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AWS DataSync

AWS 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 AWS DataSync contains documentation for a programming interface that you can use to manage AWS DataSync.

DAX is a managed caching service engineered for Amazon DynamoDB. DAX dramatically speeds up database reads by caching frequently-accessed data from DynamoDB, so applications can access that data with sub-millisecond latency. You can create a DAX cluster easily, using the AWS Management Console. With a few simple modifications to your code, your application can begin taking advantage of the DAX cluster and realize significant improvements in read performance.

AWS Device Farm is a service that enables mobile app developers to test Android, iOS, and Fire OS apps on physical phones, tablets, and other devices in the cloud.

AWS Direct Connect links your internal network to an AWS Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an AWS Direct Connect router. With this connection in place, you can create virtual interfaces directly to the AWS cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all AWS Regions except the China (Beijing) and (China) Ningxia Regions. AWS resources in the China Regions can only be accessed through locations associated with those Regions.

AWS Application Discovery Service

AWS Application Discovery Service helps you plan application migration projects by automatically identifying servers, virtual machines (VMs), software, and software dependencies running in your on-premises data centers. Application Discovery Service also collects application performance data, which can help you assess the outcome of your migration. The data collected by Application Discovery Service is securely retained in an AWS-hosted and managed database in the cloud. You can export the data as a CSV or XML file into your preferred visualization tool or cloud-migration solution to plan your migration. For more information, see AWS Application Discovery Service FAQ.

Application Discovery Service offers two modes of operation:

  • Agentless discovery mode is recommended for environments that use VMware vCenter Server. This mode doesn't require you to install an agent on each host. Agentless discovery gathers server information regardless of the operating systems, which minimizes the time required for initial on-premises infrastructure assessment. Agentless discovery doesn't collect information about software and software dependencies. It also doesn't work in non-VMware environments.

  • Agent-based discovery mode collects a richer set of data than agentless discovery by using the AWS Application Discovery Agent, which you install on one or more hosts in your data center. The agent captures infrastructure and application information, including an inventory of installed software applications, system and process performance, resource utilization, and network dependencies between workloads. The information collected by agents is secured at rest and in transit to the Application Discovery Service database in the cloud.

We recommend that you use agent-based discovery for non-VMware environments and to collect information about software and software dependencies. You can also run agent-based and agentless discovery simultaneously. Use agentless discovery to quickly complete the initial infrastructure assessment and then install agents on select hosts.

Application Discovery Service integrates with application discovery solutions from AWS Partner Network (APN) partners. Third-party application discovery tools can query Application Discovery Service and write to the Application Discovery Service database using a public API. You can then import the data into either a visualization tool or cloud-migration solution.

Application Discovery Service doesn't gather sensitive information. All data is handled according to the AWS Privacy Policy. You can operate Application Discovery Service offline to inspect collected data before it is shared with the service.

This API reference provides descriptions, syntax, and usage examples for each of the actions and data types for Application Discovery Service. The topic for each action shows the API request parameters and the response. Alternatively, you can use one of the AWS SDKs to access an API that is tailored to the programming language or platform that you're using. For more information, see AWS SDKs.

This guide is intended for use with the AWS Application Discovery Service User Guide .

Amazon Data Lifecycle Manager

With Amazon Data Lifecycle Manager, you can manage the lifecycle of your AWS resources. You create lifecycle policies, which are used to automate operations on the specified resources.

Amazon DLM supports Amazon EBS volumes and snapshots. For information about using Amazon DLM with Amazon EBS, see Automating the Amazon EBS Snapshot Lifecycle in the Amazon EC2 User Guide.

AWS Database Migration Service

AWS Database Migration Service (AWS DMS) can migrate your data to and from the most widely used commercial and open-source databases such as Oracle, PostgreSQL, Microsoft SQL Server, Amazon Redshift, MariaDB, Amazon Aurora, MySQL, and SAP Adaptive Server Enterprise (ASE). The service supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to MySQL or SQL Server to PostgreSQL.

For more information about AWS DMS, see What Is AWS Database Migration Service? in the AWS Database Migration User Guide.

Amazon DocumentDB API documentation

AWS Directory Service

AWS Directory Service is a web service that makes it easy for you to setup and run directories in the AWS cloud, or connect your AWS resources with an existing on-premises Microsoft Active Directory. This guide provides detailed information about AWS Directory Service operations, data types, parameters, and errors. For information about AWS Directory Services features, see AWS Directory Service and the AWS Directory Service Administration Guide.

