Mock sample for your project: AWS Elemental MediaPackage VOD API

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 API operations to create, read, update, and delete inputs and detector models, and to list their versions.

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

Amazon Managed Service for Prometheus

With Application Auto Scaling, you can configure automatic scaling for the following resources: Amazon AppStream 2.0 fleets Amazon Aurora Replicas Amazon Comprehend document classification and entity recognizer endpoints Amazon DynamoDB tables and global secondary indexes throughput capacity Amazon ECS services Amazon ElastiCache for Redis clusters (replication groups) Amazon EMR clusters Amazon Keyspaces (for Apache Cassandra) tables Lambda function provisioned concurrency Amazon Managed Streaming for Apache Kafka broker storage Amazon SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services API Summary The Application Auto Scaling service API includes three key sets of actions: Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets. Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history. Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

This is AWS WAF Classic documentation. For more information, see AWS WAF Classic in the developer guide. For the latest version of AWS WAF, use the AWS WAFV2 API and see the AWS WAF Developer Guide. With the latest version, AWS WAF has a single set of endpoints for regional and global use. This is the AWS WAF Classic API Reference for using AWS WAF Classic with Amazon CloudFront. The AWS WAF Classic actions and data types listed in the reference are available for protecting Amazon CloudFront distributions. You can use these actions and data types via the endpoint waf.amazonaws.com. This guide is for developers who need detailed information about the AWS WAF Classic API actions, data types, and errors. For detailed information about AWS WAF Classic features and an overview of how to use the AWS WAF Classic API, see the AWS WAF Classic in the developer guide.

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.

Amazon Web Services X-Ray provides APIs for managing debug traces and retrieving service maps and other data created by processing those traces.

AWS Step Functions AWS Step Functions is a service that lets you coordinate the components of distributed applications and microservices using visual workflows. You can use Step Functions to build applications from individual components, each of which performs a discrete function, or task, allowing you to scale and change applications quickly. Step Functions provides a console that helps visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step, and retries steps when there are errors, so your application executes predictably and in the right order every time. Step Functions logs the state of each step, so you can quickly diagnose and debug any issues. Step Functions manages operations and underlying infrastructure to ensure your application is available at any scale. You can run tasks on AWS, your own servers, or any system that has access to AWS. You can access and use Step Functions using the console, the AWS SDKs, or an HTTP API. For more information about Step Functions, see the AWS Step Functions Developer Guide .

Amazon API Gateway V2

AWS Amplify Admin API

Amazon DynamoDB Amazon DynamoDB Streams provides API actions for accessing streams and processing stream records. To learn more about application development with Streams, see Capturing Table Activity with DynamoDB Streams in the Amazon DynamoDB Developer Guide.

WAF This is the latest version of the WAF API, released in November, 2019. The names of the entities that you use to access this API, like endpoints and namespaces, all have the versioning information added, like "V2" or "v2", to distinguish from the prior version. We recommend migrating your resources to this version, because it has a number of significant improvements. If you used WAF prior to this release, you can't use this WAFV2 API to access any WAF resources that you created before. You can access your old rules, web ACLs, and other WAF resources only through the WAF Classic APIs. The WAF Classic APIs have retained the prior names, endpoints, and namespaces. For information, including how to migrate your WAF resources to this version, see the WAF Developer Guide. WAF is a web application firewall that lets you monitor the HTTP and HTTPS requests that are forwarded to Amazon CloudFront, an Amazon API Gateway REST API, an Application Load Balancer, or an AppSync GraphQL API. WAF also lets you control access to your content. Based on conditions that you specify, such as the IP addresses that requests originate from or the values of query strings, the Amazon API Gateway REST API, CloudFront distribution, the Application Load Balancer, or the AppSync GraphQL API responds to requests either with the requested content or with an HTTP 403 status code (Forbidden). You also can configure CloudFront to return a custom error page when a request is blocked. This API guide is for developers who need detailed information about WAF API actions, data types, and errors. For detailed information about WAF features and an overview of how to use WAF, see the WAF Developer Guide. You can make calls using the endpoints listed in WAF endpoints and quotas. For regional applications, you can use any of the endpoints in the list. A regional application can be an Application Load Balancer (ALB), an Amazon API Gateway REST API, or an AppSync GraphQL API. For Amazon CloudFront applications, you must use the API endpoint listed for US East (N. Virginia): us-east-1. Alternatively, you can use one of the Amazon Web Services SDKs to access an API that's tailored to the programming language or platform that you're using. For more information, see Amazon Web Services SDKs. We currently provide two versions of the WAF API: this API and the prior versions, the classic WAF APIs. This new API provides the same functionality as the older versions, with the following major improvements: You use one API for both global and regional applications. Where you need to distinguish the scope, you specify a Scope parameter and set it to CLOUDFRONT or REGIONAL. You can define a web ACL or rule group with a single call, and update it with a single call. You define all rule specifications in JSON format, and pass them to your rule group or web ACL calls. The limits WAF places on the use of rules more closely reflects the cost of running each type of rule. Rule groups include capacity settings, so you know the maximum cost of a rule group when you use it.

Dev Spaces REST API

DataSync DataSync is a managed data transfer service that makes it simpler for you to automate moving data between on-premises storage and Amazon Simple Storage Service (Amazon S3) or Amazon Elastic File System (Amazon EFS). This API interface reference for DataSync contains documentation for a programming interface that you can use to manage DataSync.

Welcome to the AWS Device Farm API documentation, which contains APIs for: Testing on desktop browsers Device Farm makes it possible for you to test your web applications on desktop browsers using Selenium. The APIs for desktop browser testing contain TestGrid in their names. For more information, see Testing Web Applications on Selenium with Device Farm. Testing on real mobile devices Device Farm makes it possible for you to test apps on physical phones, tablets, and other devices in the cloud. For more information, see the Device Farm Developer Guide.

Amazon Elastic File System Amazon Elastic File System (Amazon EFS) provides simple, scalable file storage for use with Amazon EC2 instances in the Amazon Web Services Cloud. With Amazon EFS, storage capacity is elastic, growing and shrinking automatically as you add and remove files, so your applications have the storage they need, when they need it. For more information, see the Amazon Elastic File System API Reference and the Amazon Elastic File System User Guide.

AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data. AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management. AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.

Logical network operation endpoints and objects.

Amazon DynamoDB Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database, so that you don't have to worry about hardware provisioning, setup and configuration, replication, software patching, or cluster scaling. With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic. You can scale up or scale down your tables' throughput capacity without downtime or performance degradation, and use the AWS Management Console to monitor resource utilization and performance metrics. DynamoDB automatically spreads the data and traffic for your tables over a sufficient number of servers to handle your throughput and storage requirements, while maintaining consistent and fast performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across multiple Availability Zones in an AWS region, providing built-in high availability and data durability.

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.

Amazon CloudWatch Synthetics You can use Amazon CloudWatch Synthetics to continually monitor your services. You can create and manage canaries, which are modular, lightweight scripts that monitor your endpoints and APIs from the outside-in. You can set up your canaries to run 24 hours a day, once per minute. The canaries help you check the availability and latency of your web services and troubleshoot anomalies by investigating load time data, screenshots of the UI, logs, and metrics. The canaries seamlessly integrate with CloudWatch ServiceLens to help you trace the causes of impacted nodes in your applications. For more information, see Using ServiceLens to Monitor the Health of Your Applications in the Amazon CloudWatch User Guide. Before you create and manage canaries, be aware of the security considerations. For more information, see Security Considerations for Synthetics Canaries.