Mock sample for your project: AWS Elemental MediaPackage API

Amazon AppStream 2.0 This is the Amazon AppStream 2.0 API Reference. This documentation provides descriptions and syntax for each of the actions and data types in AppStream 2.0. AppStream 2.0 is a fully managed, secure application streaming service that lets you stream desktop applications to users without rewriting applications. AppStream 2.0 manages the AWS resources that are required to host and run your applications, scales automatically, and provides access to your users on demand. You can call the AppStream 2.0 API operations by using an interface VPC endpoint (interface endpoint). For more information, see Access AppStream 2.0 API Operations and CLI Commands Through an Interface VPC Endpoint in the Amazon AppStream 2.0 Administration Guide. To learn more about AppStream 2.0, see the following resources: Amazon AppStream 2.0 product page Amazon AppStream 2.0 documentation

Amazon SES API v2 Welcome to the Amazon SES API v2 Reference. This guide provides information about the Amazon SES API v2, including supported operations, data types, parameters, and schemas. Amazon SES is an AWS service that you can use to send email messages to your customers. If you're new to Amazon SES API v2, you might find it helpful to also review the Amazon Simple Email Service Developer Guide. The Amazon SES Developer Guide provides information and code samples that demonstrate how to use Amazon SES API v2 features programmatically. The Amazon SES API v2 is available in several AWS Regions and it provides an endpoint for each of these Regions. For a list of all the Regions and endpoints where the API is currently available, see AWS Service Endpoints in the Amazon Web Services General Reference. To learn more about AWS Regions, see Managing AWS Regions in the Amazon Web Services General Reference. In each Region, AWS maintains multiple Availability Zones. These Availability Zones are physically isolated from each other, but are united by private, low-latency, high-throughput, and highly redundant network connections. These Availability Zones enable us to provide very high levels of availability and redundancy, while also minimizing latency. To learn more about the number of Availability Zones that are available in each Region, see AWS Global Infrastructure.

This is the AWS Proton Service API Reference. It provides descriptions, syntax and usage examples for each of the actions and data types for the AWS Proton service. The documentation for each action shows the Query API request parameters and the XML response. Alternatively, you can use the AWS CLI to access an API. For more information, see the AWS Command Line Interface User Guide. The AWS Proton service is a two-pronged automation framework. Administrators create service templates to provide standardized infrastructure and deployment tooling for serverless and container based applications. Developers, in turn, select from the available service templates to automate their application or service deployments. Because administrators define the infrastructure and tooling that AWS Proton deploys and manages, they need permissions to use all of the listed API operations. When developers select a specific infrastructure and tooling set, AWS Proton deploys their applications. To monitor their applications that are running on AWS Proton, developers need permissions to the service create, list, update and delete API operations and the service instance list and update API operations. To learn more about AWS Proton administration, see the AWS Proton Administrator Guide. To learn more about deploying serverless and containerized applications on AWS Proton, see the AWS Proton User Guide. Ensuring Idempotency When you make a mutating API request, the request typically returns a result before the asynchronous workflows of the operation are complete. Operations might also time out or encounter other server issues before they're complete, even if the request already returned a result. This might make it difficult to determine whether the request succeeded. Moreover, you might need to retry the request multiple times to ensure that the operation completes successfully. However, if the original request and the subsequent retries are successful, the operation occurs multiple times. This means that you might create more resources than you intended. Idempotency ensures that an API request action completes no more than one time. With an idempotent request, if the original request action completes successfully, any subsequent retries complete successfully without performing any further actions. However, the result might contain updated information, such as the current creation status. The following lists of APIs are grouped according to methods that ensure idempotency. Idempotent create APIs with a client token The API actions in this list support idempotency with the use of a client token. The corresponding AWS CLI commands also support idempotency using a client token. A client token is a unique, case-sensitive string of up to 64 ASCII characters. To make an idempotent API request using one of these actions, specify a client token in the request. We recommend that you don't reuse the same client token for other API requests. If you don’t provide a client token for these APIs, a default client token is automatically provided by SDKs. Given a request action that has succeeded: If you retry the request using the same client token and the same parameters, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If you retry the request using the same client token, but one or more of the parameters are different, the retry throws a ValidationException with an IdempotentParameterMismatch error. Client tokens expire eight hours after a request is made. If you retry the request with the expired token, a new resource is created. If the original resource is deleted and you retry the request, a new resource is created. Idempotent create APIs with a client token: CreateEnvironmentTemplateVersion CreateServiceTemplateVersion CreateEnvironmentAccountConnection Idempotent create APIs Given a request action that has succeeded: If you retry the request with an API from this group, and the original resource hasn't been modified, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If the original resource has been modified, the retry throws a ConflictException. If you retry with different input parameters, the retry throws a ValidationException with an IdempotentParameterMismatch error. Idempotent create APIs: CreateEnvironmentTemplate CreateServiceTemplate CreateEnvironment CreateService Idempotent delete APIs Given a request action that has succeeded: When you retry the request with an API from this group and the resource was deleted, its metadata is returned in the response. If you retry and the resource doesn't exist, the response is empty. In both cases, the retry succeeds. Idempotent delete APIs: DeleteEnvironmentTemplate DeleteEnvironmentTemplateVersion DeleteServiceTemplate DeleteServiceTemplateVersion DeleteEnvironmentAccountConnection Asynchronous idempotent delete APIs Given a request action that has succeeded: If you retry the request with an API from this group, if the original request delete operation status is DELETEINPROGRESS, the retry returns the resource detail data in the response without performing any further actions. If the original request delete operation is complete, a retry returns an empty response. Asynchronous idempotent delete APIs: DeleteEnvironment DeleteService

