs from various AWS services to create and start human review workflows for those services. To learn how Amazon A2I uses these APIs, see Use APIs in Amazon A2I in the Amazon SageMaker Developer Guide.

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.

AWS Elemental MediaConvert

AWS Elemental MediaConvert

Amazon Kinesis Analytics

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.

Amazon Kinesis Video Signaling Channels

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.

Amazon Lightsail

Amazon Lightsail is the easiest way to get started with Amazon Web Services (AWS) for developers who need to build websites or web applications. It includes everything you need to launch your project quickly - instances (virtual private servers), container services, storage buckets, managed databases, SSD-based block storage, static IP addresses, load balancers, content delivery network (CDN) distributions, DNS management of registered domains, and resource snapshots (backups) - for a low, predictable monthly price. You can manage your Lightsail resources using the Lightsail console, Lightsail API, AWS Command Line Interface (AWS CLI), or SDKs. For more information about Lightsail concepts and tasks, see the Amazon Lightsail Developer Guide. This API Reference provides detailed information about the actions, data types, parameters, and errors of the Lightsail service. For more information about the supported AWS Regions, endpoints, and service quotas of the Lightsail service, see Amazon Lightsail Endpoints and Quotas in the AWS General Reference.

AWS Elemental MediaStore Data Plane

An AWS Elemental MediaStore asset is an object, similar to an object in the Amazon S3 service. Objects are the fundamental entities that are stored in AWS Elemental MediaStore.

Application Migration Service

The Application Migration Service service.

AWS MediaConnect

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Amazon Kinesis Analytics

Amazon Kinesis Analytics Overview This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation. This is the Amazon Kinesis Analytics v1 API Reference. The Amazon Kinesis Analytics Developer Guide provides additional information.

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