Mock sample for your project: AWS Elemental MediaLive API

MemoryDB for Redis is a fully managed, Redis-compatible, in-memory database that delivers ultra-fast performance and Multi-AZ durability for modern applications built using microservices architectures. MemoryDB stores the entire database in-memory, enabling low latency and high throughput data access. It is compatible with Redis, a popular open source data store, enabling you to leverage Redis’ flexible and friendly data structures, APIs, and commands.

Amazon GameLift Service GameLift provides solutions for hosting session-based multiplayer game servers in the cloud, including tools for deploying, operating, and scaling game servers. Built on AWS global computing infrastructure, GameLift helps you deliver high-performance, high-reliability, low-cost game servers while dynamically scaling your resource usage to meet player demand. About GameLift solutions Get more information on these GameLift solutions in the GameLift Developer Guide. GameLift managed hosting -- GameLift offers a fully managed service to set up and maintain computing machines for hosting, manage game session and player session life cycle, and handle security, storage, and performance tracking. You can use automatic scaling tools to balance player demand and hosting costs, configure your game session management to minimize player latency, and add FlexMatch for matchmaking. Managed hosting with Realtime Servers -- With GameLift Realtime Servers, you can quickly configure and set up ready-to-go game servers for your game. Realtime Servers provides a game server framework with core GameLift infrastructure already built in. Then use the full range of GameLift managed hosting features, including FlexMatch, for your game. GameLift FleetIQ -- Use GameLift FleetIQ as a standalone service while hosting your games using EC2 instances and Auto Scaling groups. GameLift FleetIQ provides optimizations for game hosting, including boosting the viability of low-cost Spot Instances gaming. For a complete solution, pair the GameLift FleetIQ and FlexMatch standalone services. GameLift FlexMatch -- Add matchmaking to your game hosting solution. FlexMatch is a customizable matchmaking service for multiplayer games. Use FlexMatch as integrated with GameLift managed hosting or incorporate FlexMatch as a standalone service into your own hosting solution. About this API Reference This reference guide describes the low-level service API for Amazon GameLift. With each topic in this guide, you can find links to language-specific SDK guides and the AWS CLI reference. Useful links: GameLift API operations listed by tasks GameLift tools and resources

Amazon EMR is a web service that makes it easier to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several Amazon Web Services services to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehouse management.

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

Amazon CloudWatch Application Insights Amazon CloudWatch Application Insights is a service that helps you detect common problems with your applications. It enables you to pinpoint the source of issues in your applications (built with technologies such as Microsoft IIS, .NET, and Microsoft SQL Server), by providing key insights into detected problems. After you onboard your application, CloudWatch Application Insights identifies, recommends, and sets up metrics and logs. It continuously analyzes and correlates your metrics and logs for unusual behavior to surface actionable problems with your application. For example, if your application is slow and unresponsive and leading to HTTP 500 errors in your Application Load Balancer (ALB), Application Insights informs you that a memory pressure problem with your SQL Server database is occurring. It bases this analysis on impactful metrics and log errors.

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.

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

AWS App Runner AWS App Runner is an application service that provides a fast, simple, and cost-effective way to go directly from an existing container image or source code to a running service in the AWS cloud in seconds. You don't need to learn new technologies, decide which compute service to use, or understand how to provision and configure AWS resources. App Runner connects directly to your container registry or source code repository. It provides an automatic delivery pipeline with fully managed operations, high performance, scalability, and security. For more information about App Runner, see the AWS App Runner Developer Guide. For release information, see the AWS App Runner Release Notes. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that you can use to access the API, see Tools for Amazon Web Services. Endpoints For a list of Region-specific endpoints that App Runner supports, see AWS App Runner endpoints and quotas in the AWS General Reference.

Amazon EC2 Auto Scaling Amazon EC2 Auto Scaling is designed to automatically launch or terminate EC2 instances based on user-defined scaling policies, scheduled actions, and health checks. For more information about Amazon EC2 Auto Scaling, see the Amazon EC2 Auto Scaling User Guide. For information about granting IAM users required permissions for calls to Amazon EC2 Auto Scaling, see Granting IAM users required permissions for Amazon EC2 Auto Scaling resources in the Amazon EC2 Auto Scaling API Reference.

Amazon Athena is an interactive query service that lets you use standard SQL to analyze data directly in Amazon S3. You can point Athena at your data in Amazon S3 and run ad-hoc queries and get results in seconds. Athena is serverless, so there is no infrastructure to set up or manage. You pay only for the queries you run. Athena scales automatically—executing queries in parallel—so results are fast, even with large datasets and complex queries. For more information, see What is Amazon Athena in the Amazon Athena User Guide. If you connect to Athena using the JDBC driver, use version 1.1.0 of the driver or later with the Amazon Athena API. Earlier version drivers do not support the API. For more information and to download the driver, see Accessing Amazon Athena with JDBC. For code samples using the Amazon Web Services SDK for Java, see Examples and Code Samples in the Amazon Athena User Guide.

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.