AWS Elemental MediaConvert

The Application Migration Service service.

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 Mobile Service provides mobile app and website developers with capabilities required to configure AWS resources and bootstrap their developer desktop projects with the necessary SDKs, constants, tools and samples to make use of those resources.

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.

Definition of the public APIs exposed by Amazon Machine Learning

You can use Amazon CloudWatch Logs to monitor, store, and access your log files from EC2 instances, CloudTrail, and other sources. You can then retrieve the associated log data from CloudWatch Logs using the CloudWatch console, CloudWatch Logs commands in the Amazon Web Services CLI, CloudWatch Logs API, or CloudWatch Logs SDK. You can use CloudWatch Logs to: Monitor logs from EC2 instances in real-time : You can use CloudWatch Logs to monitor applications and systems using log data. For example, CloudWatch Logs can track the number of errors that occur in your application logs and send you a notification whenever the rate of errors exceeds a threshold that you specify. CloudWatch Logs uses your log data for monitoring so no code changes are required. For example, you can monitor application logs for specific literal terms (such as "NullReferenceException") or count the number of occurrences of a literal term at a particular position in log data (such as "404" status codes in an Apache access log). When the term you are searching for is found, CloudWatch Logs reports the data to a CloudWatch metric that you specify. Monitor CloudTrail logged events : You can create alarms in CloudWatch and receive notifications of particular API activity as captured by CloudTrail. You can use the notification to perform troubleshooting. Archive log data : You can use CloudWatch Logs to store your log data in highly durable storage. You can change the log retention setting so that any log events older than this setting are automatically deleted. The CloudWatch Logs agent makes it easy to quickly send both rotated and non-rotated log data off of a host and into the log service. You can then access the raw log data when you need it.

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.

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

IP pool operation endpoints and objects.

Amazon Redshift Overview This is an interface reference for Amazon Redshift. It contains documentation for one of the programming or command line interfaces you can use to manage Amazon Redshift clusters. Note that Amazon Redshift is asynchronous, which means that some interfaces may require techniques, such as polling or asynchronous callback handlers, to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a change is applied immediately, on the next instance reboot, or during the next maintenance window. For a summary of the Amazon Redshift cluster management interfaces, go to Using the Amazon Redshift Management Interfaces. Amazon Redshift manages all the work of setting up, operating, and scaling a data warehouse: provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine. You can focus on using your data to acquire new insights for your business and customers. If you are a first-time user of Amazon Redshift, we recommend that you begin by reading the Amazon Redshift Getting Started Guide. If you are a database developer, the Amazon Redshift Database Developer Guide explains how to design, build, query, and maintain the databases that make up your data warehouse.

File share operation endpoints and objects.

Azure Customer Lockbox API Reference

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.

With Fleet Hub for AWS IoT Device Management you can build stand-alone web applications for monitoring the health of your device fleets. Fleet Hub for AWS IoT Device Management is in public preview and is subject to change.

Amazon API Gateway Amazon API Gateway helps developers deliver robust, secure, and scalable mobile and web application back ends. API Gateway allows developers to securely connect mobile and web applications to APIs that run on AWS Lambda, Amazon EC2, or other publicly addressable web services that are hosted outside of AWS.

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.

Elastic Load Balancing A load balancer distributes incoming traffic across targets, such as your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered targets and ensures that it routes traffic only to healthy targets. You configure your load balancer to accept incoming traffic by specifying one or more listeners, which are configured with a protocol and port number for connections from clients to the load balancer. You configure a target group with a protocol and port number for connections from the load balancer to the targets, and with health check settings to be used when checking the health status of the targets. Elastic Load Balancing supports the following types of load balancers: Application Load Balancers, Network Load Balancers, Gateway Load Balancers, and Classic Load Balancers. This reference covers the following load balancer types: Application Load Balancer - Operates at the application layer (layer 7) and supports HTTP and HTTPS. Network Load Balancer - Operates at the transport layer (layer 4) and supports TCP, TLS, and UDP. Gateway Load Balancer - Operates at the network layer (layer 3). For more information, see the Elastic Load Balancing User Guide. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds.

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 operations on Diagnostic entity associated with your Azure API Management deployment. Diagnostics are used to log requests/responses in the APIM proxy.