Amazon Elastic File System Amazon Elastic File System (Amazon EFS) provides simple, scalable file storage for use with Amazon EC2 Linux and Mac 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 that 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 .
Elastic Inference public APIs. February 15, 2023: Starting April 15, 2023, AWS will not onboard new customers to Amazon Elastic Inference (EI), and will help current customers migrate their workloads to options that offer better price and performance. After April 15, 2023, new customers will not be able to launch instances with Amazon EI accelerators in Amazon SageMaker, Amazon ECS, or Amazon EC2. However, customers who have used Amazon EI at least once during the past 30-day period are considered current customers and will be able to continue using the service.
Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on Amazon Web Services without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS runs up-to-date versions of the open-source Kubernetes software, so you can use all the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or public clouds. This means that you can easily migrate any standard Kubernetes application to Amazon EKS without any code modification required.
Amazon ElastiCache Amazon ElastiCache is a web service that makes it easier to set up, operate, and scale a distributed cache in the cloud. With ElastiCache, customers get all of the benefits of a high-performance, in-memory cache with less of the administrative burden involved in launching and managing a distributed cache. The service makes setup, scaling, and cluster failure handling much simpler than in a self-managed cache deployment. In addition, through integration with Amazon CloudWatch, customers get enhanced visibility into the key performance statistics associated with their cache and can receive alarms if a part of their cache runs hot.
Amazon Elasticsearch Configuration Service Use the Amazon Elasticsearch Configuration API to create, configure, and manage Elasticsearch domains. For sample code that uses the Configuration API, see the Amazon Elasticsearch Service Developer Guide . The guide also contains sample code for sending signed HTTP requests to the Elasticsearch APIs . The endpoint for configuration service requests is region-specific: es. region .amazonaws.com. For example, es.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints .
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 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 shared id="EMR-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 EKSService Endpoints .
Amazon EventBridge helps you to respond to state changes in your Amazon Web Services resources. When your resources change state, they automatically send events to an event stream. You can create rules that match selected events in the stream and route them to targets to take action. You can also use rules to take action on a predetermined schedule. For example, you can configure rules to: Automatically invoke an Lambda function to update DNS entries when an event notifies you that Amazon EC2 instance enters the running state. Direct specific API records from CloudTrail to an Amazon Kinesis data stream for detailed analysis of potential security or availability risks. Periodically invoke a built-in target to create a snapshot of an Amazon EBS volume. For more information about the features of Amazon EventBridge, see the Amazon EventBridge User Guide .
This is the Amazon Fraud Detector API Reference. This guide is for developers who need detailed information about Amazon Fraud Detector API actions, data types, and errors. For more information about Amazon Fraud Detector features, see the Amazon Fraud Detector User Guide . We provide the Query API as well as AWS software development kits (SDK) for Amazon Fraud Detector in Java and Python programming languages. The Amazon Fraud Detector Query API provides HTTPS requests that use the HTTP verb GET or POST and a Query parameter Action . AWS SDK provides libraries, sample code, tutorials, and other resources for software developers who prefer to build applications using language-specific APIs instead of submitting a request over HTTP or HTTPS. These libraries provide basic functions that automatically take care of tasks such as cryptographically signing your requests, retrying requests, and handling error responses, so that it is easier for you to get started. For more information about the AWS SDKs, see Tools to build on AWS .
Amazon GameLift provides solutions for hosting session-based multiplayer game servers in the cloud, including tools for deploying, operating, and scaling game servers. Built on Amazon Web Services 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 Amazon GameLift solutions Get more information on these Amazon GameLift solutions in the Amazon GameLift Developer Guide . Amazon GameLift managed hosting -- Amazon 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 Amazon 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 Amazon GameLift infrastructure already built
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
Amazon GuardDuty is a continuous security monitoring service that analyzes and processes the following data sources: VPC flow logs, Amazon Web Services CloudTrail management event logs, CloudTrail S3 data event logs, EKS audit logs, DNS logs, and Amazon EBS volume data. It uses threat intelligence feeds, such as lists of malicious IPs and domains, and machine learning to identify unexpected, potentially unauthorized, and malicious activity within your Amazon Web Services environment. This can include issues like escalations of privileges, uses of exposed credentials, or communication with malicious IPs, domains, or presence of malware on your Amazon EC2 instances and container workloads. For example, GuardDuty can detect compromised EC2 instances and container workloads serving malware, or mining bitcoin. GuardDuty also monitors Amazon Web Services account access behavior for signs of compromise, such as unauthorized infrastructure deployments like EC2 instances deployed in a Region that has never been used, or unusual API calls like a password policy change to reduce password strength. GuardDuty informs you about the status of your Amazon Web Services environment by producing secu
Amazon HealthLake is a HIPAA eligibile service that allows customers to store, transform, query, and analyze their FHIR-formatted data in a consistent fashion in the cloud.
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.
The Amazon Web Services Snow Family provides a petabyte-scale data transport solution that uses secure devices to transfer large amounts of data between your on-premises data centers and Amazon Simple Storage Service (Amazon S3). The Snow Family commands described here provide access to the same functionality that is available in the Amazon Web Services Snow Family Management Console, which enables you to create and manage jobs for a Snow Family device. To transfer data locally with a Snow Family device, you'll need to use the Snowball Edge client or the Amazon S3 API Interface for Snowball or OpsHub for Snow Family. For more information, see the User Guide .
Amazon Inspector Amazon Inspector enables you to analyze the behavior of your AWS resources and to identify potential security issues. For more information, see Amazon Inspector User Guide .
Introduction The Amazon Interactive Video Service (IVS) API is REST compatible, using a standard HTTP API and an Amazon Web Services EventBridge event stream for responses. JSON is used for both requests and responses, including errors. The API is an Amazon Web Services regional service. For a list of supported regions and Amazon IVS HTTPS service endpoints, see the Amazon IVS page in the Amazon Web Services General Reference . All API request parameters and URLs are case sensitive. For a summary of notable documentation changes in each release, see Document History . Allowed Header Values Accept: application/json Accept-Encoding: gzip, deflate Content-Type: application/json Resources The following resources contain information about your IVS live stream (see Getting Started with Amazon IVS ): Channel — Stores configuration data related to your live stream. You first create a channel and then use the channel’s stream key to start your live stream. See the Channel endpoints for more information. Stream key — An identifier assigned by Amazon IVS when you create a channel, which is then used to authorize streaming. See the StreamKey endpoints for more information. Treat the stream key
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.
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 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.