Alexa for Business helps you use Alexa in your organization. Alexa for Business provides you with the tools to manage Alexa devices, enroll your users, and assign skills, at scale. You can build your own context-aware voice skills using the Alexa Skills Kit and the Alexa for Business API operations. You can also make these available as private skills for your organization. Alexa for Business makes it efficient to voice-enable your products and services, thus providing context-aware voice experiences for your customers. Device makers building with the Alexa Voice Service (AVS) can create fully integrated solutions, register their products with Alexa for Business, and manage them as shared devices in their organization.

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.

Application operation results.

Amazon WorkSpaces Service Amazon WorkSpaces enables you to provision virtual, cloud-based Microsoft Windows and Amazon Linux desktops for your users.

Use these REST APIs for performing operations on Property entity associated with your Azure API Management deployment. API Management policies are a powerful capability of the system that allow the publisher to change the behavior of the API through configuration. Policies are a collection of statements that are executed sequentially on the request or response of an API. Policy statements can be constructed using literal text values, policy expressions, and properties. Each API Management service instance has a properties collection of key/value pairs that are global to the service instance. These properties can be used to manage constant string values across all API configuration and policies.

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS. Amazon EMR containers is the API name for Amazon EMR on EKS. The emr-containers prefix is used in the following scenarios: It is the prefix in the CLI commands for Amazon EMR on EKS. For example, aws emr-containers start-job-run. It is the prefix before IAM policy actions for Amazon EMR on EKS. For example,"Action": [ "emr-containers:StartJobRun"]. For more information, see Policy actions for Amazon EMR on EKS. It is the prefix used in Amazon EMR on EKS service endpoints. For example, emr-containers.us-east-2.amazonaws.com. For more information, see Amazon EMR on EKS Service Endpoints.

Systems Manager Incident Manager is an incident management console designed to help users mitigate and recover from incidents affecting their Amazon Web Services-hosted applications. An incident is any unplanned interruption or reduction in quality of services. Incident Manager increases incident resolution by notifying responders of impact, highlighting relevant troubleshooting data, and providing collaboration tools to get services back up and running. To achieve the primary goal of reducing the time-to-resolution of critical incidents, Incident Manager automates response plans and enables responder team escalation.

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.

MemoryDB for Redis is a fully managed, Redis-compatible, in-memory database that delivers ultra-fast performance and Multi-AZ durability for modern applications built using microservices architectures. MemoryDB stores the entire database in-memory, enabling low latency and high throughput data access. It is compatible with Redis, a popular open source data store, enabling you to leverage Redis’ flexible and friendly data structures, APIs, and commands.

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.

Azure Application Insights client for web test locations.

Key Management Service Key Management Service (KMS) is an encryption and key management web service. This guide describes the KMS operations that you can call programmatically. For general information about KMS, see the Key Management Service Developer Guide . KMS is replacing the term customer master key (CMK) with KMS key and KMS key. The concept has not changed. To prevent breaking changes, KMS is keeping some variations of this term. Amazon Web Services provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, macOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to KMS and other Amazon Web Services services. For example, the SDKs take care of tasks such as signing requests (see below), managing errors, and retrying requests automatically. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools for Amazon Web Services. We recommend that you use the Amazon Web Services SDKs to make programmatic API calls to KMS. Clients must support TLS (Transport Layer Security) 1.0. We recommend TLS 1.2. Clients must also support cipher suites with Perfect Forward Secrecy (PFS) such as Ephemeral Diffie-Hellman (DHE) or Elliptic Curve Ephemeral Diffie-Hellman (ECDHE). Most modern systems such as Java 7 and later support these modes. Signing Requests Requests must be signed by using an access key ID and a secret access key. We strongly recommend that you do not use your Amazon Web Services account (root) access key ID and secret key for everyday work with KMS. Instead, use the access key ID and secret access key for an IAM user. You can also use the Amazon Web Services Security Token Service to generate temporary security credentials that you can use to sign requests. All KMS operations require Signature Version 4. Logging API Requests KMS supports CloudTrail, a service that logs Amazon Web Services API calls and related events for your Amazon Web Services account and delivers them to an Amazon S3 bucket that you specify. By using the information collected by CloudTrail, you can determine what requests were made to KMS, who made the request, when it was made, and so on. To learn more about CloudTrail, including how to turn it on and find your log files, see the CloudTrail User Guide. Additional Resources For more information about credentials and request signing, see the following: Amazon Web Services Security Credentials - This topic provides general information about the types of credentials used to access Amazon Web Services. Temporary Security Credentials - This section of the IAM User Guide describes how to create and use temporary security credentials. Signature Version 4 Signing Process - This set of topics walks you through the process of signing a request using an access key ID and a secret access key. Commonly Used API Operations Of the API operations discussed in this guide, the following will prove the most useful for most applications. You will likely perform operations other than these, such as creating keys and assigning policies, by using the console. Encrypt Decrypt GenerateDataKey GenerateDataKeyWithoutPlaintext

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These operations enable you to manage role definitions and role assignments. A role definition describes the set of actions that can be performed on resources. A role assignment grants access to Azure Active Directory users.