AWS provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, iOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to AWS Directory Service and other AWS services. For more information about the AWS SDKs, including how to download and install them, see Tools for Amazon Web Services.

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.

Amazon Elastic Compute Cloud

Amazon Elastic Compute Cloud (Amazon EC2) provides secure and resizable computing capacity in the AWS cloud. Using Amazon EC2 eliminates the need to invest in hardware up front, so you can develop and deploy applications faster.

To learn more about Amazon EC2, Amazon EBS, and Amazon VPC, see the following resources:

Amazon Elastic Container Registry (Amazon ECR) is a managed Docker registry service. Customers can use the familiar Docker CLI to push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry. Amazon ECR supports private Docker repositories with resource-based permissions using IAM so that specific users or Amazon EC2 instances can access repositories and images. Developers can use the Docker CLI to author and manage images.

Amazon Elastic Container Service

Amazon Elastic Container Service (Amazon ECS) is a highly scalable, fast, container management service that makes it easy to run, stop, and manage Docker containers on a cluster. You can host your cluster on a serverless infrastructure that is managed by Amazon ECS by launching your services or tasks using the Fargate launch type. For more control, you can host your tasks on a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances that you manage by using the EC2 launch type. For more information about launch types, see Amazon ECS Launch Types.

Amazon ECS lets you launch and stop container-based applications with simple API calls, allows you to get the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features.

You can use Amazon ECS to schedule the placement of containers across your cluster based on your resource needs, isolation policies, and availability requirements. Amazon ECS eliminates the need for you to operate your own cluster management and configuration management systems or worry about scaling your management infrastructure.

Amazon Elastic Container Service for Kubernetes (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on AWS 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.

AWS Elastic Beanstalk

AWS Elastic Beanstalk makes it easy for you to create, deploy, and manage scalable, fault-tolerant applications running on the Amazon Web Services cloud.

For more information about this product, go to the AWS Elastic Beanstalk details page. The location of the latest AWS Elastic Beanstalk WSDL is http://elasticbeanstalk.s3.amazonaws.com/doc/2010-12-01/AWSElasticBeanstalk.wsdl. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that enable you to access the API, go to Tools for Amazon Web Services.

Endpoints

For a list of region-specific endpoints that AWS Elastic Beanstalk supports, go to Regions and Endpoints in the Amazon Web Services Glossary.

Amazon Elastic File System

Amazon Elastic File System (Amazon EFS) provides simple, scalable file storage for use with Amazon EC2 instances in the AWS 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 User Guide.

Elastic Load Balancing

A load balancer can distribute incoming traffic across your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered instances and ensures that it routes traffic only to healthy instances. 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 and a protocol and port number for connections from the load balancer to the instances.

Elastic Load Balancing supports three types of load balancers: Application Load Balancers, Network Load Balancers, and Classic Load Balancers. You can select a load balancer based on your application needs. For more information, see the Elastic Load Balancing User Guide.

This reference covers the 2012-06-01 API, which supports Classic Load Balancers. The 2015-12-01 API supports Application Load Balancers and Network Load Balancers.

To get started, create a load balancer with one or more listeners using CreateLoadBalancer. Register your instances with the load balancer using RegisterInstancesWithLoadBalancer.

All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds with a 200 OK response code.

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, and Classic Load Balancers.

An Application Load Balancer makes routing and load balancing decisions at the application layer (HTTP/HTTPS). A Network Load Balancer makes routing and load balancing decisions at the transport layer (TCP/TLS). Both Application Load Balancers and Network Load Balancers can route requests to one or more ports on each EC2 instance or container instance in your virtual private cloud (VPC).

A Classic Load Balancer makes routing and load balancing decisions either at the transport layer (TCP/SSL) or the application layer (HTTP/HTTPS), and supports either EC2-Classic or a VPC. For more information, see the Elastic Load Balancing User Guide.

This reference covers the 2015-12-01 API, which supports Application Load Balancers and Network Load Balancers. The 2012-06-01 API supports Classic Load Balancers.

To get started, complete the following tasks:

  1. Create a load balancer using CreateLoadBalancer.

  2. Create a target group using CreateTargetGroup.

  3. Register targets for the target group using RegisterTargets.

  4. Create one or more listeners for your load balancer using CreateListener.

To delete a load balancer and its related resources, complete the following tasks:

  1. Delete the load balancer using DeleteLoadBalancer.

  2. Delete the target group using DeleteTargetGroup.

All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds.

Amazon EMR is a web service that makes it easy to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several AWS products to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehousing.

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